/* eslint-disable */

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            "doi": "10.16904/envidat.128",
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                    "description": "Meteorological parameters and present weather were measured for the duration of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign at the Weissfluhjoch at an elevation of 2700 m above sea level (a.s.l.), and in Davos Wolfgang and Kloster, two villages which are in the valley at 1600 m a.s.l. and 1170 m a.s.l., respectively. The mountain ridge Gotschna separates Davos Wolfgang in the South from Klosters in the North.  The deployed instruments were owned by ETH Zurich, Meteoswiss and TROPOS. \r\n\r\nAmbient temperature (°C), humidity (%), atmospheric pressure (hPa), solar radiation (W m-1) and wind direction (°) and speed (m s-1) were recorded at standard weather stations from Meteoswiss at Weissfluhjoch and Davos Wolfgang, and from TROPOS at Davos Wolfgang. Additionally, a present weather detector (PWD22, Vaisala) was installed at Klosters to measure the weather type, ambient ligth as well as intensity and amount of both liquid and solid precipitation (mm). \r\n\r\nRadiosondes were started in Davos Wolfgang to report height profiles of pressure, relative humidity and temperature.\r\nFurther profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121953_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
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                    "display_name": "RACLETS Field Campaign",
                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
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                    "display_name": "Meteorology",
                    "description": "Meteorological parameters and present weather were measured for the duration of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign at the Weissfluhjoch at an elevation of 2700 m above sea level (a.s.l.), and in Davos Wolfgang and Kloster, two villages which are in the valley at 1600 m a.s.l. and 1170 m a.s.l., respectively. The mountain ridge Gotschna separates Davos Wolfgang in the South from Klosters in the North.  The deployed instruments were owned by ETH Zurich, Meteoswiss and TROPOS. \r\n\r\nAmbient temperature (°C), humidity (%), atmospheric pressure (hPa), solar radiation (W m-1) and wind direction (°) and speed (m s-1) were recorded at standard weather stations from Meteoswiss at Weissfluhjoch and Davos Wolfgang, and from TROPOS at Davos Wolfgang. Additionally, a present weather detector (PWD22, Vaisala) was installed at Klosters to measure the weather type, ambient ligth as well as intensity and amount of both liquid and solid precipitation (mm). \r\n\r\nRadiosondes were started in Davos Wolfgang to report height profiles of pressure, relative humidity and temperature.\r\nFurther profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121953_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120017.589162RACLETSmeteologo.png",
                    "title": "Meteorology",
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                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
                    "title": "RACLETS Field Campaign",
                    "id": "ab759699-d40a-44c9-995f-c0e5aad1c2b5",
                    "name": "raclets-field-campaign"
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                    "description": "Site aerial photo from both Beatenberg stations. Source: Google. 2016. Site aerial photo from both Beatenberg stations. Retrieved November 11, 2016, from https://www.google.ch/maps",
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                    "display_name": "FOREST",
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                }
            ],
            "language": "en",
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            "date": "[{\"date\": \"1985-07-09\", \"date_type\": \"collected\", \"end_date\": \"2015-07-07\"}]",
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            "spatial_info": "Switzerland",
            "name": "scolytidae",
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            "notes": "Scolytidae data from all historic up to the recent projects (29.10.2019) of WSL, collected with various methods in forests of different types.\r\nData are provided on request to contact person against bilateral agreement.",
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            ],
            "title": "Scolytidae",
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        },
        {
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            "maintainer": "{\"affiliation\": \"WSL Institute for Snow and Avalanche Research SLF\", \"identifier\": \"0000-0003-3857-7449\", \"given_name\": \"\", \"email\": \"giulia.mazzotti@slf.ch\", \"name\": \"Giulia Mazzotti\"}",
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                "description": " The Research Unit investigates natural hazard processes in mountainous areas, in particular the triggering and propagation of floods, sediment transport, landslides, debris flows and rock fall. Process studies on the scale of slopes, channels and catchments form the basis for the development of simulation models and of hazard assessment procedures and for the design of countermeasures. To this end worldwide unique observation systems are developed, such as a debris flow balance and geophone systems for bedload transport. Damage and damaging processes due to frequent and extreme events are assessed as prerequisites for the risk-based and sustainable management of natural hazards.\r\n\r\nA second focus of the unit is on the estimation and prediction of snow and water resources, e.g. for hydropower production or early recognition of drought. The unit operates a snow hydrological service for federal and cantonal agencies and a drought information platform for a broad range of water users.\r\n\r\n__Further information__: https://www.wsl.ch/en/about-wsl/organization/research-units/mountain-hydrology.html",
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            "notes": "Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)\r\n\r\nThe generation of the data is described in:\r\n\r\nBühler, Y., Hafner, E. D., Zweifel, B., Zesiger, M., and Heisig, H.: Where are the avalanches? Rapid mapping of a large snow avalanche period with optical satellites, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-119, accepted for publication, 2019.\r\n\r\nAbstract. \r\nAccurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2). \r\n\r\nWe tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period. \r\n\r\nThis study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.\r\n\r\nKoordinate System: CH1903+ LV95 LN02",
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            "title": "SPOT6 Avalanche outlines 24 January 2018",
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                    "name": "surface precipitation",
                    "created": "2019-12-16T15:22:27.988752",
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                    "name": "minimum near surface air temperature",
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            ],
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            "language": "en",
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            "name": "chelsa_cmip5_ts",
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            "notes": "Predicting future climatic conditions at high spatial resolution is essential for many applications in science. Here we present data for monthly time series of precipitation and minimum and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation sums at ~5km spatial resolution globally for the years 2006-2100. We validated the performance of the downscaling algorithm by comparing model output with observed climates for the years 2006-2016. \r\n\r\nCHELSA_cmip5_ts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.\r\n",
            "owner_org": "8bdea9a0-ea8c-424f-8c27-a4a1f0c55f02",
            "related_datasets": "",
            "title": "High resolution monthly precipitation and temperature timeseries for the period 2006-2100",
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        {
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            "maintainer": "{\"affiliation\": \"Leibnitz Institute for Tropospheric Research (TROPOS)\", \"identifier\": \"\", \"given_name\": \"\", \"name\": \"Patric Seifert\", \"email\": \"seifert@tropos.de\"}",
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                "description": "The experimental and theoretical work of our research group is dedicated to the developement and application of measuring instruments for remote sensing of atmospheric processes. Our activities are aimed at the determination of optical and physical properties of aerosols and clouds as well as at the assesment of the general atmospheric state parameters (temperature, wind, moisture).\r\nThe working group has conducted more than 15 field experiments in key regions of climate research where it applies its techniques to understand the role of aerosols and clouds in the climate system. During RACLETS, the ground-based remote sensing working group participated with observations of the mobile Oceanet platform, which is usually deployed during cruises of the research vessel Polarstern. Oceanet carries a multiwavelength Raman polarization lidar and a microwave radiometer as well as standard meteorological sensors. During RACLETS, a 35-GHz cloud radar and a disdrometer were deployed in addition. This equipment was used to process synergies of the remote sensing observations via Cloudnet (http://cloudnet.fmi.fi).\r\n\r\nMore information on: https://www.tropos.de/en/institute/departments/remote-sensing-of-atmospheric-processes-new/ground-based-remote-sensing",
                "created": "2019-07-05T06:24:50.849528",
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            "metadata_created": "2019-10-09T10:39:41.058361",
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                {
                    "display_name": "Precipitation",
                    "description": "Rain or snow reaching the ground as precipitation were measured at a high elevation site and at two locations in the valley over the course of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign: Gotschnagrat (2285 m above sea level - a.s.l.), as well as Laret (1522 m a.s.l.), and Davos Wolfang (1630 m a.s.l.). The applied instruments were owned and operated by ETH Zurich, EPFL and TROPOS.\r\n\r\nThe fall velocity and size of hydrometeors were measured with disdrometers (Parsivel, OTT HydroMet), that are laser based optical systems to measure all types of precipitation, e.g. drizzle, rain, snow, hail and hybrid forms of these classes. The disdrotemer data was continously recording liquid precipitation in a particle size range of 0.2 to 8 mm, solid precipitation in a particle size range of 0.2 to 25 mm, with particle fall velocities between 0.2 and 20 m s-1. Precipitation was dicriminated into 32 size classes and corresponded to 32 particle velocity classes.  \r\n\r\nThe precipitation measurements were accompanied by [snow measurements](https://www.envidat.ch/group/about/snow) at Gotschnagrat and in Davos Wolfgang.   Instruments to measure [aerosol concentrations](https://www.envidat.ch/group/about/aerosols-raclets), [meteorological parameters](https://www.envidat.ch/group/about/meteorology), [wind profiles/velocities](https://www.envidat.ch/group/about/remote-sensing-raclets), and the [CloudNet station](https://www.envidat.ch/group/about/remote-sensing-raclets) were also located in Davos Wolfgang. \r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/IMG_8893_Scale.JPG)\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/IMG_8012_Scale.JPG)\r\n\r\nImages: Claudia Mignani\r\n",
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                    "title": "Precipitation",
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                    "name": "precipitation"
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                    "display_name": "RACLETS Field Campaign",
                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
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                    "description": "The data provided in the Excel sheet contain the following information for 55 wetlands of the canton of Zürich (Switzerland):\r\n-Species richness data for vascular plants and bryophytes classified as follows: (1) all vascular plant species; (2) wetlands specialists among vascular plants; (3) generalists, which were all non-specialist vascular plant species; (4) short-lived vascular plant specialists; (5) long-lived vascular plant specialists; (6) short-lived vascular plant generalists; (7) long-lived vascular plant generalists; (8) bryophyte species. \r\n-Area of all wetlands in 1850, 1900, 1950 and 2000\r\n-Wetland area within buffers with 2km radius with the center of the wetland as starting point\r\n-Mean indicator values according to Landolt et al. (2010) and the standard deviation of these indicator values based on presence-absence data of vascular plants. Indicator values for temperature, light availability, moisture, acidity, nutrients, amount of humus and soil aeration were considered.\r\n",
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            "notes": "This dataset includes data on species richness of vascular plants and bryophytes in 55 wetlands of the canton of Zürich (Switzerland) as well as recent and historic data on the area and connectivity of these 55 wetlands and was used for the paper Jamin A., Peintinger M., Gimmi U., Holderegger R., Bergamini A. (2020) Evidence for a possible extinction debt in Swiss wetland specialist plants. Ecology and Evolution.\r\nSpecies richness data are available for vascular plants and bryophytes. The field survey was carried out between June 5 and August 10, 2012. The survey covered all wetland (fen) types in the canton of Zürich. For data collection, at least half a day per wetland was spent searching for species. Within each wetland all different vegetation types were covered until no new species were found to get as complete species lists as possible. In the Excel file information on species richness of the following groups is provided: (1) all vascular plant species; (2) wetlands specialists among vascular plants; (3) generalists, which were all non-specialist vascular plant species; (4) short-lived vascular plant specialists; (5) long-lived vascular plant specialists; (6) short-lived vascular plant generalists; (7) long-lived vascular plant generalists; (8) bryophyte species. Specialist vascular plant species included all characteristic species listed in Appendix 1a of the wetland inventory of Switzerland (BUWAL, 1990). \r\nBased on the data of Gimmi et al. (2011), the area of all wetlands in 1850, 1900, 1950 and 2000 were determined as well as the wetland area within buffers 2km in radius with the center of the wetland as starting point. These data are also provided in the Excel sheet.\r\nMoreover, for each wetland mean indicator values according to Landolt et al. (2010) and the standard deviation of these indicator values based on presence-absence data of vascular plants were calculated and are provided in Excel sheet. Indicator values for temperature, light availability, moisture, acidity, nutrients, amount of humus and soil aeration were considered.\r\n",
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            "notes": "We used five different atmospheric turbulence datasets from four test sites, with these sites showing differences in their topographical characteristics. We chose one typical alpine test site with high topographical complexity (Weissfluhjoch, Davos, Switzerland) and three test sites consisting of one glacier site (Plaine Morte, Crans-Montana, Switzerland) and two polar sites (Greenland and Antarctica) representing a quasi-ideal site with homogeneous surface and quasi infinite fetch in all directions.\r\nThe turbulent sensible heat flux was calculated using the eddy-covariance method. Note that the sonic temperature fluctuations have been converted into virtual temperature fluctuations. \r\nThree-dimensional wind velocity and air temperature were processed using a linear detrending (Rannik and Vesala, 1999) and a planar fit approach (Massmann and Lee, 2002) to rotate the coordinate system. Air temperature, relative humidity and air pressure from weather stations were used to calculate air properties, which are required for the data processing. The weather stations are located in the immediate vicinity of the turbulence tower and are affected by the same air masses. Turbulence data were averaged to 30-min intervals, whilst changing to a 15-min time interval marginally affects the heat fluxes at the Weissfluhjoch test site (Mott et al., 2011). Note that we define a negative sensible heat flux as being directed towards the snow surface and a positive sensible heat flux as being directed upwards.\r\nThe selected datasets and corresponding test sites are briefly introduced below:\r\n\r\nWeissfluhjoch 2007 (WFJ07): A vertical set-up of two three-dimensional ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) was used at the traditional field site Weissfluhjoch (2540 m asl.) to measure three-dimensional wind velocity and air temperature at a frequency of 20 Hz. The sensors were mounted 3 m and 5 m above the ground and provided reliable data for 50 days between 11 February 2007 and 24 April 2007. Further information on the field campaign can be found in Stössel et al. (2010) and Mott et al. (2011).\r\n\r\nWeissfluhjoch 2011-13 (WFJ11): Three-dimensional wind velocity and air temperature were recorded at 5 m above the ground at a frequency of 10 Hz with a three-dimensional ultrasonic anemometer (CSAT3). The analysis was conducted for data obtained between February and March in the years 2011-13.\r\n \r\nPlaine Morte 2007 (PM07): Two three-dimensional ultrasonic anemometers (CSAT3) were installed on a horizontal boom facing opposite directions (west-north-west vs. east-south-east) at 3.75 m above the ground to measure air temperature and three-dimensional wind velocity at 20 Hz. The data were collected at the almost flat field site on the Plaine Morte glacier (2750 m asl.) near Crans-Montana, Switzerland from February to April 2007. High quality meteorological data were additionally recorded and used to force the model. A detailed description about the set-up at the Plaine Morte glacier can be found in Huwald et al. (2009) and Bou-Zeid et al. (2010).  \r\n\r\nGreenland 2000 (GR00): High-frequency three-dimensional ultrasonic anemometer measurements (CSAT3) were recorded at 50 Hz at the Summit Camp (72.3 °N, 38.8 °W, 3208 m asl.) located on the northern dome of the Greenland ice sheet. Data were collected at 1 m and 2 m above the snow surface during summer in 2000 and 2001. Additionally, meteorological measurements were obtained for the post processing and used to force the model. More information about the field campaign can be found in Cullen et al. (2007, 2014).\r\n\r\nAntarctica 2000 (AA00): A set-up of three vertical three-dimensional ultrasonic anemometers (DA-600, Kaijo Denki) were installed at Mizuho Station (70°42' S, 44°20' E, 2230 m asl.) in Eastern Antarctica at 0.2, 1 and 25 m and recorded turbulence data at a frequency of 100 Hz from October to November 2000. Longwave and shortwave radiation, relative humidity, air and snow surface temperature were additionally measured and used to force the model. More information about the field campaign can be found in Nishimura and Nemoto (2005).\r\n",
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                    "description": "The SwissForestLab will be established as a worldwide unique research platform and infrastructural network to assess the effects of a dynamically changing environment on forests and trees worldwide. \r\n\r\n### Key Topics of the Network Research: \r\nThe SwissForestLab will work on the most pressing and challenging topics in forest research: \r\n\r\n1.  Climate Change effects on forest ecosystems\r\n2.  Biodiversity and ecosystem functioning\r\n3.  Land-use change and its long-term legacy\r\n\r\nPresentation: http://www.wsl.ch/fe/walddynamik/projekte/irrigationpfynwald/Metadata/2015LWFPfynWorkshop/Gessler\r\n\r\nMore Information: http://intra.wsl.ch/forschung/swissforestlab/Information_SwissForestLab_EN\r\n",
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            "date": "[{\"date\": \"1968-01-01\", \"date_type\": \"created\", \"end_date\": \"2017-12-31\"}]",
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            "spatial_info": "Switzerland",
            "name": "longterm-hydrological-observatory-alptal-central-switzerland",
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            "notes": "This data set includes 50 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily resolution can be provided on demand.\r\nRunoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/de/ueber-die-wsl/versuchsanlagen-und-labors/naturgefahren-anlagen/wildbachforschung-im-alptal/gebietsbeschreibung.html.\r\nRunoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited. \r\nMeteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).\r\nSnow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.",
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            "title": "Longterm hydrological observatory Alptal (central Switzerland)",
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            "maintainer": "{\"affiliation\": \"University of Regensburg\", \"email\": \"lisa.huelsmann@ur.de\", \"identifier\": \"0000-0003-4252-2715\", \"given_name\": \"Lisa\", \"name\": \"Hülsmann\"}",
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                "description": "We study stand dynamics and how they can be influenced by man.  We thereby focus on the following topics:\r\n\r\n* Growth and yield research\r\n\r\n* Forest dynamics in forest reserves\r\n\r\n* Virgin forest research in the Ukraine\r\n\r\n* Adaptation of forest trees to climate change\r\n\r\n* Close-to-nature silvicultural strategies\r\n\r\n* Forest succession and young forest tending\r\n\r\n* Forest-ungulate interactions and browsing\r\n\r\nWe maintain and manage a net of long-term permanent plots and use the data in simulation models of forest dynamics. Our research contributes to an ecologically, economically and socially sustainable forest management.",
                "created": "2018-05-28T16:14:38.566274",
                "title": "Stand Dynamics and Silviculture",
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            "id": "3a492ec9-def3-4e75-9778-dc397f63264d",
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                    "description": "A set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory. \r\n\r\n## Meta data\r\n__Reserve:__ Name of the forest reserve\r\n\r\n__Plot:__ Permanent plot number\r\n\r\n## Tree data\r\n__Species:__ Latin species name (or species group, cf. _Quercus_ spp.)\r\n\r\n__y:__  Status of the tree with 0 = alive and 1 = dead\r\n\r\n__dt:__ Length of the mortality period (years)\r\n\r\n__DBH:__ Diameter at breast height (mm) of the second inventory \r\n\r\n__relBAI:__ Annual relative basal area increment (-) calculated based on the first and the second DBH measurement as the compound annual growth rate of the trees basal area\r\n\r\n## Stand data\r\n_All stand variables were calculated for the second inventory._\r\n\r\n__mDBH:__ Mean diameter at breast height (mm)\r\n\r\n__iqrDBH:__ Interquartile range of diameter at breast height (mm)\r\n\r\n__BA:__ Basal area per hectare (m2 ha-1)\r\n\r\n__N:__ Number of trees per hectare (ha-1)\r\n\r\n## Climate data\r\n_Both climate variables were calculated for the period between the second and the third inventory._\r\n\r\n__P:__ Mean annual precipitation sum (mm)\r\n\r\n__mT:__ Mean annual air temperature (°C)\r\n",
                    "name": "Calibration data",
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                    "created": "2017-11-15T16:20:18.175895",
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                    "state": "active",
                    "display_name": "EMPIRICAL MORTALITY MODELS",
                    "id": "bf9b161a-4092-46db-a178-5a80dd0db807",
                    "name": "EMPIRICAL MORTALITY MODELS"
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                    "state": "active",
                    "display_name": "FOREST RESERVES",
                    "id": "471aaba9-254b-4e64-9f6e-4168bf2435af",
                    "name": "FOREST RESERVES"
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                    "state": "active",
                    "display_name": "INVENTORY DATA",
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                    "state": "active",
                    "display_name": "TREE GROWTH",
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            ],
            "language": "en",
            "doi": "10.16904/envidat.27",
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            "creator_user_id": "89c3d23b-712b-465e-984e-ab996e347a00",
            "date": "[{\"date\": \"2017-11-15\", \"date_type\": \"created\", \"end_date\": \"\"}]",
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            "spatial_info": "Switzerland, Germany (Lower Saxony)",
            "name": "10-16904-envidat-27",
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            "url": null,
