Skip to content

Use Cases

This is a non-exhaustive list of use cases of TopoPyScale.

Please drop us a line about your usage of TopoPyScale to be featured.

Genesis project (2025)

The Genesis project , funded by Horizon Europe, aims to study how climatic risks affect Nature based Solutions in the water sector, in the Macaronesian archipelagos. TopoPyScale was applied to downscale 30 years of ERA5 hourly data to the topography of Canary Islands, Azores, Madeira and Cape Verde, from ~25 km to 180 m DEM (from resampled SRTM data). This data has been used as input to estimate extreme weather events using GEV distribution among other methods, and serve as information to elaborate the risk profiles which engineers and other stackeholders in the project need for further quantitative risk analysis.

SnowMapper.ch Online Dashboard

SnowMapper is a tool that generates high-resolution maps of snow variables (snow height, snow water equivalent and snow melt) at daily timescales. The SnowMapper is an online operational snow mapping and forecasting tool for High-Mountain Central Asia (HMCA). The two main components required to achieve this are the climate downscaling tool TopoPyscale and the Factorial Snow Model, FSM, developed by Richard Essery 1. Visualisation and web deployment is handled by the MCASS package. SnowMapper was developed as a collaboration between the WSL Institute for Snow and Avalanche Research SLF and hydrosolutions GmbH within the SDC-funded projects CROMO-ADAPT and SAPPHIRE.

TopoPyScale has been cited by

  • Concetta Lisella, Alessandra Bottero, Serena Antonucci, Giovanni Santopuoli, and Roberto Tognetti. Resilience to late frost and drought of mixed forests with turkey oak and silver fir in southern italy. Forest Ecology and Management, 580:122539, 2025. doi:https://doi.org/10.1016/j.foreco.2025.122539.
  • Xin Ma, Tonghua Wu, Saruulzaya Adiya, Dashtseren Avirmed, Xiaofan Zhu, Chengpeng Shang, Xuchun Yan, Peiqing Lou, Dong Wang, Jie Chen, Amin Wen, and Yune La. Spatiotemporal variations of permafrost extent in mongolia during 1950–2022. Ecological Indicators, 166:112558, 2024. doi:https://doi.org/10.1016/j.ecolind.2024.112558.
  • Robin B. Zweigel, Avirmed Dashtseren, Khurelbaatar Temuujin, Kristoffer Aalstad, Clare Webster, Simone M. Stuenzi, Kjetil S. Aas, Hanna Lee, and Sebastian Westermann. Simulating the thermal regime and surface energy balance of a permafrost-underlain forest in mongolia. Journal of Geophysical Research: Earth Surface, 129(6):e2023JF007609, 2024. e2023JF007609 2023JF007609. doi:https://doi.org/10.1029/2023JF007609.
  • Meven Philippe, Florence Magnin, Jean-Yves Josnin, Costanza Morino, Nicolas Monzie, and Skafti Brynjólfsson. Modelling the thermal dynamics of perched permafrost talus slopes: insights from a recently destabilised site (gislá landslide, october 6th 2020, iceland). Géomorphologie: relief, processus, environnement, 2025. doi:https://doi-org.ezproxy.uio.no/10.4000/134ad.
  • M. Mazzolini, K. Aalstad, E. Alonso-González, S. Westermann, and D. Treichler. Spatio-temporal snow data assimilation with the icesat-2 laser altimeter. EGUsphere, 2024:1–29, 2024. doi:10.5194/egusphere-2024-1404.
  • Arnaud HJ Jansen. Response of snowmelt rate and streamflow to climate change. Master's thesis, Wageningen University, 2024. URL: https://edepot.wur.nl/673474.
  • Pascal Wyss. Downscaling of future meteorology for land-surface modelling in the glacierised amu darya headwaters. Master's thesis, University of Zurich, January 2024. URL: https://doi.org/10.5167/uzh-264138.

Thanks to those who cited the tool. :)

  1. R. Essery. A factorial snowpack model (fsm 1.0). Geoscientific Model Development, 8(12):3867–3876, 2015. URL: https://gmd.copernicus.org/articles/8/3867/2015/, doi:10.5194/gmd-8-3867-2015. ↩