Explore projects

Codes investigating the relationship between extreme climate metrics and foodweb metrics.

Extension that enables blind review of private datasets.

Machine learning models developed for avalanche danger level predictions in Switzerland

SDMs for artic refugia study

Custom CKAN validators for EnviDat.

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

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

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

Django API and data import/export Python software package for long-term environmental monitoring data.

StreamFlow is an extension to the spatially-distributed snow model Alpine3D which allows the user to perform hydrological simulations. On top of discharge and water height, StreamFlow can also compute stream temperature at any point along the stream.

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.

Extension to allow paswordless login to the CKAN API.

Converting S3 based GeoTIFF to COG using rio-cogeo.

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.."