            "notes": "The dataset comprises > 90 000 records from inventories in 54 strict forest reserves in [Switzerland](https://www.wsl.ch/de/wald/biodiversitaet-naturschutz-urwald/naturwaldreservate.html) and [Lower Saxony / Germany](http://naturwaelder.de/) along a considerable environmental gradient. It was used to develop parsimonious, species-specific mortality models for 18 European tree species based on tree size and growth as well as additional covariates on stand structure and climate. \r\n\r\n## Inventory data\r\nMeasurements had been conducted repeatedly on up to 14 permanent plots per reserve for up to 60 years with re-measurement intervals of 4 - 27 years. The permanent plots vary in size between 0.03 and 3.47 ha. The inventories provide diameter measurements at breast height (DBH) and information on the species and status (alive or dead) of trees with DBH ≥ 4 cm for Switzerland and ≥ 7 cm for Germany. \r\n\r\n## Data selection\r\nWe excluded three permanent plots where at least 80 % of the trees died during an interval of 10 years, and mortality could be clearly assigned to a disturbance agent. Mortality in the remaining stands was rather low, with a mean annual mortality rate of 1.5 % and strong variation between plots from 0 to 6.5 % (assessed for trees of all species with DBH ≥ 7 cm).\r\nWe only used data from permanent plots with at least 20 trees per species to obtain reliable plot-level mortality rates even for species with low mortality rates (about 5 % during 10 years), and selected tree species occurring on at least 10 plots to cover sufficient ecological gradients. This led to a dataset of 197 permanent plots and 18 tree or shrub species: _Abies alba_ Mill., _Acer campestre_ L., _Acer pseudoplatanus_ L., _Alnus incana_ Moench., _Betula pendula_ Roth, _Carpinus betulus_ L., _Cornus mas_ L., _Corylus avellana_ L., _Fagus sylvatica_ L., _Fraxinus excelsior_ L., _Picea abies_ (L.) Karst, _Pinus mugo_ Turra, _Pinus sylvestris_ L., _Quercus pubescens_ Willd., _Quercus_ spp. (_Q. petraea_ Liebl. and _Q. robur_ L.; not properly differentiated in the Swiss inventories), _Sorbus aria_ Crantz, _Tilia cordata_ Mill. and _Ulmus glabra_ Huds.. \r\n\r\n## Predictors of tree mortality\r\nWe considered tree size and growth as key indicators for mortality risk. Radial stem growth between the first and second inventory and DBH at the second inventory were used to predict tree status (alive or dead) at the third inventory. To this end, the annual relative basal area increment (relBAI) was calculated as the compound annual growth rate of the trees basal area. Additional covariates on stand structure and climate comprise mean annual precipitation sum (P), mean annual air temperature (mT), the mean and the interquartile range of DBH (mDBH, iqrDBH), basal area (BA) and the number of trees (N) per hectare. \r\n\r\n## Further information\r\nFor further information, refer to Hülsmann _et al_. (in press) How to kill a tree – Empirical mortality models for eighteen species and their performance in a dynamic forest model. _Ecological Applications_. ",
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            "title": "Calibration data for empirical mortality models of 18 European tree species",
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            "maintainer": "{\"affiliation\": \"WSL\", \"identifier\": \"A-9836-2012\", \"given_name\": \"Anita\", \"email\": \"anita.risch@wsl.ch\", \"name\": \"Risch\"}",
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                "description": "We are studying the distribution of and interactions among producers, consumers as well as decomposers and between these communities and their environment. We focus on food webs in real world ecosystems and thus mainly sample our data during experimental field campaigns. Data collection under controlled conditions in the greenhouse or experimental garden are, however, common add-ons hereby. We are mainly interested in the functioning of natural ecosystems and often conduct research in National Parks around the world. Our main study area is, however, the Swiss National Park. While working on basic research questions, we regularly consider applied aspects that are related to protecting or conserving endangered ecosystems.\r\n\r\nExamples of research question of our research group assesses are:\r\n\r\nHow is species loss related to ecosystem processes and functions? Which species or species groups are particularly relevant for ecosystem functioning? Which effects are expected with the loss of such important species groups? How are aboveground organisms interacting with belowground organisms? Which abiotic and biotic conditions favor diverse ecosystems? Is global change (for example eutrophication, habitat fragmentation, climate) a thread for diverse ecosystems? How can diverse ecosystems be protected?",
                "created": "2018-04-20T09:51:26.756810",
                "title": "Plant-Animal Interactions",
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            "publication": "{\"publisher\": \"WSL\", \"publication_year\": \"2018\"}",
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            "author": "[{\"name\": \"Risch\", \"affiliation\": \"WSL\", \"affiliation_03\": \"\", \"given_name\": \"Anita\", \"identifier\": \"A-9836-2012\", \"email\": \"anita.risch@wsl.ch\", \"affiliation_02\": \"\"}, {\"name\": \"Schuetz\", \"affiliation\": \"WSL\", \"affiliation_03\": \"\", \"given_name\": \"Martin\", \"identifier\": \"\", \"email\": \"martin.schuetz@wsl.ch\", \"affiliation_02\": \"\"}]",
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                    "description": "ID: Fence number\r\n\r\nYear\t:Year of sampling\r\n\r\nmean.CO2: soil respiration measured with PP-systems SRC-1 soil respriation chamber attached to a EGM-4 infrared gas analyser; units CO2 g m-2 h-1\r\n\r\nGrassland: Grasslands where fences were errected. Note that on large grasslands (STAB, GRIM, MING) 2 pairs of fences were errected (2 in short, 2 in tall-grass vegetation), on small grasslands (DADA, MARG, BOTS) only one pair of fences was errected (1 short-grass; one-tallgrass vegetation)\r\n\r\nFence: Fence number; un-even numbers on short-grass vegetation (1,3,5,7,9,11,13,15,17), even numbers on tall-grass vegetation (2,4,6,8,10,12,14,16,18)\r\n\r\nVegetation:\t1 = shortgrass vegetation, 2 = tall-grass vegetation (9 replicate fences on each vegetation type)\r\n\r\nTreatment\t: 1 = all herbivores grazing, 2 = large ungulates (red deer, chamois) excluded",
                    "name": "Soil respiration Switzerland",
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                    "display_name": "GRASSLAND",
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                    "state": "active",
                    "display_name": "SUBALPINE",
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            "doi": "10.16904/envidat.38",
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            "date": "[{\"date\": \"2009-06-01\", \"date_type\": \"collected\", \"end_date\": \"2013-09-15\"}]",
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            "name": "soil-respiration-exclosure-experiment",
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            "notes": "Location of data collection\r\nThe Swiss National Park (SNP) is located in the southeastern part of Switzerland, and covers an area of 170 km2, 50 km2 of which is forested, 33 km2 is occupied by alpine and 3 km2 by subalpine grasslands. Elevations range from 1350 to 3170 m a.s.l., and mean annual precipitation and temperature are 871 mm and 0.6°C measured at the Park’s weather station in Buffalora (1980 m a.s.l.) between 1960 and 2009 (MeteoSchweiz 2011). Founded in 1914, the SNP received minimal human disturbance for almost 100 years (no hunting, fishing, or camping, visitors are not allowed to leave the trails). Large (> 1 ha) homogeneous patches of short- and tall-grass vegetation characterize the subalpine grasslands. The average vegetation height of short-grass vegetation is 2 to 5 cm. Red fescue (Festuca rubra L.), quaking grass (Briza media L.) and common bent grass (Agrostis tenuis Sipthrob) are the predominating plant species in this vegetation type. Tussocks of evergreen sedge (Carex sempervirens Vill.) and mat grass (Nardus stricta L.) are predominant in the tall-grass vegetation, which averages 20 cm in vegetation height (Schütz and others 2006). Short-grass vegetation developed in areas where cattle and sheep rested (high nutrient input) during agricultural land-use (from 14th century until 1914); tall-grass vegetation developed in areas where cattle and sheep used to graze, but did not rest (Schütz and others 2003, 2006). Herbivores were shown to consume > 60% of the biomass in short-grass compared to < 20% in tall-grass vegetation (Schütz and others 2006). The herbivore community present in the SNP can be divided into four groups based on body size/weight: large [red deer (Cervus elaphus L.) and chamois (Rupricapra rupricapra L.); 30 - 150 kg], medium [marmot (Marmota marmota L.) and snow hare (Lepus timidus L.); 3 – 6 kg], and small vertebrate herbivores (small rodents: e.g. Clethrionomys spp., Microtus spp., Apodemus spp.; 30 – 100 g) as well as invertebrates (e.g. grasshoppers, caterpillars, cicadas, < 5 g). \r\n\r\nExperimental design\r\nWe selected 18 subalpine grassland sites (9 short-grass, 9 tall-grass vegetation). The sites were spread across the entire park on dolomite parent material at altitudes of 1975 to 2300 meters. At each site we established an exclosure network (fences) in spring 2009 (early June), immediately after snowmelt. Each exclosure network consisted of a total of five 2 × 3 m sized plots that progressively excluded the different herbivores listed above (further labeled according to the herbivore guilds that had access to the respective plots “All”, “Marmot/Mice/Invertebrates”, “Mice/Invertebrates”, “Invertebrates”, “None”). The “All” treatment was thus accessible to all herbivores, was not fenced and was located at least 5 m away from a 2.1 m tall and 7 × 9 m main fence that enclosed the other four treatments. This fence was constructed of 10 × 10 cm wooden posts and electrical equestrian tape (AGRARO ECO, Landi, Bern, Switzerland; 20 mm width) mounted at 0.7 m, 0.95 m, 1.2 m, 1.5 m and 2.1 m above the ground that were connected to a solar charged battery (AGRARO Sunpower S250, Landi, Bern, Switzerland). We also mounted non-electrically charged equestrian tape at 0.5 m to help exclude deer and chamois, yet allow marmots and hares to enter safely. Within each main fenced area we randomly established four 2 × 3 m plots: (1) The “Marmot/Mice/Invertebrates” plot remained unfenced, thus, with the exception of red deer and chamois, all herbivores were able to access the plot, (2) The “Mice/Invertebrates” plot consisted of a 90 cm high electric sheep fence (AGRARO Weidezaunnetz ECO, Landi, Bern, Switzerland; mesh size 10 × 10 cm) connected to the solar panel and excluded all medium sized mammals (marmots, hares), but provided access for small mammals and invertebrates, (3) The “Invertebrates” plot provided access for invertebrates only and was surrounded by 1 m high metal mesh (Hortima AG, Hausen, Schweiz; mesh size 2 × 2 cm), (4) The “None” plot was surrounded by a 1 m tall mosquito net (Sala Ferramenta AG, Biasca, Switzerland; mesh size 1.5 × 2 mm) to exclude all herbivores. This plot was covered with a roof constructed of a wooden frame lined with mosquito mesh that was mounted on the wooden corner posts. We also treated this plot with a biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) when needed to remove insects that might have entered during data collection or that hatched from the soil. \r\n\r\n!!! The here published data set only contains data for “All”, and “Marmot/Mice/Invertebrates” (= ungulates excluded) plots !!!\r\n\r\nData collection\r\nIn-situ soil CO2 emissions were measured with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA) on two randomly selected locations on one subplot within each of the 90 plots. For each measurement the soil chamber (15 cm high; 10 cm diameter) was placed on a permanently installed PVC collar (10 cm diameter) driven five centimeters into the soil at the beginning of the study (June 2009). The measurements were conducted between 0900 and 1700 hours every two weeks from early to early September 2009, 2010, 2011 and 2013. Freshly germinated plants growing within the PVC collars were removed prior to each measurement to avoid measuring plant respiration/photosynthesis. The two measurements collected per plot every two weeks were averaged. \r\n\r\nPlease acknowledge the funding of the study: funded by the Swiss National Science Foundation, SNF grant-no 31003A_122009/1 to Anita C. Risch, Martin Schütz and Flurin Filli\r\n",
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                "description": "We are studying the distribution of and interactions among producers, consumers as well as decomposers and between these communities and their environment. We focus on food webs in real world ecosystems and thus mainly sample our data during experimental field campaigns. Data collection under controlled conditions in the greenhouse or experimental garden are, however, common add-ons hereby. We are mainly interested in the functioning of natural ecosystems and often conduct research in National Parks around the world. Our main study area is, however, the Swiss National Park. While working on basic research questions, we regularly consider applied aspects that are related to protecting or conserving endangered ecosystems.\r\n\r\nExamples of research question of our research group assesses are:\r\n\r\nHow is species loss related to ecosystem processes and functions? Which species or species groups are particularly relevant for ecosystem functioning? Which effects are expected with the loss of such important species groups? How are aboveground organisms interacting with belowground organisms? Which abiotic and biotic conditions favor diverse ecosystems? Is global change (for example eutrophication, habitat fragmentation, climate) a thread for diverse ecosystems? How can diverse ecosystems be protected?",
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                    "description": "ID: Plot ID composited of Fence & Treatment number (90 plots total)\r\n\r\nGrassland: Name of the six subalpine grasslands where the exclosure setups were erected. In large grasslands (GRIM, MING, STAB), we established four hierarchical exclosure setups (two in short- and two in tall-grass vegetation), whereas in the small grasslands (BOTS, DADA, MARG) only one setup was erected per vegetation type. BOTS = Val dal Botsch, GRIM = Grimmels, MING = Val Mingér, STAB = Alp Stabelchod, DADA = Stabelchod da daint, MARG = Margunet\r\n\r\nFence: Number of exclosure setup (1 - 18). Note that uneven numbers (1,3,5,7,9,11,13,15,17) represent setups established on short-grass vegetation, even numbers (2,4,6,8,10,12,14,16,18) setups established in tall-grass vegetation\r\nVegetation\tVegetation type, 1 = short-grass vegetation, 2 = tall-grass vegetation; (9 replicate fences on each vegetation type)\r\nTreatment\tProgressive animal exclusion, numbers indicate which animals had access to the plot: 1 = Large/medium/small mammals, and invertebrates have access (\"L/M/S/I\"), 2 = Medium/small mammals, and invertebrates have access (“M/S/I”),  3 = Small mammals and invertebrates have access (“S/I”), 4 = Invertebrates have access (“I”), 5 =  No animals have access (“None”)\r\n\r\nBulkden:\tFine fraction soil bulk density (g cm-3)\r\n\r\nSoil.moist\t: Soil moisture (%)\r\n\r\nSoil.org.C: Rhizosphere soil C content (%)\r\n\r\npH: Soil pH\r\n\r\nNema.PC1: First principal component (PC1) of principal component analysis (PCA) of the soil nematode community composition\r\n\r\nNema.PC2: Second principal component (PC2) of principal component analysis (PCA) of the soil nematode community composition\r\n\r\nMicro.PC1: \tFirst principal component (PC1) of principal component analysis (PCA) of the soil microbial community composition\r\n\r\nMicro.PC2: Second principal component (PC2) of principal component analysis (PCA) of the soil microbial community composition\r\n\r\nAbv.Inv.PC1: First principal component (PC1) of principal component analysis (PCA) of the aboveground-dwelling invertebrate community composition\r\n\r\nAbv.Inv.PC2: Second principal component (PC2) of principal component analysis (PCA) of the aboveground-dwelling invertebrate community composition\r\n\r\nArthr.PC1: First principal component (PC1) of principal component analysis (PCA) of the soil arthropod community composition\r\n\r\nArthr.PC2: Second principal component (PC2) of principal component analysis (PCA) of the soil arthropod community composition\r\n\r\nPlant.PC1: First principal component (PC1) of principal component analysis (PCA) of the plant community composition\r\n\r\nPlant.PC2: Second principal component (PC2) of principal component analysis (PCA) of the plant community composition\r\n\r\nRoot.biomass: Root biomass (g m-2)\r\n\r\nMicro.biomass\t: Microbial biomass carbon (mg kg-1)\r\n\r\nPlant.richness: Plant species richness\r\n\r\nPlant.N: Plant tissue nitrogen content (%)\r\n\r\nSoil.N.min: Soil net nitrogen mineralisation (kg ha-1 season)\r\n\r\nSoil.resp: Soil carbon dioxide emissions (soil respiration; g m-2 h-1)",
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            "notes": "This dataset contains all data on which the following publication below is based.\r\n\r\n__Paper Citation:__\r\n > Risch AC, Ochoa-Hueso R, van der Putten WH, Bump JK, Busse MD, Frey B, Gwiazdowicz DJ, Page-Dumroese DS, Vandegehuchte ML, Zimmermann S, Schütz M. Size-dependent loss of aboveground animals differentially affects grassland ecosystem coupling and functions. 2018. Nature Communications 9: 3684.  [doi: 10.1038/s41467-018-06105-4](https://doi.org/10.1038/s41467-018-06105-4).\r\n\r\nPlease cite this paper together with the citation for the datafile.\r\n\r\n#Methods\r\n##Study sites \r\nThe experimental exclosure setups were installed within the SNP (IUCN category Ia preserve; Dudley 2008), in south-eastern Switzerland. The park covers 172 km2 of forests and subalpine and alpine grasslands along with scattered rock outcrops and scree slopes. The entire area has been protected from human impact (no hunting, fishing, camping or off-trail hiking) since 1914. Large, fairly homogenous patches of short- and tall-grass vegetation, which originate from different historical management and grazing regimes, cover the park’s subalpine grasslands entirely. Short-grass vegetation developed in areas where cattle used to rest (nutrient input) prior to the park’s foundation (14th century to 1914) (Schütz and others 2003, 2006) and is dominated by lawn grass species such as Festuca rubra L., Briza media L. and Agrostis capillaris L. (Schütz and others 2003, 2006). Today, this vegetation type is intensively grazed by diverse vertebrate and invertebrate communities that inhabit the park and consume up to 60% of the available biomass (Risch and others 2013). Tall-grass vegetation developed where cattle formerly grazed, but did not rest, and is dominated by rather nutrient-poor tussocks of Carex sempervirens Vill. and Nardus stricta L. (Schütz and others 2003, 2006). This vegetation type receives considerably less grazing, with only roughly 20% of the biomass consumed (Risch and others 2013). Consequently, the two vegetation types together represent a long-term trajectory of changes in grazing regimes. Underlying bedrock of all grasslands is dolomite, which renders these grasslands rather poor in nutrients regardless of former and current land-use regimes.\r\n##Experimental design\r\nTo progressively exclude aboveground vertebrate and invertebrate animals, we established 18 size-selective exclosure setups (nine in short-grass, nine in tall-grass vegetation) distributed over six subalpine grasslands across the SNP (Risch and others 2013, 2015). Elevation differences of exclosure locations did not exceed 350 m (between 1975 and 2300 m a.s.l.). The exclosures were established immediately after snowmelt in spring 2009 and were left in place for five consecutive growing seasons (until end of 2013). They were, however, temporarily dismantled every fall (late October after first snowfall) to protect them from avalanches. They were re-established in the same location every spring immediately after snowmelt. Each size-selective exclosure setup consisted of five plots (2 x 3 m) that progressively excluded aboveground vertebrates and invertebrates from large to small. The plots are labelled according to the guilds that had access to them “L/M/S/I”, “M/S/I”, “S/I”, “I”, “None”; L = large mammals, M = medium mammals, S = small mammals, I = invertebrates, None = no animals had access. As we only had permission to have the experimental setup in place for five consecutive growing seasons, the experiment had to be completely dismantled in the late fall of 2013 and all material removed from the SNP.\r\nOur exclosure design was aimed at excluding mammalian herbivores, but naturally also excluded the few medium and small mammalian predators, as well as the entire aboveground invertebrate food web. A total of 26 large to small mammal species can be found in the SNP, but large apex predators are missing (wolf, bear, lynx) . Reptiles, amphibians and birds are scarce to absent in the subalpine grasslands under study. Only two reptile species occur in the park and they are confined to rocky areas that warm up enough for them to survive. One frog species spawns in an isolated pond far from our grasslands. Only three bird species occasionally feed on the subalpine grasslands. Using game cameras (Moultrie 6MP Game Spy I-60 Infrared Digital Game Camera, Moultrie Feeders, Alabaster, AL, USA), we did observe that the medium- and small-sized mammals (marmot/hares and mice) were not afraid to enter the fences and feed on their designated plots. We never spotted reptiles, amphibians or birds on camera. We distinguished between 59 higher aboveground-dwelling invertebrate taxa that our size-selective exclosures excluded (see also methods for aboveground-dwelling invertebrates below). \r\nThe “L/M/S/I” plot (not fenced) was located at least 5 m from the 2.1 m tall and 7 x 9 m large main electrical fence that enclosed the other four plots. The bottom wire of this fence was mounted at 0.5 m height and was not electrified to enable safe access for medium and small mammals, while fencing out the large ones. Within each main fence, we randomly established four 2 x 3 m plots separated by 1-m wide walkways from one another and from the main fence line: 1) the “M/S/I” plots were unfenced, allowing access to all but the large mammals; 2) the “S/I” plots (10 x 10 cm electrical mesh fence) excluded all medium-sized mammals. Note that the bottom 10 cm of this fence remained non-electrified to enable safe access for small mammals; 3) the “I” plots (2 x 2 cm metal mesh fence) excluded all mammals. We double-folded the mesh at the bottom 50 cm to reduce the mesh size to smaller than 1 x 1 cm openings; and 4) the “None” plots were surrounded by a 1 m tall mosquito net (1.5 x 2 mm) to exclude all animals. The top of the plot was covered with a mosquito-meshed wooden frame mounted to the corner posts (roof). We treated these plots a few times with biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) to remove insects that might have entered during data collection or that hatched from the soil, but amounts were negligible and did not impact soil moisture conditions within these plots.\r\nTo assess whether the design of the “None” exclosure (mesh and roof) affected the response variables within the plots and, therefore, influenced the results, we established an additional six “micro-climate control” exclosures (one in each of the six grasslands) (Risch and others 2013, 2015). These exclosures were built as the “None” exclosures but were open at the bottom (20 cm) of the 3-m side of the fence facing away from the prevailing wind direction to allow invertebrates to enter. A 20-cm high and 3-m long strip of metal mesh was used to block access to small mammals. Thus, this construction allowed a comparable micro-climate to the “None” plots, but also a comparable feeding pressure by invertebrates to the “I” plots. We compared various properties within these exclosures against one another to assess if our construction altered the conditions in the “None” plots. We showed that differences in plant (e.g., vegetation height, aboveground biomass) and soil properties (e.g., soil temperature, moisture) found between the “I” and the “None” treatments were not due to the construction of the “None” exclosure, but a function of animal exclusions, although the amount of UV light reaching the plant canopy was significantly reduced (Risch and others 2013). \r\n##Aboveground invertebrate sampling\r\nAboveground invertebrates were sampled with two different methods to capture both ground- and plant-dwelling organisms: 1) we randomly placed two pitfall traps (67 mm in diameter, covered with a roof) filled with 20% propylene glycol in one 1 x 1 m subplot of the 2 x 3 m treatment plots in spring 2013 (May) and emptied them every two weeks until late September 2013 (Vandegehuchte and others 2017b, 2018). A pitfall trap consisted of a plastic cylinder (13 cm depth, 6.75 cm diameter). Within each cylinder we placed a 100 ml plastic vial with outer diameter 6.70 cm and on top of the cylinder we placed a plastic funnel to guide the invertebrates into the vials. Each trap was cover with a cone-shaped and transparent plastic roof to protect the trap from rain (Vandegehuchte and others 2017b, 2018). Note that in the “None” plots only one trap was placed as control to check for effectiveness of the exclosure. 2) We vacuumed all invertebrates from a 60 x 60 cm area on another 1 x 1 m subplot with a suction sampler (Vortis, Burkhard manufacturing CO, Ltd., Rickmansworth, Hertfordshire, UK) every month from June to September 2013 (Vandegehuchte and others 2017b, 2018). For this purpose, we quickly placed a square plastic frame (60 x 60 x 40 cm) with a closable mosquito mesh sleeve attached to the top edge into the plot from the outside. The suction sample was then inserted into through the sleeve and operated for 45 s to collect the invertebrates (Vandegehuchte and others 2017b, 2018). \r\nWe sorted the ≈100 000 individuals collected with both methods by hand and identified each individual morphologically to the lowest taxonomic level feasible (59 taxa, including orders, suborders, subfamilies, families; phylum for Mollusca). These taxa belonged to the following feeding types: 19 herbivores, 16 detritivores, 9 predators, 8 mixed feeders, 5 omnivores and 2 non-classified feeders (or not feeding as adults) (Vandegehuchte and others 2017b). We summed the numbers from the two pitfall traps and the suction sampling over the course of the 2013 season to represent the aboveground invertebrate abundance and community composition of a plot. Note: we did not specifically attempt to catch flying invertebrates with e.g., sticky traps, thus a few flying insects may have been missed with our vacuum sampling approach.