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Codes for the CHELSA-W5E5 paper

Wind-Topo is a statistical downscaling model for near surface wind fields especially suited for highly complex terrain. It is based on deep learning and was trained with data from 261 stations. Dujardin and Lehning 2022 "Wind-Topo: Downscaling.."

Containerised CKAN, Postgres, Solr using Docker

Container images for simple script execution.

Microservice cron to make EnviDat data accessible via OpenDataSwiss scrapers.

Microservice cron to make EnviDat data accessible via Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH).

Codes related to DN Karger, AM Wilson, C Mahony, NE Zimmermann, W Jetz 'Global daily 1km land surface precipitation based on cloud cover-informed downscaling', arXiv preprint arXiv:2012.10108.

FastAPI implementation of the OAI-PMH protocol, for use with a downstream metadata API.

Workshop material for analysing spatially autocorrelated (SAC) data

Large Eddy Simulation flow solver coupled with Lagrangian Stochastic Model

Codes related to CHELSA EarthEnv project. Karger, D.N., Wilson, A.M., Mahony, C., Zimmermann, N.E., Jetz, W. (in review) 'Global daily 1km land surface precipitation based on cloud cover-informed downscaling', Scientific Data

Codes to SAR scale GCM output