GitLab

Code to make EnviDat data accessible via OpenDataSwiss scrapers.

SDMs for artic refugia study

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

Implements support for resource storage against multiple popular providers via apache-libcloud (S3, Azure Storage, etc...)

A conceptual model to calculate snow depth from snow water equivalent.

Train and apply a quantile mapping model for snow water equivalent maps

Servlet listing the paths in the S3 EnviDat bucket

Frontend of https://www.wsl.ch/gcnet/

Backend database and API for MastWeb.

This command line utility reads Campbell Scientific binary data files as created by these data loggers and outputs them in ascii format to the standard output. Several output profiles are available: csv, xmgrace, sql, tob32 traditional output. Tob1,

This python code uses the Finite Element library FENICS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format from which the paper figure is reproduced.

Codes to calculate a high resolution of CHELSA

Implementation of an Eulerian-Lagrangian snow transport model in OpenFOAM

Codes for the CHELSA_ISIMIP3b_BA_1km project.

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.."

This is the public repository for the ecostat coffee breaks meeting at 10am every Wednesday.

GC-Net

Frontend for the Envidat platform which provides environmental research data from researchers of the Swiss Federal Institute for Forest, Snow and Landscape.