\r\n##Sampling of plant properties \r\nThe vascular plant species composition was assessed at peak biomass every summer (July) by estimating the frequency of occurrence of each species with the pin count method in each plot (Frank and McNaughton 1990). A total of 172 taxa occurred within our 90 plots and we calculated plant species richness for each plot separately. We used the 2013 data in this study. Plant quality was assessed every year in July and September; here we use plant quality at the end of the experiment (September 2013). Two 10 x 100 cm wide strips of vegetation per plot were clipped, combined, dried at 65°C, and ground (Pulverisette 16, Fritsch, Idar-Oberstein, Germany) to pass through a 0.5 mm sieve. Twenty randomly selected samples across all treatments were analysed for N (Leco TruSpec Analyser, Leco, St. Joseph, Michigan, USA) (Vandegehuchte and others 2015). Nitrogen concentrations of the other samples were then estimated from models established for the experiment and the entire SNP relating Fourier transform-near infrared reflectance (FT-NIR) spectra to the measured values of N using a multi-purpose FT-NIR spectrometer (Bruker Optics, Fällanden, Switzerland) (Vandegehuchte and others 2015). Root biomass was sampled every fall by collecting five 2.2 cm diameter x 10 cm deep soil samples (Giddings Machine Company, Windsor, CO, USA) per plot (450 samples year-1). The samples were dried at 30 °C and roots were sorted from the sample by hand. We sorted each sample for 1 h which allowed to retrieve over 90% of all roots present in the samples (Risch and others 2013). The roots were then dried at 65 °C for 48 and weighed to the nearest mg. We averaged the values per plot and used the 2013 data only in this study.\r\n##Sampling of edaphic communities\r\nIn 2009, 2010, and 2011 we collected three composited soil samples (5 cm diameter x 10 cm depth; AMS Samplers, American Falls, ID, USA) and assessed bacterial community structure using T-RFLP profiling (Liu and others 1997; Blackwood and others 2003; Hodel and others 2014). We detected a total of 89 operational taxonomic units (OTUs). These values are in accordance with other studies reporting OTU richness (Wirthner and others 2011; Zumsteg and others 2012; Meola and others 2014) using T-RFLP profiling, a method that detects the most abundant, and thus likely, the most relevant, taxa. We averaged the data over the three years of collections for our calculations. Microbial biomass carbon (MBC) was determined with the substrate-induced method (Anderson and Domsch 1978) every fall (September) between 2009 and 2013 by collecting three mineral soil samples (5 cm diameter × 10 cm mineral soil core, AMS Samplers, American Falls, ID, USA). The three samples were combined (90 samples for each sampling year), immediately put on ice, taken to the laboratory, passed through a 2-mm sieve and stored at 4°C. Again, we only used the 2013 data in this study.\r\nSoil samples (5 cm diameter x 10 cm depth) to extract soil arthropods were collected in June, July, and August 2011 with a soil corer lined with a plastic sleeve to ensure an undisturbed sample (total of 270 samples). The plastic line core was immediately sealed on both ends using cling film and put into a cooler. All plots were sampled within three days and the extraction of arthropods started the evening of the sampling day using a high-gradient Tullgren funnel apparatus (Crossley and Blair 1991; Vandegehuchte and others 2015). Samples were kept in the extractor for four days and the soil arthropods were collected in 95% ethanol. All individuals were counted and each individual was identified morphologically to the lowest level feasible [76 taxa, including orders, suborders, subfamilies, families (Protura, Thysanoptera, Aphidina, Psylina, Coleoptera, Brachycera, Nematocera, Auchenorryncha, Heteroptera, Formicidae); sub-phylum for Myriapoda, for Acari and Collembola also including morpho-species). Note that we also included larval stages (nine of the 76 taxa) (Vandegehuchte and others 2015). All data were summed over the season. A detailed species list for mites and collembolans is published (Vandegehuchte and others 2017a) [https://doi.org/10.1371/journal.pone.0118679.s001]. Earthworms are rare in the SNP and therefore were not included. We collected eight random 2.2 cm diameter x 10 cm deep soil cores from each plot in September 2013 to determine the soil nematode community composition. The samples were mixed and the nematodes were extracted from 100 ml of fresh soil using Oostenbrink elutriators (Oostenbrink 1960). All nematodes in a 1 ml of the 10 ml extract were counted, a minimum of 150 individuals sample-1 were identified to genus or family level using (Bongers 1988), the numbers of all nematodes were extrapolated to the entire sample and expressed for a 100 g dry sample. In total we identified 63 genus or family levels (Vandegehuchte and others 2015). The list of all the nematodes found is published (Vandegehuchte and others 2015) [http://www.oikosjournal.org/appendix/oik-03341] or DOI: [doi: 10.1111/oik.03341]. \r\nWe are aware that sampling soil microbes from 2009 to 2011 and soil arthropods in 2011 was not ideal, but we are positive that this does not bias the results. Most of the parameters measured in our experiment either already showed a treatment response after the first growing season (e.g., plant biomass) or did not respond over the entire time experiment (e.g., microbial biomass C). The microbial community composition (2009 – 2011) was highly influenced by inter-annual differences in temperature and precipitation, but did not differ between treatments or vegetation types (Hodel and others 2014). We therefore felt comfortable using the 2009 through 2011 data for describing the soil microbial community in our experimental treatments. Similarly, we are positive that our soil arthropod data are representative. We did assess soil arthropods in August 2012 and found no differences to the August 2011 data. However, we did not feel comfortable combining the 2011 June, July, August data with only August data for 2012 for our analyses. \r\n##Sampling of soil properties\r\nWe collected three soil samples (5 cm diameter x 10 cm depth) in each plot in September 2013 after removing the vegetation. First, we collected the top layer of mineral soil rich in organic matter, the surface organic layer or rhizosphere, typically 1 to 3 cm in depth with a soil corer (AMS Samples, American Falls, Idaho, USA). Second, we collected a 10 cm mineral soil core beneath this surface layer. The cores for each layer were composited, dried at 65 °C for 48 h and fine-ground to pass a 0.5 mm screen. We then analysed all samples for total C using a Leco TruSpec Analyser (Leco, St. Joseph, Michigan, USA). Mineral soil pH was measured potentiometrically in 1:2 soil:CaCl2 solution with an equilibration time of 30 min. \r\nSoil net N mineralisation was assessed during the 2013 growing season (Risch and others 2015). For this purpose, we randomly collected a 5 cm diameter x10 cm deep soil sample with a soil corer (AMS Samples, American Falls, Idaho, USA) after clipping the vegetation in June 2013. After weighing and sieving (4 mm mesh) the soil, we extracted a 20 g subsample in 1 mol l-1 KCl for 1.5 h on an end-over-end shaker and thereafter filtered it through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnenmühle FineArt GmbH, Dassel, Germany). From these filtrates NO3- concentrations were measured colorimetrically (Norman and Stucki 1981) and NH4+with flow injection analysis (FIAS 300, Perkin Elmer, Waltham Massachusetts, USA) (Risch and others 2015). We dried the rest of the sample 105 °C to constant mass to determine fine,fraction bulk density. A second soil sample was collected within each plot in June 2013 with a corer lined with a 5 x 13 cm aluminium cylinder. The corer was driven 11.5 cm deep into the soil so that the top 1.5 cm of the cylinder remained empty. Into this space we placed a polyester bag (250 µm) filled an ion-exchanger resin to capture the incoming N. The bag was filled with a 1:1 mixture of acidic and alkaline exchanger resin (ion-exchanger I KA/ion exchanger IIIAA, Merck AG, Darmstadt, Germany). We then removed 1.5 cm soil at the bottom of the cylinder and placed a second resin exchanger bag into this space to capture the N leached from the soil column. To assure that the exchange resin was saturated with H+ and Cl- prior to filling the bags, the mixture was stirred with 1.2 ml l-1 HCl for 1 h and then rinsed with demineralized water until the electrical conductivity of the water reached 5 µm cm-1. The cylinder with the resin bags in place was reinserted into the soil with the top flush to the soil surface and incubated for three months. We recollected the cylinders in September 2013. Each resin bag and 20 g of sieved soil (4 mm mesh) from each cylinder were then separately extracted with KCl and NO3- and NH4+ concentrations were measured. Nitrate and NH4+ concentrations of all samples were then converted to a content basis by multiplying their values with fine fraction bulk density. Net N mineralisation was thereafter calculated as the difference between the N content of the samples collected at the end of the three-month incubation (including the N extracted from the bottom resin bag) and the N content at the beginning of the incubation (Risch and others 2015). \r\nSoil CO2 emissions were measured every two weeks between 0900 and 1700 hrs from early May through late September 2013 with a PP-Systems SRC-1 soil respiration chamber (15 cm high, 10 cm diameter; closed circuit) attached to a PP-Systems EGM-4 infrared gas analyser (PP-Systems, Amesbury, MA, USA) on two locations per plot (Risch and others 2013). The chamber was placed on randomly placed, permanently installed PVC collars (10 cm diameter) driven 5 cm into the soil at the beginning of the study (Risch and others 2013). Freshly germinated plants growing within the collars were removed prior to each measurement to avoid measuring plant respiration or photosynthesis. The two measurements collected per plot and sampling date were averaged. \r\nSoil moisture (with time domain reflectometry; Field-Scout TDR-100, Spectrum Technologies, Plainfield, Illionois, USA) and temperature (with a waterproof digital pocket thermometer; Barnstead International, Dubuque, Iowa, USA) were measured at five random locations per plot every two weeks during the growing seasons during the experiment for the 0 to 10 cm depth (Risch and others 2013, 2015). As soil moisture and soil temperature were highly negatively correlated (Risch and others 2013), we only used soil moisture for this study. We used plot-level averages of all values available to capture soil moisture variability during the five years of the experiment. The results remained unchanged when we only used soil moisture from the 2013 growing season.\r\n##Numeral calculations and statistical analyses\r\nEcosystem coupling. We conducted principal component analyses (PCAs; unscaled) at the complete dataset level using the abundances of each taxonomical entity to describe each of the five different communities used in this study: aboveground-dwelling invertebrates, vascular plants, soil microorganisms, soil arthropods and soil nematodes. We retained the first two components (PCA axis 1 and PCA axis 2) of each analysis as we found them to adequately represent the temporal and spatial variability of our 90 treatment plots in previous studies55,67. Together they explained a total of 71.70% of the variation for aboveground invertebrates, 44.36% for plants, 44.85% for soil microorganisms, 61.85% for soil arthropods and 77.19% for soil nematodes. In addition, we used soil pH and soil organic C content as a proxy for soil chemical properties, soil bulk density as a proxy for soil physical properties and soil moisture (negatively correlated with soil temperature) as a proxy for soil micro-climatic conditions for an overall total of fourteen constituents.\r\nWe calculated ecosystem coupling9 for each exclosure treatment within each vegetation type (i.e., 2  5 treatment combinations in total) as an integrated measure of pairwise ecological interactions between ecosystem constituents representing ecological communities and the soil abiotic environment. These ecological interactions are defined by non-parametric Spearman rank correlation analyses between two constituents, excluding interactions involving two abiotic constituents (e.g., soil pH vs. soil moisture) and interactions between the first (PC1) and second (PC2) component of each community type, as these are orthogonal by definition. Interactions between abiotic constituents were excluded from the analyses because the focus of our study was on communities and how they interact with one another and their surrounding environment; therefore, including abiotic-abiotic interactions was not of interest here. Given that the effectiveness of our experimental design resulted in that no community composition data of aboveground-dwelling invertebrates was available for the “None” plots (all animals excluded), only thirteen instead of fourteen constituents were included in the ecosystem coupling calculations for this treatment. The complete absence of aboveground invertebrates represents the most extreme case of disturbance between aboveground animal communities and the rest of the ecosystem constituents. This may have resulted in a slight overestimation of ecosystem coupling for these plots. \r\n\tAverage ecosystem coupling was calculated as follows: \r\nEcosystem coupling=\r\nwhere Xi is the absolute Coupling was calculated value of the Spearman’s rho coefficient of the ith correlation for each treatment within each vegetation type (i.e., based on nine replicates each), considering and n is the number of pairwise comparisons considered (n = a total of 80;  interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment).\tCoupling was calculated for each treatment within each vegetation type (i.e., based on nine replicates each), considering a total of 80 interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment). \r\nTo establish whether constituents were significantly and positively coupled within treatments (i.e., the average of their correlation coefficients were greater than in a null model where correlation only happens by chance), we calculated one-tailed p-values based on permutation tests with 999 permutations.   \r\n \r\nWe considered six ecosystem functions and process rates commonly used to assess ecosystem functioning (Meyer and others 2015; Manning and others 2018). Plant N content represents a measure of forage quality, while plant richness has been shown to stabilise biomass production, thus allowing the system to respond to changes in herbivory. Soil net N mineralisation, soil respiration, root biomass, and microbial biomass represent fluxes or stocks of energy. For all functions and processes higher values represent higher functioning (Manning and others 2018). All these variables were measured in the last year of the experiment (2013). We then quantified ecosystem multifunctionality using the multiple threshold approach (Byrnes and others 2014; Manning and others 2018), which considers the number of functions that are above a certain threshold, over a series of threshold values (typically 10-99%) that are defined based on the maximum value of each function. We weighted all our functions equally for these calculations (Manning and others 2018). The number of functions in a plot with values higher than a given threshold value for the respective function is summed up. The sum represents ecosystem multifunctionality for that plot. Given that choosing any particular threshold as a measure of ecosystem multifunctionality is arbitrary, we calculated the average of thresholds from 10-90% (in 10% intervals) as a more integrated representation of ecosystem multifunctionality. \r\nWe used Pearson correlations to explore the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and ecosystem multifunctionality by calculating the slopes of all relationships between ecosystem coupling and multifunctionality for all thresholds between 10 and 99%. We also related ecosystem coupling with the average of multifunctionality at thresholds between 30-80% as explained before and considered this correlation as a robust indication of the type of association between these two variables. In addition, we explored the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and individual ecosystem functions. The effects of exclosures and vegetation type on individual functions and multifunctionality were evaluated using linear mixed effects models ('lme' function of the nlme package), with exclosure and vegetation type as fixed effects and fence as a random factor. All statistical analyses and numerical calculations were done in R version 3.4.0 (R Core Team 2016).\r\n\r\n#References\r\n\r\n- Anderson J, Domsch K. 1978. A physiological method for the quantitative measurement of microbial biomass in soil. Soil Biol Biochem 10:215–21.\r\n- Blackwood CB, Marsh T, Kim S-H, Paul EA. 2003. Terminal Restriction Fragment Length Polymorphism Data Analysis for Quantitative Comparison of Microbial Communities. Appl Environ Microbiol 69:926–32. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC143601/\r\n- Bongers T. 1988. De nematoden von Nederland. Schoorl, The Netherlands: Pirola\r\n- Byrnes JEK, Gamfeldt L, Isbell F, Lefcheck JS, Griffin JN, Hector A, Cardinale BJ, Hooper DU, Dee LE, Duffy JE. 2014. Investigating the relationship between biodiversity and ecosystem multifunctionality: Challenges and solutions. Methods Ecol Evol 5:111–24.\r\n- Crossley DAJ, Blair JM. 1991. A high-efficiency low-technology Tulgren-type extractor for soil microarthopods. Agric Ecosyst Environ 34:187–92.\r\n- Dudley N. 2008. Guidelines for applying protected area managment categories. Gland: IUCN\r\n- Frank DA, McNaughton SJ. 1990. Aboveground biomass estimation with the canopy intercept method: A plant growth form caveat. Oikos 57:57–60.\r\n- Haynes AG, Schütz M, Buchmann N, Page-Dumroese DS, Busse MD, Risch AC. 2014. Linkages between grazing history and herbivore exclusion on decomposition rates in mineral soils of subalpine grasslands. Plant Soil 374.\r\n- Hodel M, Schütz M, Vandegehuchte ML, Frey B, Albrecht M, Busse MD, Risch AC. 2014. Does the aboveground herbivore assemblage influence soil bacterial community composition and richness in subalpine grasslands? Microb Ecol 68:584–95.\r\n- Liu WT, Marsh TL, Cheng H, Forney LJ. 1997. Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microbiol 63:4516–22. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC168770/\r\n- Manning P, van der Plas F, Soliveres S, Allan E, Maestre FT, Mace G, Whittingham MJ, Fischer M. 2018. Redefining ecosystem multifunctionality. Nat Ecol Evol 2:427–36. https://doi.org/10.1038/s41559-017-0461-7\r\n- Meola M, Lazzaro A, Zeyer J. 2014. Diversity, resistance and resilience of the bacterial communities at two alpine glacier forefields after a reciprocal soil transplantation. Environ Microbiol 16:1918–34. https://onlinelibrary.wiley.com/doi/abs/10.1111/1462-2920.12435\r\n- Meyer ST, Koch C, Weisser WW. 2015. Towards a standardized Rapid Ecosystem Function Assessment (REFA). Trends Ecol Evol 30:390–7. http://www.sciencedirect.com/science/article/pii/S0169534715000968\r\n- Norman R., Stucki JW. 1981. The determination of nitrate and nitrite in soil extracts by ultraviolet spectrophotometry. Soil Sci Soc Am J 45:347–53.\r\n- Ochoa-Hueso R. 2016. Non-linear disruption of ecological interactions in response to nitrogen deposition. Ecology 87:2802–2814.\r\n- Oostenbrink M. 1960. Estimating nematode populations by some selected methods. In: Sasser NJ, Jenkins WR, editors. Nematology. Chapel Hill, NC, USA: University of North Carolina Press. pp 85–101.\r\n- R Core Team. 2016. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing\r\n- Risch AC, Haynes AG, Busse MD, Filli F, Schütz M. 2013. The response of soil CO2 fluxes to progressively excluding vertebrate and invertebrate herbivores depends on ecosystem type. Ecosystems 16:1192–202.\r\n- Risch AC, Schütz M, Vandegehuchte ML, Van Der Putten WH, Duyts H, Raschein U, Gwiazdowicz DJ, Busse MD, Page-Dumroese DS, Zimmermann S. 2015. Aboveground vertebrate and invertebrate herbivore impact on net N mineralization in subalpine grasslands. Ecology 96:3312–22.\r\n- Schütz M, Risch AC, Achermann G, Thiel-Egenter C, Page-Dumroese DS, Jurgensen MF, Edwards PJ. 2006. Phosphorus translocation by red deer on a subalpine grassland in the Central European Alps. Ecosystems 9:624–633.\r\n- Schütz M, Risch AC, Leuzinger E, Krüsi BO, Achermann G. 2003. Impact of herbivory by red deer (Cervus elaphus L.) on patterns and processes in subalpine grasslands in the Swiss National Park. For Ecol Manage 181:177–88.\r\n- Vandegehuchte ML, van der Putten WH, Duyts H, Schütz M, Risch AC. 2017a. Aboveground mammal and invertebrate exclusions cause consistent changes in soil food webs of two subalpine grassland types, but mechanisms are system-speciﬁc. Oikos 126:212–23.\r\n- Vandegehuchte ML, Raschein U, Schütz M, Gwiazdowicz DJ, Risch AC. 2015. Indirect short- and long-term effects of aboveground invertebrate and vertebrate herbivores on soil microarthropod communities. PLoS One 10:e0118679.\r\n- Vandegehuchte ML, Schütz M, de Schaetzen F, Risch AC. 2017b. Mammal-induced trophic cascades in invertebrate food webs are modulated by grazing intensity in subalpine grassland. J Anim Ecol 86:1434–46.\r\n- Vandegehuchte ML, Trivellone V, Schütz M, Firn J, de Schaetzen F, Risch AC. 2018. Mammalian herbivores affect leafhoppers associated with specific plant functional types at different timescales. Funct Ecol 32:545–55.\r\n- Wirthner S, Frey B, Busse MD, Schütz M, Risch AC. 2011. Effects of wild boar (Sus scrofa L.) rooting on the bacterial community structure in mixed-hardwood forest soils in Switzerland. Eur J Soil Biol 47:296–302. http://dx.doi.org/10.1016/j.ejsobi.2011.07.003\r\n- Zumsteg A, Luster J, Göransson H, Smittenberg RH, Brunner I, Bernasconi SM, Zeyer J, Frey B. 2012. Bacterial, Archaeal and Fungal Succession in the Forefield of a Receding Glacier. Microb Ecol 63:552–64. https://doi.org/10.1007/s00248-011-9991-8\r\n",
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            "notes": "The reaction of ozone with bromide in polar regions results in the formation of reactive bromide species with impacts on ozone budget and the oxidative capacity of the lower atmosphere. Here, we present a data investigating the temperature dependence of bromide oxidation by ozone using a coated wall flow tube reactor coated with an aqueous mixture of citric acid and sodium bromide, a proxy for sea salt aerosol in snow or the free troposphere. Thus study shows the effect of of organic species at relatively mild temperatures between the freezing point and eutectic temperature as typical for Earth's cryosphere. ",
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            "notes": "The datasets comprise nearly 19’000 trees of European beech (_Fagus sylvatica_ L.) from unmanaged forests in Switzerland, Germany / Lower Saxony and Ukraine. Tree death was modelled as a function of size and growth, i.e., stem diameter (DBH) and relative basal area increment (relBAI). To explain the spatial and temporal variability in mortality patterns, we considered a large set of environmental and stand characteristics.\r\n\r\n## Inventory data\r\nThe strict forest reserves in Switzerland and Germany had been established in the period of 1961-1975 and 1971-1974, respectively. Every reserve included up to 10 permanent plots ranging from 0.09 to 1.8 ha in size, with slightly irregular re-measurement intervals. Permanent plots with pure or mixed beech stands were selected from the reserves of both networks. Reserves with considerable wind disturbance during the monitored intervals were excluded from the analysis. In addition to data from the Swiss and German reserves, data from a 10 ha plot in the primeval beech forest Uholka in Western Ukraine including three remeasurements were used. The inventory data provide diameter measurements at breast height (dbh) for revisited trees with a diameter of more than 4, 7 and 6 cm for Switzerland, Germany and Ukraine, respectively.\r\n\r\n## Mortality predictors\r\nA set of three consecutive inventories was used to generate records for the calibration of mortality models based on trees that were alive in the first and second inventory and either dead or alive in the third inventory. As an explanatory variable, the annual relative basal area increment (relBAI) was calculated based on the first and the second dbh measurement as the compound annual growth rate of the trees basal area. Tree dbh in the second inventory was used in addition to relBAI to model tree status (alive or dead) of the third inventory. \r\n\r\nTo increase the generality of the mortality models, we selected environmental variables that are known to have a considerable influence on growth and mortality of beech. We emphasized the effects of water availability using a large set of drought characteristics that were calculated based on the local site water balance. We also related beech mortality to soil pH, temperature, precipitation and growing degree-days. Additionally, we considered stand characteristics that reflect the development stage, competition and structure of the forests.\r\n\r\n## Further information\r\nFor further information, refer to Hülsmann _et al_. (2016) Does one model fit all? patterns of beech mortality in natural forests of three European regions. _Ecological Applications_.",
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            "notes": "This dataset contains open vector data for railways, forests and power lines, as well an open digital elevation model (DEM) for a small area around a sample forest range in Europe (Germany, Upper Bavaria, Kochel Forest Range, some 70 km south of München, at the edge of Bavarian Alps).\r\nThe purpose of this dataset is to provide a documented sample dataset in order to demonstrate geospatial preprocessing at FOSS4G2019 based on open data and software. This sample has been produced based on several existing open data sources (detailed below), therefore documenting the sources for obtaining some data needed for computations related to forest accessibility and wood harvesting. For example, they can be used with the open methodology and QGIS plugin [Seilaplan]( https://doi.org/10.16904/envidat.software.1) for optimising the geometric layout cable roads or with additional open software for computing the forest accessibility for wood harvesting.\r\nThe vector data (railways, forests and power lines) was extracted from OpenStreetMap (data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). The railways and forests were downloaded and extracted on 18.05.2019 using the open sources QGIS (https://www.qgis.org) with the QuickOSM plugin, while the power lines were downloaded a couple of days later on 23.05.2019. \r\n\r\nAdditional notes for vector data: \r\nPlease note that OpenStreeMap data extracts such as forests, roads and railways (except power lines) can also be downloaded in a GIS friendly format (Shapefile) from http://download.geofabrik.de/ or using the QGIS built-in download function for OpenStreetMap data. The most efficient way to retrieve specific OSM tags (such as power=line) is to use the QuickOSM plugin for QGIS (using the Overpass API -  https://wiki.openstreetmap.org/wiki/Overpass_API) or directly using overpass turbo (https://overpass-turbo.eu/). Finally, the digitised perimeter of the sample forest range is also made available for reproducibility purposes, although any  perimeter or area can be digitised freely using the QGIS editing toolbar.\r\n\r\nThe DEM was originally adapted and modified also with QGIS (https://www.qgis.org) based on the elevation data available from two different sources, by reprojecting and downsampling datasets to 25m then selecting, for each individual raster cell, the elevation value that was closer to the average. These two different elevation sources are:\r\n\r\n- Copernicus Land Monitoring Service - EU-DEM v.1.1 (TILE ID E40N20, downloaded from https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1; this original DEM was produced by the Copernicus Land Monitoring Service “with funding by the European Union” based on SRTM and ASTER GDEM)\r\n- Digitales Geländemodell 50 m Gitterweite (https://opendata.bayern.de/detailansicht/datensatz/digitales-gelaendemodell-50-m-gitterweite/), produced by the Bayerische Vermessungsverwaltung – www.geodaten.bayern.de –and downloaded from http://www.geodaten.bayern.de/opendata/DGM50/dgm50_epsg4258.tif\r\n\r\nThis methodology was chosen as a way of performing a basic quality check, by comparing the EU-DEM v.1.1 derived from globally available DEM data (such as SRTM) with more authoritative data for the randomly selected region, since using authoritative data is preferred (if open and available). For other sample regions, where authoritative open data is not available, such comparisons cannot longer be performed.\r\n\r\nAdditional notes DEM: a very good DEM open data source for Germany is the open data set collected and resampled by Sonny (sonnyy7@gmail.com) and made available on the Austrian Open Data Portal http://data.opendataportal.at/dataset/dtm-germany. In order to simplify end-to-end reproducibility of the paper planned for FOSS4G2019, we use and distribute an adapted (reprojected and resampled to 25 meters) sample of the above mentioned dataset for the selected forest range.\r\n\r\nThis sample dataset is accompanied by software in Python, as a Jupiter Notebook that generates harmonized output rasters with the same extent from the input data. The extent is given by the polygon vector dataset (Perimeter). These output rasters, such as obstacles, aspect, slope, forest cover, can serve as input data for later computations related to forest accessibility and wood harvesting questions. The obstacles output is obtained by transforming line vector datasets (railway lines, high voltage power lines) to raster. Aspect and slope are both derived from the sample digital elevation model.",
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                    "description": "The \"soundings\" radiosond data contains information on ambient pressure (mbar), temperature (C), relative humidity (%), wind speed ([m s&#8254; &#185;]) and wind direction (true deg), and are ordered with respect to the height above ground (m AGL) with a step size of 20 m. The first line of each file idicates the geographic location and the start time (in UTC) of the ascent. If the wind speed was zero, no wind direction is given.\r\nThe zip files contain ascents on the following days:  \r\nFebruary 10 (morning and afternoon),  \r\nFebruary 11 (morning),  \r\nFebruary 16 (afternoon),  \r\nFebruary 22 (morning),   \r\nMarch 1 (morning),   \r\nMarch 5 (morning),   \r\nMarch 11 (morning),   \r\nMarch 12 (morning),   \r\nMarch 13 (morning),   \r\nMarch 14 (morning),   \r\nMarch 17 (afternoon), and   \r\nMarch 18.    \r\nThe data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.",
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                    "description": "Meteorological parameters and present weather were measured for the duration of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign at the Weissfluhjoch at an elevation of 2700 m above sea level (a.s.l.), and in Davos Wolfgang and Kloster, two villages which are in the valley at 1600 m a.s.l. and 1170 m a.s.l., respectively. The mountain ridge Gotschna separates Davos Wolfgang in the South from Klosters in the North.  The deployed instruments were owned by ETH Zurich, Meteoswiss and TROPOS. \r\n\r\nAmbient temperature (°C), humidity (%), atmospheric pressure (hPa), solar radiation (W m-1) and wind direction (°) and speed (m s-1) were recorded at standard weather stations from Meteoswiss at Weissfluhjoch and Davos Wolfgang, and from TROPOS at Davos Wolfgang. Additionally, a present weather detector (PWD22, Vaisala) was installed at Klosters to measure the weather type, ambient ligth as well as intensity and amount of both liquid and solid precipitation (mm). \r\n\r\nRadiosondes were started in Davos Wolfgang to report height profiles of pressure, relative humidity and temperature.\r\nFurther profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121953_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120017.589162RACLETSmeteologo.png",
                    "title": "Meteorology",
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                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
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                    "description": "The trajectories are started from surface up to 5000 m altitude, with an equidistant vertical spacing of 200 m, and calculated 120 h backward in time. As long as the trajectories stay in the COSMO1 domain (essentially the Alpine region), as run operationally at MeteoSwiss, the COSMO analysis wind fields are used. When the trajectories leave this domain, they are extended further backward in time based on ECMWF analysis data. The following fields are traced along the trajectories: longitude, latitude, geopotential height, pressure, specific humidity, temperature and surface topography. Furthermore, it is indicated for each trajectory time instance on which model data, COSMO or ECMWF, the trajectory time is based. Finally, the trajectories are started every hour in the specified time period, and positions and fields are available every 10 min. Each day is saved as a separate file. The last 8 digits of the file names indicate the starting date of the trajectories. ",
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            "doi": "10.16904/envidat.120",
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                    "description": "The regional numerical weather predicton model COSMO was used to simulate certain periods of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign. The one-moment scheme which described cloud microphysical processes with prognostic variables was replaced by a two-moment scheme which considered a higher number of hydrometeor classes and used prescribed CCN and INP concentrations. \r\n\r\nThe results of the two-moment scheme were compared to both, the operationally used one-moment scheme and the in-situ cloud microphysical data and precipitation measurements of the campaign. In addition to tuning of parameterizations of cloud microphysical processes, which are important prerequisites for the stabilization of orographic MPCs and therewith orographic precipitation in the model, the influence of anthropogenic aerosol on precipitation was assesd. The simulations were conducted with various CCN and INP concentrations under the same meteorological conditions to represent clean and polluted scenarios.    \r\n",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120058.853032RACLETSmodellogo.png",
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                    "display_name": "RACLETS Field Campaign",
                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
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            ],
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                    "description": "Rain or snow reaching the ground as precipitation were measured at a high elevation site and at two locations in the valley over the course of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign: Gotschnagrat (2285 m above sea level - a.s.l.), as well as Laret (1522 m a.s.l.), and Davos Wolfang (1630 m a.s.l.). The applied instruments were owned and operated by ETH Zurich, EPFL and TROPOS.\r\n\r\nThe fall velocity and size of hydrometeors were measured with disdrometers (Parsivel, OTT HydroMet), that are laser based optical systems to measure all types of precipitation, e.g. drizzle, rain, snow, hail and hybrid forms of these classes. The disdrotemer data was continously recording liquid precipitation in a particle size range of 0.2 to 8 mm, solid precipitation in a particle size range of 0.2 to 25 mm, with particle fall velocities between 0.2 and 20 m s-1. Precipitation was dicriminated into 32 size classes and corresponded to 32 particle velocity classes.  \r\n\r\nThe precipitation measurements were accompanied by [snow measurements](https://www.envidat.ch/group/about/snow) at Gotschnagrat and in Davos Wolfgang.   Instruments to measure [aerosol concentrations](https://www.envidat.ch/group/about/aerosols-raclets), [meteorological parameters](https://www.envidat.ch/group/about/meteorology), [wind profiles/velocities](https://www.envidat.ch/group/about/remote-sensing-raclets), and the [CloudNet station](https://www.envidat.ch/group/about/remote-sensing-raclets) were also located in Davos Wolfgang. \r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/IMG_8893_Scale.JPG)\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/IMG_8012_Scale.JPG)\r\n\r\nImages: Claudia Mignani\r\n",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120313.061012RACLETSpreciplogo.png",
                    "title": "Precipitation",
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                {
                    "display_name": "RACLETS Field Campaign",
                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
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                    "display_name": "Remote Sensing",
                    "description": "Remote sensing instruments providing information on aerosols, radiation, and clouds were deployed in Davos Wolfgang, 1630 m above sea level (a.s.l), and Kloster, 1150 m a.s.l for the duration of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign. The instruments were owned and supervised by ETH Zürich, Meteoswiss, and TROPOS Leipzig. \r\n\r\nAt Davos Wolfgang, a CloudNet station combined a Raman Lidar (Polly-XT), a Doppler Cloud Radar (Mira-36, METEK GmbH) and a Microwave Radiometer (RPG-HATPRO, Radiometer Physics GmbH) to measure aerosol and cloud properties. In addition, a Doppler Lidar (Windcube 100S, Leosphere) and a Radar Wind Profiler were deployed to get information on wind properties like direction (°), speed (m s-1) and vertical profile (up to 5000 m above ground). The tethered balloon system carrying a holographic imager, named [HoloBalloon](https://www.envidat.ch/group/about/clouds-in-situ-raclets) to measure cloud microphysics, was launched close to the CloudNet station. \r\nA Ceilometer (CL31, Vaisala), which was deployed in Kloster, reported the cloud base height (m a.s.l.) and vertical visibility (m).\r\nQuicklooks of the measurements and more information on the instruments can be found here: http://data.iac.ethz.ch/holodavos2019/\r\n\r\n![imahge is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Annika/DSC_4599_Scale.jpg)\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Jan/IMG_20190210_201419_Scale.jpg)\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Jan/IMG_20190209_103309_Scale.jpg)\r\n\r\nImages: Jan Hennerbger, Annika Lauber\r\n",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120138.007368RACLETSremotelogo.png",
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                    "display_name": "Snow",
                    "description": "During the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign, snow measurements were conducted at the mountain top site Gotschnagrat at 2285 m above sea level (a.s.l.) and hosted by WSL/SLF. \r\nThe shape and morphology of single ice crystals were recorded at Weissfluhjoch at an elevation of 2700 m a.s.l. and in Laret (1522 m a.s.l.). The University of Basel collected and analyzed the ice crystal pictures.\r\n\r\nThe snow observation at Gotschnagrat included snow mass-flux (Snow Particle Counter, SPC-7, Nigaata; Flowcapt, FC4, ISAW) in kg m-2 s-1, snow surface temperature (SI-111, Campbell) in °C, snow height (SHM31, Lufft) in m and measurements of meteorological parameters like air temperature in °C, humidity in % (CS215, Campbell), and three dimensional wind speed (81000, Young) in m s-1 for every wind direction.\r\nThe data contains information on the amount of fresh snow, bonding of the snowpack, the formation of surface hoar and snowdrift accumulations. \r\n\r\nAt Weissfluhjoch, there is the chance to directly sample ice crystals within the cloud if the cloud touches the mountain or after falling through the atmosphere when the cloud base is higher than the mountaintop. At Laret, ice crystals and snowflakes can be observed which were atmospherically processed while falling. \r\n\r\nIce crystals and water droplets were additionally recorded in-situ with a holographic imager ([HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), mounted on a cable car, operating between Gotschnaboden (1779 m a.s.l.) and Gotschnagrat (2285 m a.s.l.).\r\nOther parameters measured at Weissfluhjoch included [precipitation](https://www.envidat.ch/group/about/precipitation), [aerosol, INP and CCN concentrations](https://www.envidat.ch/group/about/aerosols-raclets).\r\n\r\n\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121970_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
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                    "title": "Snow",
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            "notes": "The instrument (MRR, Metek) was mounted at a height of 1 m above snow surface (at the beginning of the campaign) with an orientation of 22° with respect to North and a horizontal viewing direction. The sampling time was either 5 s or 10 s, depending on the settings at the specific period.  The MRR produces standard outputs like radar reflectivity, doppler velocity, etc., and additional information can be found [here](https://metek.de/de/product/mrr-2/).",
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            "author": "[{\"name\": \"Gerber\", \"affiliation\": \"Laboratory of Cryospheric Sciences, School of Architecture and Civil Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland and WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland\", \"affiliation_03\": \"\", \"given_name\": \"Franziska\", \"identifier\": \"\", \"email\": \"gerberf@slf.ch\", \"affiliation_02\": \"\"}, {\"name\": \"Mott\", \"affiliation\": \"WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland\", \"affiliation_03\": \"\", \"given_name\": \"Rebecca\", \"identifier\": \"\", \"email\": \"mott@slf.ch\", \"affiliation_02\": \"\"}, {\"name\": \"Hoch\", \"affiliation\": \"Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah\", \"affiliation_03\": \"\", \"given_name\": \"Sebastian W.\", \"identifier\": \"\", \"email\": \"sebastian.hoch@utah.edu\", \"affiliation_02\": \"\"}, {\"name\": \"Bavay\", \"affiliation\": \"WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland\", \"affiliation_03\": \"\", \"affiliation_02\": \"\", \"identifier\": \"\", \"email\": \"bavay@slf.ch\", \"given_name\": \"Mathias\"}, {\"name\": \"Lehning\", \"affiliation\": \"Laboratory of Cryospheric Sciences, School of Architecture and Civil Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland and WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland\", \"affiliation_03\": \"\", \"affiliation_02\": \"\", \"identifier\": \"\", \"email\": \"lehning@slf.ch\", \"given_name\": \"Michael\"}]",
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            "notes": "The data presented here corresponds to the publication \"A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation\" (Gerber et al., 2017), which investigates an eddy-like structure in the vicinity of the Sattelhorn in the Dischma valley (Davos Switzerland)  and its influence on snow accumulation. The dataset contains:\r\n\r\n* Alpine3D: Alpine3D snow depth grids (25 m resolution) for two simulations with and without snow redistribution.\r\n* ARPS: 10 ARPS simulations (25 m horizontal resolution) with different model setups (wind direction, wind speed, stability).\r\n* LiDAR: Processed LiDAR PPI (D2_PPI_1h) and RHI (D2_cross_1h) across the valley with a hourly resolution for the period 27 October 2015 01:00 - 29 October 2015c 21:00 (spatial resolution: 25 m).\r\n* meteostations-dischma: Meteorological station data of two meteorological stations in the Dischma valley with 10 minute resolution for the period 28 October 2015 - 30 October 2015.\r\n* TLS: Snow depth change data (m) between 28 October 2015 and 30 October 2015 based on terrestrial laser scans.\r\n\r\nFor more details about the simulation and observation data, see Gerber et al., 2017.\r\n\r\n__Publication__: Gerber et al., 2017: A Close-Ridge Small-Scale Atmospheric Flow Field and its Influence on Snow Accumulation, submitted to JGR - Atmospheres. ",
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            "title": "DISCHMEX - Observations and simulations of the close-ridge small-scale atmospheric flow field and snow accumulation at Sattelhorn, Dischma valley, Davos, Switzerland.",
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                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
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                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
                    "title": "RACLETS Field Campaign",
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                },
                {
                    "display_name": "Snow",
                    "description": "During the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign, snow measurements were conducted at the mountain top site Gotschnagrat at 2285 m above sea level (a.s.l.) and hosted by WSL/SLF. \r\nThe shape and morphology of single ice crystals were recorded at Weissfluhjoch at an elevation of 2700 m a.s.l. and in Laret (1522 m a.s.l.). The University of Basel collected and analyzed the ice crystal pictures.\r\n\r\nThe snow observation at Gotschnagrat included snow mass-flux (Snow Particle Counter, SPC-7, Nigaata; Flowcapt, FC4, ISAW) in kg m-2 s-1, snow surface temperature (SI-111, Campbell) in °C, snow height (SHM31, Lufft) in m and measurements of meteorological parameters like air temperature in °C, humidity in % (CS215, Campbell), and three dimensional wind speed (81000, Young) in m s-1 for every wind direction.\r\nThe data contains information on the amount of fresh snow, bonding of the snowpack, the formation of surface hoar and snowdrift accumulations. \r\n\r\nAt Weissfluhjoch, there is the chance to directly sample ice crystals within the cloud if the cloud touches the mountain or after falling through the atmosphere when the cloud base is higher than the mountaintop. At Laret, ice crystals and snowflakes can be observed which were atmospherically processed while falling. \r\n\r\nIce crystals and water droplets were additionally recorded in-situ with a holographic imager ([HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), mounted on a cable car, operating between Gotschnaboden (1779 m a.s.l.) and Gotschnagrat (2285 m a.s.l.).\r\nOther parameters measured at Weissfluhjoch included [precipitation](https://www.envidat.ch/group/about/precipitation), [aerosol, INP and CCN concentrations](https://www.envidat.ch/group/about/aerosols-raclets).\r\n\r\n\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121970_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
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                    "description": "Meteorological parameters and present weather were measured for the duration of the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign at the Weissfluhjoch at an elevation of 2700 m above sea level (a.s.l.), and in Davos Wolfgang and Kloster, two villages which are in the valley at 1600 m a.s.l. and 1170 m a.s.l., respectively. The mountain ridge Gotschna separates Davos Wolfgang in the South from Klosters in the North.  The deployed instruments were owned by ETH Zurich, Meteoswiss and TROPOS. \r\n\r\nAmbient temperature (°C), humidity (%), atmospheric pressure (hPa), solar radiation (W m-1) and wind direction (°) and speed (m s-1) were recorded at standard weather stations from Meteoswiss at Weissfluhjoch and Davos Wolfgang, and from TROPOS at Davos Wolfgang. Additionally, a present weather detector (PWD22, Vaisala) was installed at Klosters to measure the weather type, ambient ligth as well as intensity and amount of both liquid and solid precipitation (mm). \r\n\r\nRadiosondes were started in Davos Wolfgang to report height profiles of pressure, relative humidity and temperature.\r\nFurther profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121953_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
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                    "display_name": "RACLETS Field Campaign",
                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
                    "title": "RACLETS Field Campaign",
                    "id": "ab759699-d40a-44c9-995f-c0e5aad1c2b5",
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                },
                {
                    "display_name": "Snow",
                    "description": "During the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign, snow measurements were conducted at the mountain top site Gotschnagrat at 2285 m above sea level (a.s.l.) and hosted by WSL/SLF. \r\nThe shape and morphology of single ice crystals were recorded at Weissfluhjoch at an elevation of 2700 m a.s.l. and in Laret (1522 m a.s.l.). The University of Basel collected and analyzed the ice crystal pictures.\r\n\r\nThe snow observation at Gotschnagrat included snow mass-flux (Snow Particle Counter, SPC-7, Nigaata; Flowcapt, FC4, ISAW) in kg m-2 s-1, snow surface temperature (SI-111, Campbell) in °C, snow height (SHM31, Lufft) in m and measurements of meteorological parameters like air temperature in °C, humidity in % (CS215, Campbell), and three dimensional wind speed (81000, Young) in m s-1 for every wind direction.\r\nThe data contains information on the amount of fresh snow, bonding of the snowpack, the formation of surface hoar and snowdrift accumulations. \r\n\r\nAt Weissfluhjoch, there is the chance to directly sample ice crystals within the cloud if the cloud touches the mountain or after falling through the atmosphere when the cloud base is higher than the mountaintop. At Laret, ice crystals and snowflakes can be observed which were atmospherically processed while falling. \r\n\r\nIce crystals and water droplets were additionally recorded in-situ with a holographic imager ([HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), mounted on a cable car, operating between Gotschnaboden (1779 m a.s.l.) and Gotschnagrat (2285 m a.s.l.).\r\nOther parameters measured at Weissfluhjoch included [precipitation](https://www.envidat.ch/group/about/precipitation), [aerosol, INP and CCN concentrations](https://www.envidat.ch/group/about/aerosols-raclets).\r\n\r\n\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121970_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120220.421222RACLETSsnowlogo.png",
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            "notes": "A Young 81000 sonic anemomenter was deployed to record three components of the wind velocity (u, v, w in [m s&#8254; &#185;]) and air temperature (Ts in [°C]). The anemomenter was mounted in direction North at a height of 1.5 m above snow surface at the beginning. The time within each data set is given in UTC+1. Instrument specifications can be found [here](http://www.youngusa.com/Manuals/81000-90(I).pdf) . ",
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                    "description": "The relative humidity was measured with a Campbell CS-215 at a height of 2.2 m above ground. The time is given in UTC+1.",
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                    "description": "The air temperature was measured with a Campbell CS-215 which was mounted at a height of 2.2 m above ground. The time is given in UTC+1.",
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                    "description": "The snow depth was measured with a Lufft SHM-31 which was mounted at 1.7 m above ground. The time is given in UTC+1.",
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                    "description": "The snow surface temperature was measured with a Campbell SI-111 at 0.7 m above ground. The time is given in UTC+1.",
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            "tags": [
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                {
                    "display_name": "RACLETS Field Campaign",
                    "description": "### Campaign Overview\r\n\r\nThe __RACLETS__ - _Role of Aerosols and CLouds Enhanced by Topography on Snow_ - campaign uniquely combines cloud and snow research to improve the understanding of precipitation formation in clouds and snow deposition on the ground.  \r\n\r\n\r\nDuring the RACLETS campaign in February and March 2019, an extensive set of instruments was deployed in the Davos regions including aerosol, cloud, precipitation and snow measurements. In a unique cooperation between cloud and snow research groups, this study aimed to observe the complete life cycle of ice crystals:\r\n\r\n- Cloud droplet formation and ice nucleation on aerosol particles\r\n- Growth of cloud droplets and ice crystals to precipitation\r\n- Ice crystal enhancement by ice multiplication\r\n- Precipitation location and amount on the ground\r\n- Redistribution of snow on the ground\r\n\r\n\r\nThe measurements were contextualized by using regional numerical weather models for the atmosphere and high-resolution models for snow deposition.\r\n\r\nTo cover the spatial differences of the topography, instruments were deployed at five different locations and on a cable car. The main measurement site was located in __Davos Wolfang__, 1630 m above sea level (a.s.l.). Here, [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets) were probed in-situ by a tethered balloon system (HoloBalloon), [radiosondes](https://www.envidat.ch/group/about/meteorology) were launched, [precipitation](https://www.envidat.ch/group/about/precipitation) was measured (disdrometer), [remote sensing instruments](https://www.envidat.ch/group/about/remote-sensing-raclets) were deployed (OceaNet station, Wind Profiler and Wind LIDAR) and [aerosol and INP measurements](https://www.envidat.ch/group/about/aerosols-raclets) were carried out to study the atmosphere. The mountain ridge __Gotschna__ separates Davos Wolfgang in the south from Klosters in the north. In __Klosters__ (1170 m a.s.l.), a [ceilometer](https://www.envidat.ch/group/about/remote-sensing-raclets) was applied to measure the cloud base. On a cable car, running on the north side of the ridge towards __Gotschnagrat__ (2285 m a.s.l.), HoloGondel was attached, which took in-situ images of ice crystals and droplets in [clouds](https://www.envidat.ch/group/about/clouds-in-situ-raclets). A [snow drift station](https://www.envidat.ch/group/about/snow) and a [disdrometer](https://www.envidat.ch/group/about/precipitation) were located at __Gotschnagrat__. At the mountain site __Weissfluhjoch__ (2700 m a.s.l.), south of __Gotschna__, [Aerosols, INPs, CCNs](https://www.envidat.ch/group/about/aerosols-raclets) were measured in addition to analysing [snowflakes](https://www.envidat.ch/group/about/snow) and performing [snow measurements](https://www.envidat.ch/group/about/snow). [Snow](https://www.envidat.ch/group/about/snow) and [precipitation](https://www.envidat.ch/group/about/precipitation) measurements were performed in __Laret__, which is located in the valley at an elevation of 1522 m a.s.l. and in a distance of about 1 km north of Davos Wolfgang.\r\n\r\n\r\n\r\n![An image is missing, e.g. picture Gotschnagrat, cablecar, Weissfluhjoch, etc.](https://iacweb.ethz.ch/data/holimo/images/RACLETS-OverviewMap_Scale.png) \r\n\r\n\r\n### Data Files\r\nThe data recorded during the campaign can be accessed via the following subprojects (as link): \r\n\r\n- [_Aerosols_](https://www.envidat.ch/group/aerosols-raclets)\r\n- [_Clouds in-situ_](https://www.envidat.ch/group/clouds-in-situ-raclets)\r\n- [_Meteorology_](https://www.envidat.ch/group/meteorology) \r\n- [_Modelling_](https://www.envidat.ch/group/modeling) \r\n- [_Precipitation_](https://www.envidat.ch/group/precipitation) \r\n- [_Remote Sensing_](https://www.envidat.ch/group/remote-sensing-raclets)\r\n- [_Snow_](https://www.envidat.ch/group/snow) \r\n\r\n  \r\n### __Project Partners__\r\nMore information about participating insitutes can be found here: \r\n\r\n- https://duw.unibas.ch/de/home/\r\n- https://www.epfl.ch/en/home/\r\n- http://www.iac.ethz.ch/group/atmospheric-physics.html\r\n- https://www.meteoswiss.admin.ch/home.html?tab=overview\r\n- https://www.slf.ch/\r\n- https://www.tropos.de/institut/ueber-uns/das-institut/\r\n- https://www.wsl.ch/de/schnee-und-eis.html  \r\n\r\n",
                    "image_display_url": "https://iacweb.ethz.ch/data/holimo/images/RACLETS_logo.jpg",
                    "title": "RACLETS Field Campaign",
                    "id": "ab759699-d40a-44c9-995f-c0e5aad1c2b5",
                    "name": "raclets-field-campaign"
                },
                {
                    "display_name": "Snow",
                    "description": "During the [RACLETS](https://www.envidat.ch/group/about/raclets-field-campaign) campaign, snow measurements were conducted at the mountain top site Gotschnagrat at 2285 m above sea level (a.s.l.) and hosted by WSL/SLF. \r\nThe shape and morphology of single ice crystals were recorded at Weissfluhjoch at an elevation of 2700 m a.s.l. and in Laret (1522 m a.s.l.). The University of Basel collected and analyzed the ice crystal pictures.\r\n\r\nThe snow observation at Gotschnagrat included snow mass-flux (Snow Particle Counter, SPC-7, Nigaata; Flowcapt, FC4, ISAW) in kg m-2 s-1, snow surface temperature (SI-111, Campbell) in °C, snow height (SHM31, Lufft) in m and measurements of meteorological parameters like air temperature in °C, humidity in % (CS215, Campbell), and three dimensional wind speed (81000, Young) in m s-1 for every wind direction.\r\nThe data contains information on the amount of fresh snow, bonding of the snowpack, the formation of surface hoar and snowdrift accumulations. \r\n\r\nAt Weissfluhjoch, there is the chance to directly sample ice crystals within the cloud if the cloud touches the mountain or after falling through the atmosphere when the cloud base is higher than the mountaintop. At Laret, ice crystals and snowflakes can be observed which were atmospherically processed while falling. \r\n\r\nIce crystals and water droplets were additionally recorded in-situ with a holographic imager ([HoloGondel](https://www.envidat.ch/group/about/clouds-in-situ-raclets), mounted on a cable car, operating between Gotschnaboden (1779 m a.s.l.) and Gotschnagrat (2285 m a.s.l.).\r\nOther parameters measured at Weissfluhjoch included [precipitation](https://www.envidat.ch/group/about/precipitation), [aerosol, INP and CCN concentrations](https://www.envidat.ch/group/about/aerosols-raclets).\r\n\r\n\r\n\r\n![image is missing](https://iacweb.ethz.ch/data/holimo/images/notUploaded/Claudia/P2121970_Scale.JPG)\r\n\r\nImage: Claudia Mignani",
                    "image_display_url": "https://www.envidat.ch/uploads/group/2019-08-21-120220.421222RACLETSsnowlogo.png",
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                    "description": "The institute's former main building on the Weissfluhjoch remains at its disposal for research purposes. The test site below the building is the [SLF's](http://www.envidat.ch/organization/slf) oldest and equipped with numerous measuring instruments.\r\n\r\n## Globally unrivalled serial measurements\r\nIn autumn 1936, the Expert Commission for Snow and Avalanche Research (now the SLF) in Switzerland built the first snow laboratory on the Weissfluhjoch. Since these early days, SLF employees have been observing the weather and snow conditions on the adjacent test site daily. The site is located on a flat area of the Dorftälli, approximately 150 m below the Weissfluhjoch towards Davos, at an altitude of 2540 m. In view of the good accessibility and the numerous avalanche-prone slopes in the vicinity, researchers have conducted countless major experiments and studies here in the fields of snow mechanics, snow metamorphism, snow characterisation and measuring methodology. They have also tested the prototypes of various instruments, calibrated remote sensing products, and used the data collected at the test site to compare their snowpack models with those of other scholars.\r\nThe Weissfluhjoch test site is now the only one in the world at this altitude that has a daily record of snow depths and snowfall dating back more than 70 years.\r\n\r\n__More information:__ http://www.slf.ch/ueber/standorte/weissfluhjoch/index_EN",
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            "notes": "# Overview\r\n\r\nThe CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change.\r\n\r\n# Experimental Setup\r\n\r\nFuture snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085).\r\n\r\n# Data\r\n\r\nSnow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average.\r\n",
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                    "description": "The core of the European Snow Booklet (ESB), the country reports of 38 European countries, are based on information and metadata on snow measurements collected through a comprehensive survey, the ESB Questionnaire, between August 2017 and March 2018. The station metadata (for example location, elevation, measurement start date) from each country was provided by one or several institutions responsible for snow observations. By answering the questionnaire the contacts agreed that the information and metadata provided could be presented in the ESB. For cases where institutions indicated that information on station locations could be made publicly available, the metadata for the variables snow depth (HS), depth of snowfall (HN) and water equivalent of the snow cover (SWE), is additionally provided here for download (METADATA.xlsx).\r\nPlease note that not all institutions gave permission to publish their station metadata. This metadata has to be requested from the non-personal institution contacts provided in the METADATA.xlsx file. In some cases, however, no institutional contact is available and thus the contact of the country representative who filled in the questionnaire is used. \r\nFor current, updated station metadata we refer to the (non-personal) institutional contacts provided in METADATA.xlsx and/or the institution webpages. Note, however, that we cannot guarantee for completeness of the dataset for all countries because operational networks are prone to changes.",
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                    "description": "Here you can find the list of all lead authors of the different chapters of the European Snow Booklet (ESB).\r\nIn addition a list of the editorial board that reviewed the ESB is given.",
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                    "description": "Please find here the web version of the COST European Snow Booklet (ESB).",
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            "notes": "The European Snow Booklet (ESB) is a book of reference for snow measurements that has been produced through collaboration with many European snow practitioners and snow scientists in the framework of the European Cooperation in Science and Technology (COST) Action ES1404 “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction (HarmoSnow)”. The ESB provides a unique collection of information about operational snow observations in the European countries and the methods used to perform basic measurements of snow on the ground: snow depth (HS), depth of snowfall (HN), water equivalent of the snow cover (SWE) and presence of snow on the ground (PSG). Information and station metadata (for example location, elevation) for these basic snow variables were collected through a comprehensive survey, the ESB questionnaire between August 2017 and March 2018. Numerous institutions of 38 European countries provided detailed information describing the status of the operational snow observations and the methods used at the time of the survey. Based on the information provided, a country report was written for each European country. Similarities and differences among the countries, that is, the choice of snow variables to be measured, the measurement principles applied, the number of stations, or the spatial and elevational station distribution are pointed out. Thus the collection of country reports demonstrates the relevance of snow measurements for each country. Thus, the intention of the ESB is to foster better knowledge transfer regarding snow measurements between the snow science and operational communities and to improve the communication of information to the general public.\r\n\r\nFor detailed information on the European countries, we refer to the ESB, which can be downloaded here (envidat.ch). Please note that the ESB is not a living document and information and station metadata are from August 2017 till March 2018, except for Latvia (metadata updated in December 2018).",
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                "description": "__Air pollution and climate change have an effect on the forest. We examine these effects as part of the Long-Term Forest Ecosystem Research (LWF) programme.__\r\n\r\nWe need reliable information in order to record the condition of the forest on an ongoing basis and to understand precisely what happens in the forest when the environment changes. An important source of data here is the Long-Term Forest Ecosystem Research (LWF) programme. It consists of 19 permanent monitoring sites on which we have regularly carried out numerous measurements since 1994. We have also been recording the health of trees on the monitoring sites of the Sanasilva Inventory, which is part of the LWF programme (see Sites), since 1985.\r\n\r\nWe disclose the gathered data, as well as the scientific interpretation of this data, to national and international decision-makers.\r\n\r\nWith the legally enshrined functions of the LWF programme, Switzerland participates in international research programmes such as the \"International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests\" ICP Forests and the LTER-Europe Network (Long-Term Ecosystem Research in Europe).\r\n\r\nThe Long-term Forest Ecosystem Research (LWF) programme is run and financed by the WSL.\r\n \r\n### Objectives of the programme\r\n\r\n *   Early detection and a representative assessment of changes in forest condition\r\n *   Determination of external influences, both from anthropogenic and natural sources and their effect on the forest ecosystem (element inputs, climate)\r\n *    Determination of changes in important components within the forest ecosystem\r\n *   Development of indicators to assess the condition of the forest\r\n *   Integrated risk assessment based on different stress scenarios\r\n *   Extended platform for internal and external research projects\r\n\r\n__Further information__: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf.html",
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            "related_publications": "Graf Pannatier, E., Thimonier, A., Schmitt, M., Walthert, L., Waldner, P. (2011): A decade of monitoring at Swiss Long-Term Forest Ecosystem Research (LWF) sites: can we observe trends in atmospheric acid deposition and in soil solution acidity?. Environmental Monitoring and Assessment, 174, 1-4: 3-30. https://doi.org/10.1007/s10661-010-1754-3\r\n\r\nThimonier, A., Kosonen, Zaida, Braun, S., Rihm, Beat, Schleppi, P., Schmitt, M., Seitler, Eva, Waldner, P., Thöni, L. 2019. Total deposition of nitrogen in Swiss forests: comparison of assessment methods and evaluation of changes over two decades. Atmos. Environ. 198, 335-350. https://doi.org/10.1016/j.atmosenv.2018.10.051\r\n\r\nRebetez, M., von Arx, G., Gessler, A., Graf Pannatier, E., Innes, J.L., Jakob, P., Jetel, M., Kube, M., Nötzli, M., Schaub , M., Schmitt, M., Sutter, F., Thimonier, A., Waldner, P., Haeni, M. 2018. Meteorological data series from Swiss long-term forest ecosystem research plots since 1997. Ann. For. Sci. 75, 41-48. https://doi.org/10.1007/s13595-018-0709-7\r\n\r\n__Manuals__\r\n\r\nUkonmaanaho, L., Pitman, R., Bastrup-Birk, A., Breda, N. & Rautio, P. 2016. Part XIII: Sampling and Analysis of Litterfall. In: Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests (ed. UNECE ICP Forests Programme Co-ordinating Centre) (Thünen Institute for Forest Ecosystems, Eberswalde, Germany).\r\n\r\nRaspe, S., Beuker, E., Preuhsler, T. & Bastrup-Birk, A. 2016. Part IX: Meteorological Measurements. In: Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests (ed. UNECE ICP Forests Programme Co-ordinating Centre) (Thünen Institute for Forest Ecosystems, Eberswalde, Germany).\r\n\r\nClarke, N., Zlindra, D., Ulrich, E., Mosello, R., Derome, J., Derome, K., König, N., Lövblad, G., Draaijers, G. P.J., Hansen, K., Thimonier, A., Waldner, P. 2016. Part XIV: Sampling and Analysis of Deposition. In: Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests (ed. UNECE ICP Forests Programme Co-ordinating Centre) (Thünen Institute for Forest Ecosystems, Eberswalde, Germany).",
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            "notes": "This dataset contains the parameters used in the statistical analyses for the manuscript SREP-19-40170-T, submitted in Scientific Reports. This study is part of the WSL Drought Initiative 2018 (C3 - Analysis of the beech litterfall of the drought year 2018).\r\n\r\nData originate from the Long-term Forest Ecosystem Research Programme LWF (litterfall, soil matric potential, deposition (precipitation) and meteo (temperature)), and from the Swiss Federal Office of Meteorology and Climatology MeteoSwiss (pollen).\r\n\r\n__Datafile:__\r\n\r\n _LWF_beech_plots_litterfall_pollen.xlsx_\r\n\r\n1. Sheet _extreme_weather_: values used for analysis of weather conditions in strongest mast years compared to years with fruit abortion.\r\n\r\n2. Sheet _weather_and_resource_allocation_: values used for analysis of weather impacts on mast occurrence and resource allocation models.\r\n\r\n__Related Datasets__\r\n\r\nMatthias Haeni; Arthur Gessler; Martine Rebetez (2019). Bettlachstock, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards. EnviDat. https://doi.org/10.16904/envidat.96. \r\n\r\nMatthias Haeni; Arthur Gessler; Martine Rebetez (2019). Lausanne, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1996 onwards. EnviDat. https://doi.org/10.16904/envidat.101. \r\n\r\nMatthias Haeni; Arthur Gessler; Martine Rebetez (2019). Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards. EnviDat. https://doi.org/10.16904/envidat.107. \r\n\r\nKatrin Meusburger; Elisabeth Graf Pannatier (2019). MPS-2 soil water matric potential LWF. EnviDat. doi:10.16904/envidat.lwf.31. \r\n\r\nKatrin Meusburger; Elisabeth Graf Pannatier; Emily Solly; Jörg Sintermann; Peter Waldispühl (2019). Matric potential (manual suction cups) LWF. EnviDat. doi:10.16904/envidat.lwf.27. \r\n\r\nAnne Thimonier; Maria Schmitt; Peter Waldner (2019). Atmospheric deposition (throughfall and bulk deposition) LWF. EnviDat. https://doi.org/10.16904/envidat.lwf.15. \r\n\r\nAnne Thimonier; Maria Schmitt; Peter Waldner (2019). Litterfall LWF. EnviDat. https://doi:10.16904/envidat.lwf.17\r\n",
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            "notes": "Two stem core samples of 10 trees outside the plot of each main species in the plot were taken at breast height (1.3 m above ground) with a SUUNTO corer. Tree ring width and density were determined with the instruments CATRAS and TSAP, the Densitometer DENDRO 2003 and a stereo-microscope. The selected trees included at least 10 pre-dominant or dominant trees. \r\n\r\n### Purpose: ###\r\n\r\nN and C stable isotope signals\r\n\r\n\r\n\r\n### Paper Citation: ###\r\n\r\n * Tomlinson, G., Siegwolf, R.T.W., Buchmann, N., Schleppi, P., Waldner, P., Weber, P., 2014. The mobility of nitrogen across tree-rings of Norway spruce (Picea abies L.) and the effect of extraction method on tree-ring d15N and d13C values. Rapid Commun. Mass Spectrom. 28, 1258-1264.\r\n\r\n",
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            "notes": "Two stem core samples of 12 to 20 trees outside the plot of each main species in the plot were taken at breast height (1.3 m above ground) with a SUUNTO corer. Tree ring width and density were determined with the instruments CATRAS and TSAP, the Densitometer DENDRO 2003 and a stereo-microscope. The selected trees included at least 12 pre-dominant or dominant trees and if possible also 4 subdominant or surpressed trees. NOTE: The samplings were carried out between 1996 and 1999 for most plots and in 2003 for the plot Lantsch. The cores cover a time span depending on the age of the oldest trees on a plot. On one plot the oldest sampled tree ring grew in the year 1646. \r\n\r\n### Purpose: ###\r\n\r\nReconstruction of stand history and tree growth\r\n\r\n\r\n\r\n### Manual Citation: ###\r\n\r\n * Paolo Cherubini, Matthias Dobbertin, 1997: Bestandesgeschichte (Dendrochronologie). In: Peter Brang (ed.), Aufnahmeanleitung LWF. Langfristige Waldökosystem-Forschung LWF, Eidg. Forschungsanstalt WSL, Birmensdorf, 3 S. \r\n\r\n *  Cherubini, P.; Dobbertin, M., 1998: The Swiss long-term forest ecosystem research: methods for reconstructing forest history. In: Borghetti, M. (ed): Società Italiana di Selvicoltura ed Ecologia Forestale (SISEF), Atti I: 19-22.\r\n\r\n\r\n\r\n### Paper Citation: ###\r\n\r\n * Cherubini, P., Fontana, G., Rigling, D., Dobbertin, M., Brang, P., Innes, J.L., 2002. Tree-life history prior to death: two fungal root pathogens affect tree-ring growth differently. J. Ecol. 90, 839-850.\r\n\r\n",
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            "notes": "Leaf area index (LAI), defined as the total one-sided foliage area per unit ground surface area, is one of the most important characteristics of plant canopy structure. Leaves are the active interface between the atmosphere and the ecosystem. Thus, LAI affects many ecosystem processes, including light and precipitation interception, evapotranspiration, CO2 fluxes and dry deposition. LAI was measured repeatedly in the period 1996-2013 at 18 LWF plots using 1) a LAI-2000 plant canopy analyser (Licor, Inc) and 2) hemispherical photographs of the canopy. Measurements were performed above the 16 vegetation quadrats in the 43 m x 43 m intensive monitoring subplot. In 1996-2003, LAI measurements were usually carried out on the same day as the vegetation surveys. It is also planned to characterise the potential light conditions (diffuse and direct) using the hemispherical photographs of the canopy.\r\n\r\n### Purpose: ###\r\n\r\n1) To estimate an important structural parameter of the forest stand, which is needed as an input variable in most ecosystem process models simulating carbon and water cycles on a stand or regional scale; and 2) to document changes in the canopy structure, and thus in light conditions, which may be responsible for changes in ground vegetation\r\n\r\n\r\n\r\n### Manual Citation: ###\r\n\r\n * Thimonier, A., 1997. Kapitel C6. Blattflächenindex (LAI), in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-5. \r\n\r\n *  Thimonier, A., 1997. Kapitel C7. Lichtverhältnisse im Wald, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-4. \r\n\r\n *  Fleck  S,  Raspe  S,  Cater  M,  Schleppi  P,  Ukonmaanaho  L,  Greve  M,  Hertel  C,  Weis  W,  Rumpf,  S.,  Thimonier, A., Chianucci, F., Beckschäfer, P., 2016: Part XVII: Leaf Area Measurements. In: UNECE ICP Forests  Programme  Co-ordinating  Centre  (ed.):  Manual  on  methods  and  criteria  for  harmonized  sampling,  assessment,  monitoring  and  analysis  of  the  effects  of  air  pollution  on  forests.  Thünen  Institute    of    Forest    Ecosystems,    Eberswalde,    Germany,    34    p.    +    Annex    [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)\r\n\r\n\r\n\r\n### Paper Citation: ###\r\n\r\n * Thimonier A, Kull P, Keller W, Moser B, Wohlgemuth T (2011) Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments. Environmental Monitoring and Assessment, 174: 47-63. [doi: 10.1007/s10661-010-1759-y](https://doi.org/10.1007/s10661-010-1759-y) \r\n\r\n *  Thimonier A, Sedivy I, Schleppi P (2010) Estimating leaf area index in different types of mature forest stands in Switzerland: a comparison of methods. European Journal of Forest Research, 129 (4): 543-562. [10.1007/s10342-009-0353-8](https://doi.org/10.1007/s10342-009-0353-8)\r\n\r\n",
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            "notes": "Ground vegetation is an important compartment of the ecosystem in terms of biodiversity and it takes an active part in the general functioning of the ecosystem. It is also a useful bio-indicator of the site conditions and its monitoring may enable the detection of environmental changes. Ground vegetation relevés were carried out repeatedly at 17 LWF plots during in the the period between 1994 and 2011. In 2013, ground vegetation was surveyed at an additional LWF plot (Laegeren). The cover of all plant species occurring in 16 1-m2 quadrats, distributed over the 43 x 43 m intensive monitoring subplot was visually assessed. Seedlings and saplings were also counted and their position within the quadrat was noted in order to assess tree regeneration.\r\n\r\n### Purpose: ###\r\n\r\nTo assess the species diversity of ground vegetation and detect possible environmental changes using its bio-indicator value.\r\n\r\n\r\n\r\n### Manual Citation: ###\r\n\r\n * Kull, P., 1997. Kapitel D2. Vegetationsaufnahmen. In: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-9. \r\n\r\n * Canullo  R,  Starlinger  F,  Granke  O,  Fischer  R,  Aamlid  D,  2016:  Part  VI.1:  Assessment  of  Ground  Vegetation. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on  forests.  Thünen  Institute  of  Forest  Ecosystems,  Eberswalde,  12  p.  +  Annex  [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)\r\n\r\n\r\n\r\n### Paper Citation: ###\r\n\r\n * Thimonier A, Kull P, Keller W, Moser B, Wohlgemuth T (2011) Ground vegetation monitoring in Swiss forests: comparison of survey methods and implications for trend assessments. Environmental Monitoring and Assessment, 174: 47-63. [doi: 10.1007/s10661-010-1759-y](http://doi.org/10.1007/s10661-010-1759-y)\r\n\r\n",
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            "notes": "This dataset consist of simulated hourly power production from an Enercon E82 Turbine at 100 m hub-height. It describes the hourly power output a 1MW turbine would produce in each 0.01° grid cell for the years 2016 and 2017.\r\n\r\n100 m wind speed data was taken from the COSMO-1 model (Consortium for Small-scale Modeling 2017), which has a 0.01° horizontal resolution. The domain covered is the whole of Switzerland, with the exclusion of lakes. As such, the number of 0.01◦ pixels within Switzerland amounts to 48657. \r\nConversion to power output was done based on the power curve of the Enercon E82 Turbine. As power output is lower at altitude due to lower air density, we corrected for this effect as described in (Kruyt et al. 2017). \r\n\r\nPlease cite the following paper in connection with the dataset:\r\n\r\n__Paper Citation:__\r\n > _Bert Kruyt, Jérôme Dujardin, and Michael Lehning: Improvement of wind power assessment in complex terrain: The case of COSMO-1 in the Swiss Alps, Front. Energy Res., [doi:10.3389/fenrg.2018.00102] (https://doi.org/10.3389/fenrg.2018.00102)_\r\n\r\n\r\n",
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                    "description": "The dataset contains volumes, solutes and stable water isotopes of snowpack outflow at daily resolution.  10-minute data are provided of the measurements taken by three snowmelt lysimeter systems at spatially-distributed locations.  \r\n",
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            "notes": "This data contain volumes, solutes and isotopes of snowpack outflow measured by a snowmelt lysimeter system at three locations in the southern Alp catchment, situated Central Switzerland.  The river Alp is a snow-dominated catchment situated in Central Switzerland characterized by an elevation range from 840 to 1898 m a.s.l.  \r\nThe dataset provides solutes (major anions and cations, trace metals) and stable water isotopes and water fluxes (snowpack outflow volumes) at daily intervals from several sampling locations. Additionally, the data measured by the snowmelt lysimeter system are provided in 10-minute resolution.  The data will be publically available estimated by the end of 2019. \r\n",
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            "notes": "### UAV-derived DSMs and orthoimages\r\n\r\nUnmanned Aerial Vehicle  (UAV) surveys were conducted between 2015 and 2016 on the __Sankt Annafirn__, __Findelen-__ and __Griesgletscher__, situated in the __Swiss Alps__. Three surveys at the Sankt Annafirn allowed for a full glacier coverage,  four  surveys at Griesgletscher allowed an almost full glacier coverage and seven surveys at Findelengletscher allowed for a partial coverage of the glacier tongue (see individual datasets for exact extent). For each survey, a __high resolution orthoimage__ and a __Digital Surface Model (DSM)__ was created.\r\n\r\n### UAV surveys:\r\n\r\nPrior flight, Ground Control Points (GCPs) were deployed on the glacier surface and measured with a differential GPS (Trimble R7 or Leica GPS 1200). They allowed precise georeferencing of the UAV-derived datasets. UAV flight plans were planned with the software *eMotion 2* and a SenseFly eBee was used as surveying platform. The images were then processed with the software Agisoft Photoscan Pro 1.1.6 .\r\n\r\nThe location and dates of each survey can be found in the table together with the number of flights performed (Nflights), the number of acquired images (Nimages), the number of GCPs set (NGCPs) and the surveyed area.\r\n\r\nA folder for each dataset is available (see folder name in table), which contains:\r\n\r\n- An orthoimage  __*glacier_date_photoscan_oi_CH1903+_LV95_0.1m.tif*__\r\n\r\n- A Digital Surface Model  __*glacier_date_photoscan_dsm_CH1903+_LV95_0.1m.tif*__\r\n\r\n- The Agisoft Photoscan automatic processing report   __*glacier_date_photoscan_report.pdf*__\r\n\r\nwhere:\r\n\r\n- __*glacier*__ is the name of the surveyed glacier\r\n\r\n- __*date*__ is the date of the UAV image acquisition\r\n\r\n- __*photoscan*__ is the name of the photogrammetric software\r\n\r\n- __*oi*__ or __*dsm*__ the type of dataset\r\n\r\n- __*CH1903+_LV95*__ is the coordinate system and datum of the dataset\r\n\r\n- __*0.1m*__ is the resolution of the dataset in meter\r\n\r\n- __*.tif*__ is the extention of the dataset\r\n\r\n&nbsp;\r\n\r\nDetails about the UAV surveys, the image processing and the accuracy of the UAV-derived products can be found in this publication below.\r\n\r\n__Paper Citation:__\r\n > _Gindraux et al. 2017. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’Imagery on Glaciers, Remote Sensing, 9, 186, 1-15,  [doi: 10.3390/rs9020186](https://doi.org/10.3390/rs9020186)._\r\n\r\nThe folder UAV_flight_paths.zip contains all UAV flights performed on the Sankt Annafirn, Findelengletscher and Griesgletscher. The flights were planned with the software eMotion2 and have the .afp extention.",
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            "notes": "Meteorological measurements recorded in the Dischma valley from 2014-2016. In 2014 and 2015 we used 11 mobile weather stations from sensorscope to record meteorological parameter in the upper Dischma valley in the closer surroundings of the Gletschboden area. The meteorological stations are eqiupped with at least air temperature/humidity, wind velocity and wind direction sensors. Some stations are additionally equipped with precipitation, shortwave radiation and snow surface temperature sensors.  \r\nThree transects were installed at different aspects and were equipped with air temperature/humidity and wind sensors. Transect 1 (stations 2-4) provides meteorological Information on an east-north-east facing slope at elevations ranging between 2100 m and 2500 m. Transect 2 (stations 5-7) provides meteorological Information on a south-west slope and transect 3 (stations 8-10) on a north-west slope. Station 1 is fully equipped with meteorological sensors (temperature/humidity, wind, IR, up and downwand shortwave radiation and precipitation).\r\nIn 2016, mobile stations from sensorscope were replaced with six permanent meteorological stations. Meteorological stations 1-3 are equipped with an air temperature/humidity sensor, two wind speed sensors, a wind direction sensor and an incoming and outgoing shortwave radiation sensor. Stations 4 and 6 are equipped with an air temperature/humidity sensor and a wind speed/direction sensor. Station 5 is a equipped with an air temperature/humidity sensor, a wind speed/direction sensor, a snow surface temperature sensor, an incoming and outgoing shortwave radiation sensor and an incoming longwave radiation sensor.",
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                    "description": "The provided folder structure follows the set up of the scripts.\r\nData is only provided when it has been fully produced by us, otherwise dummies are given.\r\nFor data that will be produced by one of the scripts, no dummies are given.\r\nThe folders may contain sub-folders, which would be filled if the scripts were all run\r\n\r\n## 00_Analysis_Data\r\nData produced throughout the process of the calibration and projection that is later needed for analysis\r\n\r\n## 01_Raw_Data\r\nPrimary data from external sources that were used to compile the rasters and numbers used during the calibration and projection of landscape transitions as well as service calculation\r\n\r\n## 02_Prepared_Data\r\nData that will be prepared for further use by scripts are put in here\r\nAdditionally it contains the parameter sheets for the transition predictors that we compiled\r\n\r\n## 03_Model_Data\r\n# Model outputs\r\nFolder were the projection models statistics will be saved\r\n# Models\r\nFolder into which the actual transition models will be saved\r\n# Residuals\r\nFolder into which data on models residuals will be saved for future use\r\n\r\n## 04_Projected_Data\r\nThe output of the projections will be saved into this folder\r\n\r\n## 05_Service_Data\r\nAny service calculations will be saved in here\r\n\r\n## 06_Results_Analysis\r\nAny Analysis plots and tables as well as intermediate data will be saved here in the respective sub-folder\r\n",
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                    "description": "Scripts ordered by their main purpose within sequential folders in this ReadMe marked with ##\r\n\r\nWithin the folders the capital letters refer to the parallel or sequential use of the scripts; scripts here in ReadMe are marked with #\r\n\r\n\r\n## 00_Function Scripts ##\r\n# Functions.r\r\nScript containing several functions for analyzing statistical models: cohen.kappa, meva.table, D2, max-Tss, plot-TSS\r\n\r\n# Service_functions.R\t\t\r\nScript containing functions for calculating all services and returning sums (and median for bd and rec) as well as rasters\r\n\r\n\r\n\r\n## 01_Data Preparation ##\r\n# A_AS_raster_preparation.R\t\r\nPreparation of the land use rasters for the years 1985, 1997, and 2009 based on the original Arealstatistik (AS/ASCH); Assigning our categories and assining new values to all \"construction sites\" for calibrating the models\r\nFor model projection starting point (2009) and for service calculations (all ASCH years) the \"other\" categories were assigned to the land use categories based on dominant neighbor, so that there were no empty cells\r\nCreation of water & mountainous area raster that stayed stable throughout the projections\r\nCreation of MFH raster (2009), to have as base for all new projection years, as this category never becames any other\r\n\r\n# B_Factors_preparation.R\t\r\nPreparation of the factor rasters that were used to calculate service values per cell (see Table 2): LWfactor, Transportation, Vol, Rivers, Lakes, slope, TWW, Hazard_risk\r\n\r\n# B_Predictors_preparation.R\r\nPreparation of the raster of the predictors used for calibrating (ASCH years) and projecting (stable) the transition models that do not depend on the land use categories: Temperature (ASCH years), solar radiation (stable), Public transportation access (stable), Elevation (stable), Workers density (ASCH years), Population change (ASCH transitions)\r\n\r\n# B_Regions_preparation.R\t\r\nPreparation of bioregions as raster to be used to mask asxxxx later to calculated services and land use area just for one region\r\n\r\n# C_Pred_proj.R \t\r\nProjecting the dynamic predictors into the future for projecting the land use transitions with the model: Linear extrapolations for workers densities and population; 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calibrated separately for each bioregion\r\n\r\n# E_Residuals_trans_models.R\r\nCalculation of Moran's I statistics to analyze the residuals of the land use transition models\r\n\r\n\r\n\r\n\r\n## 03_Projections ##\r\n# A_Bioreg_Projections_run.R\t\r\nMaster script for: Extrapolaitng into the future with the regional models and then assembling for each time step to calculate new AS predictors; Several Outputs: txt file to test for NAs in Predictors, txt file with random seed number for sampling, txt file with times for calculation steps (check progress of script while running), csv sheet with projected transition frequencies, tif-rasters for every region and time step, pdf with raster plot for every region and time step\r\n\r\n\r\n\r\n\r\n## 04_Service calculation ##\r\n# A_Bioreg_as_services.R\t\r\nCalculate services per bioregion for years 1985, 1997, 2009\r\n\r\n# A_Service_calculation_bioregions.R\t\r\nExtracting service numbers(sums) per bioregions for all projection runs and storing them in a list of matrixes to be available for further plotting; 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Initial=intensively managed grasslands; Harvest only= multiple hay harvest (2-3 times) per years; Topsoil= Topsoil removal (upper 10-30 cm); Topsoil+Propagules= Topsoil removal (upper 10-30 cm) combined with introduction of target plant species; Target= species-rich ancient grasslands\r\n\r\nX: X-Coordinate\r\n\r\nY: Y-Coordinate\r\n\r\nRi.veg: Total number of plant species\r\n\r\nDiv.veg: Shannon diversity of plant species\r\n\r\nRi.nem: Total number of nematode families\r\n\r\nDiv.nem: Shannon diversity of nematode families\r\n\r\nabund: Total nematode abundance (individuals per 100g dry soil)\r\n\r\nMI: Maturity index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)\r\n\r\nPPI: Plant parasite index according to Bongers 1990; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)\r\n\r\nPPI.MI: Plant parasite to Maturity index according to Bongers, van der Meulen, & Korthals 1997; calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)\r\n\r\nCI: Channel index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)\r\n\r\nEI: Enrichment index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)\r\n\r\nSI: Structure index according to Ferris, Bongers, & de Goede 2001 (%); calculations done in online tool NINJA (Sieriebriennikov, Ferris, & de Goede, 2014)\r\n\r\nHe.a: Herbivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014\r\n\r\nHe.ecto.a: Herbivorous ectoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014\r\n\r\nHe.endo.a: Herbivorous endoparasite nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014\r\n\r\nBa.a:  Bacterivorous nematode abundance (individuals per 100g dry soil); classification according to Sieriebriennikov, Ferris, & de Goede, 2014\r\n\r\nFu.a: Fungivorous  nematode abundance (individuals per 100g dry soil); 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            "doi": "10.16904/envidat.65",
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            "notes": "This dataset contains all data on which the following publication below is based.\r\n\r\n__Paper Citation:__\r\n > Resch, M.C., Schütz, M., Graf, U., Wagenaar, R., van der Putten, W.H., Risch, A.C. accepted. Does topsoil removal in grassland restoration benefit both soil nematode and plant communities? Journal of Applied Ecology.  [doi:10.16904/envidat.65](https://doi.org/10.16904/envidat.65).\r\n\r\nPlease cite this paper together with the citation for the datafile.\r\n\r\n# Methods\r\n## Study area and experimental settings\r\nThe study was conducted in a nature reserve (Eigental: 47° 27’ to 47° 29’ N, 8° 37’ E, 461 to 507 m a.s.l.) that is located on the Swiss Central plateau close to Zurich airport (Canton Zurich, Switzerland). The mean annual temperature in this area ranges from 8.9 to 10.6 °C, mean annual precipitation from 910 to 1260 mm [10-year average (2007-2017); MeteoSchweiz, 2018]. The main soil types are calcaric to gleyic Cambisol and Gleysols. The reserve was established in 1967 to protect small remnants of oligotrophic semi-natural grasslands (roughly 12 ha). The plant community can be characterized as Molinion and Mesobromion (semi-wet to semi-dry), depending on the site-specific groundwater level and slope inclination (Delarze, Gonseth, Eggenberg, & Vust, 2015). These remnants represent species-rich islands in an otherwise intensively managed agricultural landscape. Semi-natural grasslands covered an area of 60,000 ha in the Canton Zurich in 1939, however, by 2005 only roughly 600 ha remained (Baudirektion Kanton Zürich, 2007). In 1990, the government of Canton Zurich decided to enlarge the nature reserve Eigental. The goal was to incorporate eleven patches of 20 ha adjacent intensively farmed land and transform these patches into semi-natural grasslands. The patches had a different agricultural history, ranging from permanent (no tillage for >50 years) to temporary grassland (as part of crop rotation; last tillage <5 years). On all freshly integrated patches fertilization was stopped in 1992 and from then on biomass was harvested three times a year and removed. After 5 years without noticeable effects on vegetation composition, the Nature Conservation Agency of Canton Zurich decided to increase the restoration efforts. In 1995, a large-scale experiment was initialized to evaluate if certain treatments can facilitate restoration within a reasonable timeframe of 5 to 10 years after treatment implementation.\r\nThe three restoration treatments used were: \r\ni. “Harvest only”: Plots are being mowed two to three times a year and the biomass is removed.\r\nii. “Topsoil”: Topsoil was removed to a depth of 10 to 20 cm, depending on the depth of the O and A horizon, in four randomly selected areas within each of the eleven patches in late autumn 1995. The size of each topsoil removal area depended on individual patch size and was between 2700 and 7000 m2. \r\niii. “Topsoil+Propagules”: Propagules from target vegetation were added on half of the area where topsoil was removed, using fresh, seed-containing hay originating from a mixture of semi-dry to semi-wet species-rich grasslands of local provenance (within a radius of 7 km). Hay applications were conducted twice in 1995 and 1996. Repeated applications were chosen to account for the low quantity of available plant material per transfer, since area ratio between receptor and donor sites was roughly 1:1. In addition, hand-collected propagules from 15 selected target species of regional provenance (within a radius of 30 km) were equally applied in 1996 and 1997. \r\n“Topsoil” and “Topsoil+Propagules” plots are mowed once a year, and the biomass is removed. Mowing on these plots started five years after the treatment was implemented. \r\nEleven permanent plots of 5 m x 5 m were randomly established in each treatment to monitor the vegetation development. The experiment was complemented with 11 control plots that represent the initial state of intensively managed grasslands, further referred to as “Initial”, and 11 control plots that represent the targeted state of donor sites for “Topsoil+Propagules”, further referred to as “Target”. Consequently, the experiment consists of 55 plots (5 treatments x 11 replicates). Management of intensively used grasslands includes mowing and fertilizing (manure) between two to five times a year, as well as different tillage regimes (no tillage for >50 years; last time of tillage <5 years). \r\n\r\n## Nematode and plant sampling\r\nSoil nematodes were sampled in 2 m x 2 m plots, randomly established at least 2 m away from the vegetation plots. We collected eight soil cores with a 2.2 cm diameter soil core sampler (Giddings Machine Company, Windsor, CO, USA) to a depth of 12 cm (representing the majority of the plant rooting system) in each plot at the beginning of July 2017. The eight cores within each replicate plot were combined, gently homogenized, placed in coolers and transported to the laboratory of NIOO in Wageningen, the Netherlands, within one week. Free-living nematodes were extracted from 200 g of fresh soil using Oostenbrink elutriator (Oostenbrink, 1960) and concentrated, resulting in 6 mL nematode solution. The nematode solution was subdivided into three subsamples, two for morphological identification and quantification, and one for molecular work (not used in this study). For morphological identification and quantification, nematodes were heat-killed at 90 °C and fixed in 4 % formaldehyde solution (final volume 10 mL per subsample). All nematodes in 1 mL of formaldehyde solution were counted, and a minimum of 150 individuals per 1 mL sample (or all if less nematodes were present) were identified to family level using Bongers (1988). We then extrapolated the numbers of each nematode taxa identified to the entire sample and expressed them per 100 g dry soil for further analyses. \r\nWe calculated number of nematode taxa and Shannon diversity and assessed nematode community composition. In addition, we classified the nematode taxa into feeding types (herbivores, bacterivores, fungivores, omni-carnivores), structural and functional guilds (Table S4). Structural guilds assign nematode taxa according to life-history traits into five colonizer-persister (C-P) classes, ranging from one (early colonizers of new resources) to five (persisters in undisturbed habitats; Bongers 1990). C-P classes can be categorized as indicators for nutrient-enriched (C-P1), stressed (C-P2) and structured (C-P3 + C-P4 + C-P5) soil conditions (Ferris, Bongers, & de Goede, 2001). Functional guilds assign nematode taxa according to their C-P classification combined with their feeding habits (Ferris, Bongers, & de Goede, 2001). Based on the structural and functional guild classification we calculated five additional indices to assess soil nutrient status, disturbance and food web characteristics using NINJA (Sieriebriennikov, Ferris, & de Goede, 2014). 1) The Maturity index indicates the degree of different environmental perturbations (e.g., tillage, nutrient enrichment, pollution) and is used to monitor colonization and subsequent succession after disturbances (Bongers, 1990). 2) The ratio between the Plant Parasite (C-P of herbivorous nematodes only) to Maturity index is used to monitor the recovery of disturbed habitats incorporating information of life-history traits for all feeding types (Bongers, van der Meulen, & Korthals, 1997). 3) The Enrichment index indicates nutrient-enriched soils and agricultural management practices (Ferris, Bongers, & de Goede, 2001). 4) The Structure index provides information about the succession stage of the soil food web and therefore correlates with the degree of maturity of an ecosystem (Ferris, Bongers, & de Goede, 2001). 5) The Channel index provides information about the predominant decomposition pathways, where higher values stand for a higher proportion of energy transformed through the slow fungal decomposition channel (Ferris, Bongers, & de Goede, 2001). In addition, the Structure and Enrichment indices can be displayed in a biplot where nematode assemblages are plotted along a structure (x-axis) and enrichment (y-axis) trajectory (increasing index values). Each biplot quadrat reflects different levels of disturbance, soil nutrient pools and decomposition pathways (Ferris, Bongers, & de Goede, 2001). \r\nThe plant surveys were conducted on the 25 m2 permanent plots in June 2017. Plant species cover was visually assessed according to the semi-quantitative cover-abundance scale of Braun-Blanquet (1964; nomenclature: Lauber & Wagner, 1996). We calculated number of species and Shannon diversity, and assessed plant community composition. We also counted the number of target species (all species recorded in the eleven target plots plus propagules of species applied by hand, resulting in a total of 143 species) and categorized plant species into species of concern based on their red list status in Switzerland as well as their protection status in Switzerland and the Canton Zurich (Moser, Gygax, Bäumler, Wyler, & Palese, 2002). Furthermore, we calculated indicator values for soil moisture and soil nutrients for each species according to Landolt et al. (2010).\r\n\r\n## References\r\nBaudirektion Kanton Zürich (2007). 10 Jahre Naturschutz-Gesamtkonzept für den Kanton Zürich 1995-2005 – Stand der Umsetzung. Zürich: Baudirektion Kanton Zürich.\r\nBongers, T. (1988). De nematoden van Nederland. Utrecht: Stichting Uitgeverij Koninklijke Nederlandse Natuurhistorische Vereniging.\r\nBongers, T. (1990). The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia, 83, 14-19. doi:10.1007/BF00324627\r\nBongers, T., van der Meulen, H., & Korthals, G. (1997). Inverse relationship between the nematode maturity index and plant parasite index under enriched nutrient conditions. Applied Soil Ecology, 6, 195-199. doi:10.1016/S0929-1393(96)00136-9\r\nBraun-Blanquet, J. (1964). Pflanzensoziologie, Grundzüge der Vegetationskunde (3rd ed.). Wien: Springer.\r\nDelarze, R., Gonseth, Y., Eggenberg, S., & Vust, M. (2015). Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten (3rd ed.). Bern: Ott.\r\nFerris, H., Bongers, T., & de Goede, R.G.M. (2001). A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Applied Soil Ecology, 18, 13-29. doi:10.1016/S0929-1393(01)00152-4\r\nLandolt, E., Bäumler, B., Erhardt, A., Hegg, O., Klötzli, F., Lämmler, W., … Wohlgemuth, T. (2010). Flora indicativa. Ecological indicator values and biological attributes of the Flora of Switzerland and the Alps (2nd ed.). Bern: Haupt.\r\nLauber, K., & Wagner, G. (1996). Flora Helvetica. Flora der Schweiz. Bern: Haupt.\r\nMeteoSchweiz (2018). Klimabulletin Jahr 2017, Zürich: MeteoSchweiz.\r\nMoser, D., Gygax, A., Bäumler, B., Wyler, N., & Palese, R. (2002) Rote Liste der gefährteten Farn- und Blütenpflanzen der Schweiz. Bern: BUWAL.\r\nOostenbrink, M. (1960). Estimating nematode populations by some selected methods. In N.J. Sasser & W.R. Jenkins (Eds.), Nematology (pp. 85-101). Chapel Hill: University of North Carolina Press. \r\nSieriebriennikov, B., Ferris, H., & de Goede, R.G.M (2014). NINJA: An automated calculation system for nematode-based biological monitoring. European Journal of Soil Biology, 61, 90-93. doi:10.1016/j.ejsobi.2014.02.004\r\n\r\n\r\n",
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            "notes": "### Overview\r\nThe SUNWELL Modelling Environment is a combination of data and code that models electricity production from satellite-derived irradiance data and other spatial data sets for all of Switzerland. This ensemble accompanies the publication \"The bright side of PV production in snow-covered mountains\", published in the Proceedings of the National Academy of Science and reproduces all results and figures of. Code and resources are in their original form (with documentation). A new version with a more generalized application to PV modelling and with more flexibility in terms of input and output formats will be released in the coming months.\r\n\r\n### Format\r\nAll code is written and has to be executed in Matlab. The input and output data sets are also in the Matlab-specific .mat format. Whenever publicly available, the original data is provided as geotif, .xlsx or other common format. \r\nThis is the case for:\r\n\r\n- Digital Elevation Model (InputsFromMatlab/MSG/OriginalData/ASTERDEM), \r\n- Landsurface cover type (InputsFromMatlab/MSG/OriginalData/CORINE), \r\n- Population Density (InputsFromMatlab/MSG/OriginalData/popdensRaster, \r\n- Electricity production from three of our validation sites (/Validation/WSL), \r\n- Measured irradiance for two validation sites (/Validation/ASRB)\r\nThe ‘Metadata’ documents in the respective folders provide further information about the data sources and processing. Figures are produced either in .pdf or .png format. \r\n\r\n### Structure\r\nThe central level of the SUNWELL environment holds the 5 Mains, which run the different modelling aspects of the paper; each code is documented separately. Additional code is located in the __‘DataProcessing’__ and the __‘functions’__ folder. Functions are called in the different Mains.\r\n\r\n__‘InputsFromMatlab’__ contains the radiation and albedo input data sets in separate subfolders (SIS/SISDIR/ALB). The original data is not publicly available, but can be requested for research purposes free of charge. We provide a processed subset of the data set that was used to run the SUNWELL simulations. The MSG subfolder contains additional spatial input data sets.\r\n\r\n__‘Outputs’__ contains the output files from the different mains (matching names, Main_CHallpixels.m  Prod_CHallpixels)\r\n\r\n__‘Publication_figures’__ contains all individual figures from the PNAS publication, as well as the generating code (/code_plot) and the power point figures (/ppts) that provide the combined final figures.\r\n\r\n__‘Validation’__ contains the data sets used in the model validation:\r\n\r\n- Electricity production from three of our validation sites (/WSL), \r\n- Measured irradiance for two validation sites (/ASRB)\r\n\r\n__Electricity__ production from a validation site at Lac des Toules in Wallis (/LDT), this data set was provided under an NDA and cannot be made publicly available. \r\n\r\n__Paper Citation:__\r\n > _Annelen Kahl; Jérôme Dujardin; Michael Lehning (2018). Dataset on PV Production in Snow Covered Mountains. PNAS - Proceedings of the National Academy of Sciences. (in press)_",
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            "notes": "Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).\r\nThe calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX  for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:\r\n\r\n- ICHEC-EC-EARTH\tDMI-HIRHAM5\t2.6\tEUR-11\r\n- ICHEC-EC-EARTH\tDMI-HIRHAM5\t4.5\tEUR-11  \r\n- ICHEC-EC-EARTH\tDMI-HIRHAM5\t8.5\tEUR-11  \r\n- ICHEC-EC-EARTH\tSMHI-RCA4\t2.6\tEUR-11  \r\n- ICHEC-EC-EARTH\tSMHI-RCA4\t4.5\tEUR-11  \r\n- ICHEC-EC-EARTH\tSMHI-RCA4\t8.5\tEUR-11  \r\n- MOHC-HadGEM2-ES\tSMHI-RCA4\t4.5\tEUR-11  \r\n- MOHC-HadGEM2-ES\tSMHI-RCA4\t8.5\tEUR-11  \r\n- MPI-M-MPI-ESM-LR\tSMHI-RCA4\t4.5\tEUR-11  \r\n- MPI-M-MPI-ESM-LR\tSMHI-RCA4\t8.5\tEUR-11  \r\n\r\n__*References*__:\r\n\r\n-\tKöplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.\r\n-\tNational Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.\r\n-\tSchäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.\r\n-\tViviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH.  Part II - Physical model description_, Geographica Bernensia, 40, 1-89.\r\n-\tViviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.\r\n-\tViviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation  for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.",
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                    "description": "Species trait (i.e. adult body size, home range mobility behaviour, circadian activity and schooling) data gathered from the General Approach to Species Abundance Relationships (GASPAR) database (Kulbicki et al. 2013, Parravicini et al. 2013). \r\n\r\nKulbicki, M. et al. 2013. Global biogeography of reef  shes: a hier- archical quantitative delineation of regions. – PLoS One 8: e81847.\r\n\r\nParravicini, V. et al. 2013. Global patterns and predictors of tropi- cal reef  sh species richness. – Ecography 36: 1254–1262.\r\n\r\nTo complement the trait data with Pelagic Larval Duration information refer to the following publication:\r\n\r\nLuiz, Osmar J., et al. \"Adult and larval traits as determinants of geographic range size among tropical reef fishes.\" Proceedings of the National Academy of Sciences 110.41 (2013): 16498-16502.\r\n\r\nIn Donati et al. \"A process-based model supports an association between dispersal and the prevalence of species traits in tropical reef fish assemblages\" accepted in Ecography in August 2019, we used the PLD gathered from Luiz et al. 2013 as described in the methods - section \"Species trait data\".\r\n\r\n",
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            "notes": "The data presented here corresponds to the publication \"Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain\" (Gerber et al., 2018a), which investigates the precipitation variability of snow precipitation in the central northern part of the Grisons (CH) and the publication \"The importance of near-surface winter precipitation processes in complex alpine terrain\" (Gerber et al., 2018b). The dataset contains:\r\n\r\n* WRFsimulations: WRF simulation output for simulations with 4x (14x) terrain smoothing with an output timestep of 30 min/5 min and horizontal grid spacings of 1350 m, 450 m, 150 m and 50 m (currently: data available upon request).\r\n* StationData: Meteorological station data of 18 meteorological stations in the central northern part of the Grisons with 30 minute resolution for the period 1 January 2016 till 1 May 2016.\r\n* ADS80data: Photogrammetrically determined snow depth distribution data over the Dischma valley for the 26 January 2016 and 9 March 2016. Snow heights are corrected for buildings, vegetation (> 1m), outliers, and pixles, which are obivously snow-free on the pictures (Bühler et al., 2015). In addition the snow depth differences (snow depth on 9 March 2016 minus snow depth on 26 January 2016) are provided.\r\n\r\nFor more details about the simulation and observation data, see Gerber et al., 2018 and Gerber and Sharma (2018).\r\n\r\n__Publications:__\r\n\r\nBühler, Y., Marty, M., Egli, L., Veitinger, J., Jonas, T., Thee, P., and Ginzler, C.: Snow depth mapping in high-alpine catchments using digital photogrammetry. Cryosphere, 9, 229–243, doi:10.5194/tc-9-229-2015, 2015.\r\n\r\nGerber, F., Besic, N., Sharma, V., Mott, R., Daniels, M., Gabella, M., Berne, A., Germann, U., and Lehning, M.: Spatial variability in snow precipitation and accumulation in COSMO-WRF simulations and radar estimations over complex terrain, The Cryosphere, 12, 3137–3160, doi:10.5194/tc-12-3137-2018, 2018.\r\n\r\nGerber, F., Mott, R. and Lehning, M.: The importance of near-surface winter precipitation processes in complex alpine terrain, Journal of Hydrometeorology, accepted, 2018.\r\n\r\nGerber, F., and Sharma, V.:  Running COSMO-WRF on very-high resolution over complex terrain. Laboratory of Cryospheric Sciences CRYOS, École Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland. doi:10.16904/envidat.35, 2018.",
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            "notes": "Table of Content: 1. General context of the data set \"lsUDPs\" ; 2. Background and aims of the study using the data set lsUDPs; 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalisation\r\n\r\n1. General context of the data set \"lsUDPs\"\r\nThe data set \"lsUDPs\" has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2020. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, strategic spatial plans) into quantitative land-change modelling approaches at the urban regional level. The first stage (2016-2017) of the CONCUR project focussed on 21 urban regions in Western Europe. The urban regions were selected through a multi-stage strategy for empirical research (see Hersperger, A. M., Grădinaru, S., Oliveira, E., Pagliarin, S., & Palka, G. (2019). Understanding strategic spatial planning to effectively guide development of urban regions. Cities, 94, 96–105. https://doi.org/10.1016/j.cities.2019.05.032 ).\r\n\r\n2. Background and aims of the study using the data set lsUDPs\r\nAs part of the CONCUR project, a specific task was to examine the relationship between strategic spatial plans and the formulation and implementation (i.e. urban land change) of large-scale urban development projects in Western Europe.\r\nStrategic urban projects are typically large-scale, prominent urban transformations implemented locally with the aim to stimulate urban growth, for instance in the form of urban renewals of deprived neighborhoods, waterfront renewals and transport infrastructures. While strategic urban projects are referred to in the literature with multiple terms, in the CONCOR project we call them large-scale urban development projects (lsUDPs).\r\nPrevious studies acknowledged both local and supra-local (or structural) factors impacting the context-specific implementation of lsUDPs. Local governance factors, such as institutional capacity, coordination among public and private actors and political leadership, intertwine with supra-local conditions, such as state re-scaling processes and devolution of state competencies in spatial planning, de-industrialisation and increasing social inequality. Hence, in implementing lsUDPs, multi-scalar factors act in combination.\r\nBecause the formulation and implementation of lsUDPs require multi-scalar coordination among coalitions of public and private actors over an extended period of time, they are generally linked to strategic spatial plans (SSPs). Strategic spatial plans convey collective visions and horizons of action negotiated among public and private actors at the local and/or regional level to steer future urban development, and can contain legally binding dispositions, but also indicative guidelines.\r\nThe key question remains as to what extent large-scale urban development projects and strategic spatial plans can be regarded as aligned. By alignment, or “concordance”, we mean that strategic projects are formulated and implemented as part of the strategic planning process (“high concordance”), or that the strategic role of projects is reconfirmed in (subsequent) strategic plans (“moderate concordance”). Lack of concordance is found when lsUDPs have been limitedly (or not at all) acknowledged in strategic spatial plans.\r\nWe assume that certain local and supra-local factors, characterising the development of the projects, foster (but not strictly “cause”) the degree of alignment between lsUPDs and SSPs. In this study, we empirically examine how, and to what extent, the concordance between 38 European large-scale urban development projects and strategic plans (outcome: CONCOR) has been enabled by five multi-scalar factors (or conditions): (i) the role of the national state (STATE), (ii) the role of (inter)national private actors (PRIVATE), (iii) the occurrence of supra-regional external events (EVENTS), (iv) the degree of transport connectivity (TRANSP), and (v) local resistance from civil society (RESIST). We adopted a (multi-data) case-based qualitative strategy for empirical research and applied the formalised procedure of within- and cross-case comparison offered by fuzzy-set Qualitative Comparative Analysis appropriate for the goal of this study. Based on set theory, QCA formally integrates contextual sensitivity to case specificities (within-case knowledge) with systematic comparative analysis (across-case knowledge).\r\nThe research question the data set has been created to reply to is the following: which conditions, and combinations of conditions, enable the concordance between large-scale urban development projects and strategic spatial plans?\r\nThe conditions (“independent variables”) considered are. STATE: the set of large-scale urban projects characterized by a high degree of state intervention and support in their formulation and implementation, PRIVATE: the set of large-scale urban projects characterized by a high degree of involvement of (inter)national private actors in their formulation and implementation, EVENTS: the set of large-scale strategic projects whose formulation and implementation have been strongly affected by unforeseen international events and/or global trends, TRANSP: the set of large-scale strategic projects with a high degree of road and/or transit connectivity, and RESIST: set of large-scale strategic projects whose realization has been characterized by resistances that have substantially delayed or modified the project implementation.\r\nThe outcome (“dependent variable”) under analysis is CONCOR: the set of large-scale urban projects having a high degree of concordance/alignment/integration with strategic spatial plans \r\n\r\n3. The data set lsUDPs\r\n\r\n      3.1 Selection of cases and data collection\r\nTo generate the current data set on large-scale urban development projects in European urban regions (data set \"lsUDPs\"), we identified 35 large-scale urban development projects in a sample of the 21 Western urban regions considered in the CONCUR project (see supra, Hersperger et al. 2019): Amsterdam, Barcelona, Copenhagen, Hamburg, Lyon, Manchester, Milan, Stockholm, Stuttgart. The criteria we followed to identify the 35 large-scale urban development projects are: geographical location, size (large-scale), site (located either in the city core or in the larger urban region) and urban function (e.g. housing, transportation infrastructures, service and knowledge economic functions). Employing these criteria facilitated the selection of diverse large-scale urban development projects while still ensuring sufficient comparability.\r\nIn 2016, we performed 47 in-depth interviews with experts in urban and regional planning and large-scale strategic projects and infrastructure (i.e. academics and practitioners) about the formulation, implementation and development (1990s–2010s) of each project in each of the 9 selected urban regions. On average, each interviewee answered questions on 3.1 large-scale urban development projects. Three cases were subdivided into two cases because a clear differentiation between specific implementation stages was identified by the interviewees (expansion of the Barcelona airport, cases “bcn_airport80-90” and “bcn_airport00-16”; realisation of Lyon Part-Dieu, cases “lyo_partdieu70-90” and “lyo_partdieu00-16”; MediaCityUK, cases “man_salfordquays80-00” and “man_mediacityuk00-16”). Therefore, from the initial 35 cases, the final number of analysed cases in the lsUDPs dataset is 38.\r\n\r\n       3.2 The data set lsUDPs: Data management and operationalisation\r\nInterviews were fully transcribed and analysed through MAXQDA (version 12.3, VERBI GmbH, Berlin, Germany), and intercoder agreement was evaluated on a sample of nine interviews. We also compiled “synthetic case descriptions” (SCD) for each case (totalling more than 160 SCDs) to spot potential inconsistencies among interviewees’ accounts and to facilitate completion of the “calibration table” for each case (see below). An online expert survey distributed to the interviewees (response rate 78%) helped systematise the information collected during the interviews. We also consulted both academic and gray literature on the case studies to check for possible ambiguity and inconsistencies in the interview data, and to solve discrepancies between our assigned set membership scores and questionnaire values. Site visits were also carried out to retrieve additional information on the selected cases.\r\nFor each case (i.e. each of the 38 selected large-scale urban development projects), we operationalised each condition (i.e. STATE, PRIVATE, EVENTS, TRANSP, RESIST) and the outcome (CONCOR) in terms of sets, for subsequent application of Qualitative Comparative Analysis. This process is called “calibration”; we used a number of indicators for each condition to qualitatively assess each large-scale project across the conditions. The case-based qualitative assessment was then transformed into fuzzy-set membership values. Fuzzy-set membership values range from 0 to 1, and should be conceived as “fundamentally interpretative tools” that “operationalize theoretical concepts in a way that enhances the dialogue between ideas and evidence” (Ragin 2000:162, in “Fuzzy-set Social Science”. Chicago: University Press). We employed a four-value fuzzy-set scale (0, 0.33, 0.67, 1) to “quantify” into set membership scores the individual histories of cases retrieved from interview data. Only the condition TRANSP was calibrated as a crisp-set (0, 1). \r\nThe translation of qualitative case-based information into numerical fuzzy-set membership values was iteratively performed by populating a calibration table following standard practices recently emerged in QCA when dealing with qualitative (interview) data.\r\n",
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                    "description": "Data has been collected from summer 2011 to 2016. \r\n\r\n\r\nMain reasons for NA values: \r\n\r\n-\tD. kuriphilus still not arrived in the site.\r\n-\tNo galls were found during the field sampling.\r\n-\tSite has not been sampled in the correspondent year because of time, weather or money constrains.\r\n-       T. sinensis not found in the galls\r\n\r\n\r\nVariable description:\r\n\r\nYear = sampling year.\r\n\r\nCoordinate, elevation, slope, aspect = average site characteristics.\r\n\r\nts_arrival = T. sinensis arrival year.\r\n\r\ndk_arrival = D. kuriphilus arrival year.\r\n\r\ndk_parasitism_by_ts = D. kuriphilus parasitism rate by T. sinensis. Formula: (no. of T. sinensis/ no. of D. kuriphilus chambers) * 100 at gall level.\r\n\r\ndk_infestation = Percentage of attacked buds. Formula: no. of attacked buds / no. of total developed buds*100 (as presented in Kotobuki et al. 1985) at shoot level.\r\n\r\nts_per_bud = number of alive T. sinensis individual calculated at bud level.\r\n\r\ndk_per_bud = number of alive D. kuriphilus individual calculated at bud level.\r\n\r\ndk_pot_per_bud = overall number (dead and alive) D. kuriphilus individual calculated at bud level.\r\n\r\ntotal_gall_nr_per_bud = average gall number per bud.\r\n\r\nchamber_per_galls = average D. kuriphilus chamber number per gall.\r\n\r\nFor details see the submitted publication with the same name\r\n\r\n\r\nReferences\r\nKotobuki, K., Mori, K. and Sato, Y. (1985) ‘2 methods to estimate the tree damage by chestnut gall wasp Dryocosmus-kuriphilus’, Bulletin of the fruit tree research station A (Yatabe), 2(12), pp. 29–36.\r\n\r\n",
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            "notes": "The wind-driven saltation of sand and snow shapes dunes and ripples, generates dust emission, and erodes the surface of the Antarctic ice sheet. Here, we use a model based on the discrete element method to simulate grain-flow interactions and study the effect of particle cohesion on saltation dynamics. \r\n\r\nThe data contains the model output of granular splash simulations and saltation simulations. Granular splash, the main particle entrainment process in saltation, occurs upon impact of saltating particles with the granular bed. We performed Monte Carlo simulations of granular splash for loose sand grains and for cohesive ice grains. The analysis indicate that different values of cohesion have significant effects not on the number of splashed grains, on the ejection velocity, and the rebound velocity.\r\n\r\nIn our saltation simulations, we trigger particle movement with a single splash event at the inlet section section and let the system evolve until steady state. Our results show that saltation over cohesive surfaces is difficult to initiate but easy to sustain at low wind speed. The occurrence of transport thus depends on the history of the wind speed, a phenomenon known as hysteresis. We also show that saltation over cohesive surfaces presents higher mass fluxes but requires longer distances to saturate, which increases the size of the smallest stable surface ripples. Our model results have implications for large-scale aeolian processes on Earth and Titan, where sand grains are thought to be very cohesive.",
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                "description": " The Research Unit investigates natural hazard processes in mountainous areas, in particular the triggering and propagation of floods, sediment transport, landslides, debris flows and rock fall. Process studies on the scale of slopes, channels and catchments form the basis for the development of simulation models and of hazard assessment procedures and for the design of countermeasures. To this end worldwide unique observation systems are developed, such as a debris flow balance and geophone systems for bedload transport. Damage and damaging processes due to frequent and extreme events are assessed as prerequisites for the risk-based and sustainable management of natural hazards.\r\n\r\nA second focus of the unit is on the estimation and prediction of snow and water resources, e.g. for hydropower production or early recognition of drought. The unit operates a snow hydrological service for federal and cantonal agencies and a drought information platform for a broad range of water users.\r\n\r\n__Further information__: https://www.wsl.ch/en/about-wsl/organization/research-units/mountain-hydrology.html",
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            "language": "de",
            "doi": "10.16904/envidat.software.1",
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            "notes": "Cable-based technologies have been a backbone for harvesting on steep slopes. The layout of a single cable road is challenging because one must identify intermediate support locations and heights that guarantee structural safety and operational efficiency while minimizing set-up and dismantling costs. Seilaplan optimizes the layout of a cable road by\r\nSeilaplan stands for Cable Road Layout Planner. Seilaplan is able to calculate the optimal rope line layout (position and height of the supports) between defined start and end coordinates on the basis of a digital elevation model (DEM).\r\nThe program is designed for Central European conditions and is designed on the basis of a fixed suspension rope anchored at both ends. For the calculation of the properties of the load path curve an iterative method is used, which was described by Zweifel (1960) and was developed especially for standing skylines. When testing the feasibility of the cable line, care is taken that 1) the maximum permissible stresses in the skyline are not exceeded, 2) there is a minimum distance between the load path and the ground and 3) when using a gravitational system, there is a minimum inclination in the load path. The solution is selected which has a minimum number of supports in the first priority and minimizes the support height in the second priority.\r\nThe newly developed method calculates the load path curve and the forces occurring in it more accurately than tools available on the market to date (status 2019) and is able to determine the optimum position and height of the intermediate supports.\r\nThe reason for the more accurate results of the new tool is the assumption that the skyline is anchored at both end points. Forest cable yarders used in Europe have a skyline that is fixed at both ends. The behaviour of fixed-anchored suspension ropes is very difficult to describe mathematically and cannot be solved analytically. For this reason, simplified linearized assumptions have so far been used in the forestry sector, which corresponds to the behaviour of a weight-tensioned suspension rope and is known as the Pestal method (1961). Weight-tensioned suspension ropes are used for passenger transport. \r\nFor the calculation of the load path curve we use an iterative method, which was described by Zweifel (1960) and developed especially for fixed anchored suspension ropes. This makes mathematics much more demanding, but leads to more accurate and realistic results. Since there are no current models which describe the installation costs with adequate accuracy, the solution sought is the one which has a minimum number of supports in the first priority and minimises the support height in the second priority (Figure 2). The presented method is the first one, which starts from a fixed anchored supporting rope and identifies the mathematically optimal column layout at the same time. In contrast to methods that assume a weight-tensioned suspension rope, this approach achieves more realistic solutions with longer spans and lower support heights, which ultimately leads to lower installation costs. Background information on rope mechanics and calculation methods is documented in Bont and Heinimann (2012).\r\n\r\nLicense: GNU, General Public License, Version 2 or newer.\r\n\r\nLiterature:\r\nBont, L., & Heinimann, H. R. (2012). Optimum geometric layout of a single cable road. European journal of forest research, 131(5), 1439-1448.",
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                    "description": "Shapefile of 307 catchments for which estimates of water supply, demand, and reservoir volumes are provided. The OBJECTID entry corresponds to the catchment ID which is used as a reference in the other datasets provided.",
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                    "description": "Reservoir volume for the 307 medium-sized catchments for different storage categories: natural lakes, artificial reservoirs, reservoirs for artificial snow production, drinking water reservoirs, and usable volumes of natural lakes.  Unit: Mio m<sup>&#xb3;</sup>. One column per catchment (see shapefile).",
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                    "description": "Simulated discharge series for a reference period 1981-2010 and till the end of the century. Data are provided for 39 climate model chains and a control run based on the observed meteorology. Data are provided at daily resolution (mm/d). ",
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                    "description": "Water demand estimates for the 307 medium-sized catchments for different categories for current and future conditions. One text file is provided per demand category. One column corresponds to one catchment (IDs compare to shapefile), The data are provided at monthly resolution in mm/d and can be converted to volumes by using the catchment area. E.g. \r\nQ[mm/d] * catchment area [m<sup>&#xb2;</sup>] /1000 = Q[m<sup>&#xb3;</sup>/d] \r\nor to obtain discharge in m<sup>&#xb3;</sup>/s \r\nQ[mm/d] * catchment area [m<sup>&#xb2;</sup>]/1000/24/3600 = Q [m<sup>&#xb3;</sup>/s].\r\nFuture irrigation and hydropower water demand are provided per climate model chain. ",
                    "name": "Water demand version 2 (corrected version)",
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                    "url": "https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/15462633-0157-4027-9f17-1e80ec4c1f92/download/demand.zip",
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                    "description": "Warning: please use the corrected version 2, since this file contains errors for certain categories such as Livestock, Industry or Houshold. \r\n\r\nWater demand estimates for the 307 medium-sized catchments for different categories for current and future conditions. One text file is provided per demand category. One column corresponds to one catchment (IDs compare to shapefile), The data are provided at monthly resolution in mm/d and can be converted to volumes by using the catchment area. E.g. \r\nQ[mm/d] * catchment area [m<sup>&#xb2;</sup>] /1000 = Q[m<sup>&#xb3;</sup>/d] \r\nor to obtain discharge in m<sup>&#xb3;</sup>/s \r\nQ[mm/d] * catchment area [m<sup>&#xb2;</sup>]/1000/24/3600 = Q [m<sup>&#xb3;</sup>/s].\r\nFuture irrigation and hydropower water demand are provided per climate model chain. ",
                    "name": "Water demand (deprecated)",
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                    "url": "https://www.envidat.ch/dataset/3fc83159-6e65-47f9-9fd8-dd60f749fda4/resource/ab06042e-059a-40b0-b9da-101958dab5e7/download/demand.zip",
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                    "display_name": "CLIMATE CHANGE",
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                    "display_name": "RESERVOIRS",
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            "language": "en",
            "doi": "10.16904/envidat.69",
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            "name": "hydro-ch2018-reservoirs",
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            "notes": "The dataset Hydro-CH2018 reservoirs provides estimates of current and future water supply, water demand, and storage volumes for 307 medium-sized catchments in Switzerland. \r\nWater supply for current (1981-2010) and future (2070-2099) climate conditions was simulated using the hydrological model PREVAH. For modeling current water supply, observed meteorological time series were used as input, while simulated meteorological time series derived from 39 model chains of the CH2018 initiative were used as an input for simulating future climate conditions.\r\n\r\nWater demand was estimated for six categories: \r\n\r\n- 1) Drinking water (households and tourism),\r\n- 2) industry (second and third sector), \r\n- 3) artificial snow production, \r\n- 4) agriculture (irrigation and livestock feeding), \r\n- 5) ecology (residual flows), and \r\n- 6) hydropower.\r\n\r\nFuture estimates consider changes in demand related to population growth and changes in the hydrological conditions.\r\nStorage volumes are provided for natural lakes (storage capacities and usable volumes), artificial reservoirs, reservoirs for artificial snow production, and drinking reservoirs.\r\n\r\nA detailed description of the simulation and estimation procedures can be found in \r\n\r\n*   Brunner, M.I., Björnsen Gurung, A., Zappa, M., Zekollari, H., Farinotti, D., Stähli, M., 2019. Present and future water scarcity in Switzerland: Potential for alleviation through reservoirs and lakes. Sci. Total Environ. 666, 1033–1047. https://doi.org/10.1016/j.scitotenv.2019.02.169.\r\n\r\nThis dataset contains the following information:\r\n\r\n1.\tShapefile with the 307 medium-sized Swiss catchments.\r\n2.     Textfiles with the water supply simulations for the control run and the 39 climate model chains (one file per chain) at daily resolution for the 307 catchments.\r\n3.\tTextfiles with the current and future demand estimates per category at monthly resolution for the 307 catchments.\r\n4.\tTextfiles with the storage volumes per category and catchment.",
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            "title": "Hydro-CH2018 reservoirs",
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            "maintainer": "{\"affiliation\": \"Swiss Federal Institute for Forest Snow and Landscape Research WSL, Zuercherstrasse 111, 8903 Birmensdorf, Switzerland\", \"identifier\": \"\", \"given_name\": \"Anne\", \"name\": \"Thimonier\", \"email\": \"anne.thimonier@wsl.ch\"}",
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                "description": "__Air pollution and climate change have an effect on the forest. We examine these effects as part of the Long-Term Forest Ecosystem Research (LWF) programme.__\r\n\r\nWe need reliable information in order to record the condition of the forest on an ongoing basis and to understand precisely what happens in the forest when the environment changes. An important source of data here is the Long-Term Forest Ecosystem Research (LWF) programme. It consists of 19 permanent monitoring sites on which we have regularly carried out numerous measurements since 1994. We have also been recording the health of trees on the monitoring sites of the Sanasilva Inventory, which is part of the LWF programme (see Sites), since 1985.\r\n\r\nWe disclose the gathered data, as well as the scientific interpretation of this data, to national and international decision-makers.\r\n\r\nWith the legally enshrined functions of the LWF programme, Switzerland participates in international research programmes such as the \"International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests\" ICP Forests and the LTER-Europe Network (Long-Term Ecosystem Research in Europe).\r\n\r\nThe Long-term Forest Ecosystem Research (LWF) programme is run and financed by the WSL.\r\n \r\n### Objectives of the programme\r\n\r\n *   Early detection and a representative assessment of changes in forest condition\r\n *   Determination of external influences, both from anthropogenic and natural sources and their effect on the forest ecosystem (element inputs, climate)\r\n *    Determination of changes in important components within the forest ecosystem\r\n *   Development of indicators to assess the condition of the forest\r\n *   Integrated risk assessment based on different stress scenarios\r\n *   Extended platform for internal and external research projects\r\n\r\n__Further information__: https://www.wsl.ch/en/forest/forest-development-and-monitoring/long-term-forest-ecosystem-research-lwf.html",
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            "id": "f99d408c-624f-4e6c-b51e-6a1bc2250d00",
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            "notes": "Stemflow (portion of precipitation running down the branches and the trunk and depositing at the base of the tree) can represent a substantial fraction of the total water and nutrient input in stands of smoothbarked species with upright branches. Stemflow was measured with silicone gutters installed on the trunk of 5 trees at three LWF plots during 1-2 years. High capacity containers were used at Novaggio. An automated tipping bucket system, allowing continuous recording of volumes and sampling of representative proportional fraction, is currentlx used at the LWF sites Laegeren, Lausanne, Othmarsingen and Schänis. \r\n\r\n### Purpose: ###\r\n\r\nTo quantify the contribution of stemflow to the water and nutrient budget and to the atmospheric deposition in selected forests stands.\r\n\r\n\r\n\r\n### Manual Citation: ###\r\n\r\n * Thimonier, A., Brang, P., Wenger, K., 1997. Kapitel C4. Atmosphärische Deposition: Freiland- und Bestandesniederschläge, in: Brang, P. (Ed.), Aufnahmeanleitungen aller Forschungsprojekte auf Flächen der Langfristigen Waldökosystem-Forschung (LWF). Eidg. Forschungsanstalt WSL, Birmensdorf, pp. 1-48. \r\n\r\n *  Clarke  N,  Žlindra  D,  Ulrich  E,  Mosello  R,  Derome  J,  Derome  K,  König  N,  Lövblad  G,  Draaijers  GPJ,  Hansen K, Thimonier A, Waldner P, 2016: Part XIV: Sampling and Analysis of Deposition. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling,  assessment,  monitoring  and  analysis  of the  effects  of  air  pollution  on  forests.  Thünen  Institute    of    Forest    Ecosystems,    Eberswalde,    Germany,    32    p.    +    Annex    [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual)\r\n\r\n",
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            "notes": "This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.\r\nThe following information is contained (by column and column title):  \r\n\r\n* year\r\n* total number of hazard fatalities\r\n* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.\r\n* number of fatalities by debris flow (German: Murgang).\r\n* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).\r\n* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).\r\n* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.\r\n* number of fatalities by lightning (German: Blitz).\r\n* number of fatalities by ice avalanche (German: Eislawine).\r\n* number of fatalities by earthquake (German: Erdbeben).\r\n* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).\r\n\r\nThe data was collected based on newspaper research. For more information please refer to \r\n\r\n_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._\r\n\r\nThe data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.\r\n\r\n__Restrictions: The data set is not complete.__ Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).\r\n\r\nFatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).\r\n",
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            "notes": "This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm. The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.\r\n\r\nA detailed description is given here:\r\n\r\nBühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.\r\n\r\nAbstract:\r\nDetailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain. \r\nRemote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass. This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.\r\n",
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            "notes": "# Abstract\r\nSnow and hydrological modeling in alpine environments remains a challenge because of the complexity of the processes complexity affecting the mass and energy balance. This study examines the influence of snowmelt on the hydrological response of a high-alpine catchment of 43.2 km2 in the Swiss Alps during the water year 2014-2015. Based on recent advances in Alpine3D, we examine how modeled snow distributions, and modeled liquid water transport within the snowpack influence runoff dynamics. By combining these results with multi-scale field data (snow lysimeter data, distributed snow depths and streamflow), we demonstrate the added value of a more realistic representation of snow distribution at the onset of melt season. At the site scale, snowpack runoff is well simulated when the snowpack mass balance errors are corrected (R2 = 0.95 vs. R2 = 0.61). At the sub-basin scale, a more heterogeneous snowpack leads to a more rapid runoff pulse originated in the shallower areas while an extended melting period (by more than a month) is caused by slower snowmelt from deeper areas. This result is a marked improvement over results obtained using a less heterogeneous snow distribution (i.e., traditional precipitation interpolation method). Catchment hydrological response is also improved by the more realistic representation of snowpack heterogeneity (Nash coefficient of 0.85 vs. 0.74), even though the calibration process smoothens out the differences. \r\nThe added value of a more complex liquid water transport scheme is obvious at the site scale but decreases at the sub-basin and basin scales. Our results highlight not only the importance but also the difficulty of getting a realistic snowpack distribution even in a well-instrumented area and present a model validation from multi-scale experimental datasets.",
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            "notes": "The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below. \r\n\r\n__Publication__ http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract\r\n",
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                    "description": "We drilled six boreholes in two clusters. The boreholes reached a depth between 2 and 9 m below the ground surface. The lower half of boreholes BH1 and BH6 were cored with a 9 cm-diameter rotational diamond drilling head. The other boreholes were drilled destructively with an 11 cm-diameter Mitsubishi hammer system. Boreholes BH1, BH2 and BH5 were equipped with open standpipe piezometers, whereas BH3, BH4 and BH6 were equipped with a special piezometer system composed of an enclosed measuring cell at the bottom of a 1 inch-PVC tube. The free groundwater level in the PVC tube is measured in the standpipe piezometer, but it doesn’t necessarily represent the water table in the soil layer because the pressure sensor is located in the sealed lower part of the piezometer in the enclosed measuring cell and thus is not in contact with the air. This system allows the hydraulic pressure of lithologies with low permeability to be measured directly. Two piezometers were installed in BH6 at different depths. The PVC tubes were slotted at the bottom for 0.5, 1 or 2 meters and the boreholes were sealed carefully with clay pellets above this filter section to avoid by-pass and infiltration from the surface. DCX-22 pressure sensors from Keller AG Winterthur, with integrated data loggers, were installed in each piezometer to measure the relative hydraulic pressure at a 30 minute-intervals from November 2010 to November 2011. The data were corrected for in-situ air-pressure fluctuations.",
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            "notes": "Rufiberg is a pre-alpine meadow site in Switzerland where shallow landslides have been observed after past intense rain storms. In order to assess the triggering mechanisms of these landslides, a comprehensive investigation was conducted within the project TRAMM from Nov 2009 to Oct 2012. It included meteorological observations, soil moisture measurements, bedrock groundwater measurements. The Rufiberg is located at the NW side of the Gnipen to the north of the village Arth-Goldau in the Canton of Schwyz. In the summer months, the site is used for pasturing. Usually, from December to March a snow cover is present at the Rufiberg. The site is at an altitude between 1080 – 1180 m asl, is ENE oriented, and has an average slope of 30 -35°. The Subalpine Molasse in the region is inclined with 30 - 35° to SE. In the area of the field site, beds of conglomerate with several m of thickness alter with beds of sandstone and marlstone. A ca. 2 – 5 m thick eluvium/colluvium layer composed of silty and sandy clay covers the bedrock. This site has been chosen because on one hand, during heavy rainfall events, e.g. autumn 2005, numerous landslides occur in the region of the Gnipen and the Rufiberg. On the other hand, the Rufiberg is very appropriate for experiments due its location away from infrastructures and due to its accessibility. The goal of the investigation was to understand the hydrology and hydrogeology of the slope with regard to shallow landslides. \r\n\r\nMore information: Brönnimann, C., Stähli, M., Schneider, P., Seward, L. and Springman, S.M. 2013. Bedrock exfiltration as a triggering mechanism for shallow landslides. Water Resources Research, 49 (9): 5155–5167. DOI: 10.1002/wrcr.20386.\r\n",
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            "notes": "A landslide testsite dataset related to pore water pressure perturbations on the stability of unsaturated silty sand slopes leading to the initiation and propagation of the shear deformations and eventual rapid mass movements. This project was initiated and led by the Institute of Geotechnical Engineering (IGT) of the Swiss Federal Institute of Technology (ETH Zurich) and was incorporated in a Swiss national (TRAMM) and a European Union (SafeLand) multidisciplinary research project. Field site: The experimental slope is 7.5 m wide by 35 m long, located in the Swiss lowlands on an east facing slope over-looking the river Rhine, at an altitude of ~ 350 masl. Originally there were forestry covertures of circa 80%, heights of 5-20 m. Shrubs up to 1-5 m high and a free herb layer covered ~ 50% of the surface. The average gradient was determined to be from 38° to 43° with a slightly concave surface. The underlying rock consists mainly of Molasse, which is formed by alternate layers of sea deposits under the Tethys Sea (Seawater Molasse) and land deposits (Freshwater Molasse). Several augured samples, as well as an outcrop of the bedrock about 20 m above the selected field, revealed horizontal layering of fine grained sand- and marlstone at the test site. The sandstone was later proven to be highly permeable and fissured. Grain-size distributions were determined and the soil was classified as medium-low plasticity silty sand. Site instrumentation:Measurements of soil suction, groundwater level, soil volumetric water content, rain intensity and soil temperature were taken and combined with geophysical monitoring using Electrical Resistance Tomography (ERT) and investigations into subsurface flow by means of tracer experiments. Deformations were monitored during the experiment, both on the surface via photogrammetrical methods and within the soil mass, using a flexible probe equipped with strain gauges at different points and two axis inclinometers on the top and acoustic sensors. Instruments were installed mainly in three clusters at depths of 15, 30, 60, 90, 120, and 150 cm below the ground surface over the slope, including jet-fill tensiometers, TDRs, Decagon TDRs, piezometers, soil temperature sensors, deformation probes, earth pressure cells, acoustic sensors and rain gauges. A ring-net barrier (provided by Geobrugg AG) was set up at the foot of the slope to protect the road. Experiments: A sprinkling experiment was carried out in September 2008 to investigate the hydrological and mechanical response of the slope (Experiment 1), followed by a second one to trigger a landslide in March 2009 (Experiment 2). \r\n\r\n__Publications__\r\n\r\n1. Lehmann, P., F. Gambazzi, B. Suski, L. Baron, A. Askarinejad, S. M. Springman, K. Holliger, and D. Or (2013), Evolution of soil wetting patterns preceding a hydrologically induced landslide inferred from electrical resistivity survey and point measurements of volumetric water content and pore water pressure, Water Resour. Res., 49, 7992–8004, doi:[10.1002/2013WR014560](http://dx.doi.org/10.1002/2013WR014560).\r\n\r\n2. Springman, S. M., Kienzler, P., Casini, F., & Askarinejad, A. (2009). Landslide triggering experiment in a steep forested slope in Switzerland. In 17th International Conference of Soil Mechanics and Geotechnical Engineering, Alexandria, Egypt (pp. 1698-1701). doi: [10.3233/978-1-60750-031-5-1698](http://dx.doi.org/10.3233/978-1-60750-031-5-1698)\r\n",
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            "notes": "Total water reserves of the snow cover [mio m3] for Wägital catchment, Switzerland, for reference date April 1. Data is separated in 2 elevation zones 900m-1500m asl and 1500m-2300m asl. Time period 1943-2019, status 2019-04-24.\r\n\r\nFunded currently or in the past by:\r\n\r\n- Federal Office of Meteorology and Climatology MeteoSwiss in the context of GCOS Switzerland\r\n- Meteodat GmbH\r\n- Institute of Geography, University of Zurich\r\n- WSL Institute for Snow and Avalanche Research SLF\r\n- Institute of Geography, ETH Zurich (IAC ETH Zurich)\r\n- AG Kraftwerk Wägital (AXPO and EWZ)\r\n\r\nSee also https://www.meteodat.ch/waegital.html",
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            "notes": "Silvopastoral systems are highly productive and combine long-term wood production with annual provision of forage for livestock. In the Swiss Jura Mountains these systems are a key component of the landscape. As in other cold biomes, climate change can potentially accelerate landscape change within these historically sustainable systems.\r\n\r\nIn order to anticipate the evolution of subalpine wooded pasture ecosystems under future climate and land-use changes, this project focused on the interplay between soil, vegetation and climate. It was aimed at providing experimental evidence for chief ecosystem processes, with emphasis on the quality of the ecosystem services provided. The main interest was placed on vegetation turf resistance to climate change along an unwooded – sparsely wooded - densely wooded pasture gradient (land-use intensity), where plant productivity, diversity and succession along with rates of carbon cycling and microbial activity provided measures of ecosystem functioning at both plot and landscape level.\r\n\r\nExperimental transplantation of monolith soil turfs to lower altitudes allowed to simulate soil warming and reduced annual precipitation. In order to simulate a year-round warmer and drier climate the natural climate variation along an altitudinal gradient was used as a proxy. The aim was to simulate realistic climate change scenarios for the second half of the 21st century predicted by the IPCC report and downscaled for Switzerland providing regionalized interpolated projections integrating therein trends for temperature increase and precipitation decrease. By using permanent meteorological stations within the network of the Federal Office of Meteorology and Climatology (MeteoSwiss), we obtained high resolution regional data on the variation of mean annual temperature (MAT) and mean annual precipitation (MAP) in relation to altitude in the Swiss Jura Mountains. We observed a general increase of +0.5 K in MAT and a decrease of -20 % MAP for each 100 m decrease in altitude along the SE slope of the Swiss Jura Mountains. These relationships served for the selection of the transplantation sites such that in comparison to a control site at 1350 m a.s.l. (Combe des Amburnex, N 46°54’, E 6°23’) a +2 K MAT and -20 % MAP was achieved at 1010 m a.s.l. (Saint-George, N 46°52’, E 6°26’), a +4 K MAT and -40 % MAP at 570 m a.s.l., (Arboretum d’Aubonne, N 46°51’, E 6°37’), and a +5 K MAT and -50 % MAP at 395 m a.s.l. (Les Bois Chamblard, N 46°47’, E 6°41’). The two stations at 1010 m a.s.l. and 570 m a.s.l. corresponded to the IPCC scenario A1B for a moderate increase in greenhouse gas emissions and to scenario A2 for a high increase in greenhouse gas emissions, respectively. The station at 395 m a.s.l. was chosen to represent an extreme scenario with climate variables lying at the positive tail distribution of model predictions under the A2 scenario.\r\n\r\nSoil cores were assembled into rectangular PVC boxes of 60  80 cm2 size and of 35 cm height. All mesocosms were dug down to surface level into previously prepared trenches in the ground thus preventing lateral heat exchange with the atmosphere. Since at each site the mesocosms were placed in a common garden with no light interception, mesocosms with turfs from the two wooded pastures were shaded from direct sun light to simulate the natural light conditions in the corresponding habitats. Each mesocosm was equipped with a drainage system and was connected to a water tank thus representing a zero potential lysimeter collecting soil solution and precipitation/snowmelt runoff. ECH2O EC-TM sensor probes coupled to Em50 data-loggers (Decagon Devices, Inc., USA) recorded soil temperature and volumetric water content in each mesocosm at the top-soil (0 to -3 cm) every minute and data were averaged over one hour intervals. Climate parameters at each transplantation site were monitored continuously throughout the experiment by means of automated weather stations (Sensor Scope Sàrl, Switzerland), measuring rain precipitation (non-heated tipping bucket gauges) and air temperature and humidity 2 m above the ground surface at one minute intervals.\r\n\r\nA list of above- and belowground variables were measured to assess the resilience of biogeochemical processes, plant productivity, tree regeneration, and carbon sequestration for each respective land-use practice. Furthermore, the experimental data were used to improve on (parameterization) the existing spatially explicit, dynamic model WoodPaM and refine the modelʼs climatic and land-use variables so that different scenarios of climate change and land use change could be simulated. Natural and management induced disturbance patterns were incorporated into the model. \r\nThe data have been made available within the project CCES Mounted. The climate stations Sensorscope are still in use within the project CLIMARBRE (Wald und Klimawandel, WSL/BAFU).\r\n\r\n#References\r\n\r\n1. Puissant, J., Cécillon, L., Mills, R.T.E., Robroek, B.J.M. Gavazov, K., De Danieli, S., Spiegelberger, T., Buttler, A., Brun, J.J. 2015. Seasonal influence of climate manipulation on microbial community structure and function in mountain soils. Soil Biology and Biochemistry 80: 296–305.\r\n2. Mills, R., K. Gavazov, T. Spiegelberger, D. Johnson and A. Buttler 2014. Diminished soil functions occur under simulated climate change in a sup-alpine pasture, but heterotrophic temperature sensitivity indicates microbial resilience. Science of the Total Environment, vol. 473–474(0): 465-472.\r\n3. Gavazov, K., Spiegelberger, T. and Buttler, A. 2014. Transplantation of subalpine wood-pasture turfs along a natural climatic gradient reveals lower resistance of unwooded pastures to climate change compared to wooded ones. Oecologia (174) : 1425-1435.\r\n4. Peringer A., Siehoff S., Chételat J., Spiegelberger T., Buttler A. & Gillet F. 2013. Past and future landscape dynamics in pasture-woodlands of the Swiss Jura Mountains under climate change. Ecology and Society, 18, 3: 11. DOI: 10.5751/ES-05600-180311. [online] URL: http://www.ecologyandsociety.org/vol18/iss3/art11/\r\n5. Gavazov, K. S., A. Peringer, A. Buttler, F. Gillet and T. Spiegelberger. 2013. Dynamics of Forage Production in Pasture-woodlands of the Swiss Jura Mountains under Projected Climate Change Scenarios. Ecology and Society 18 (1): 38. [online] URL: http://www.ecologyandsociety.org/vol18/iss1/art38/",
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