Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1753-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-1753-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
02 Mar 2022
Model description paper |
| 02 Mar 2022
| 02 Mar 2022
TopoCLIM: rapid topography-based downscaling of regional climate model output in complex terrain v1.1
Joel Fiddes
CORRESPONDING AUTHOR
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Kristoffer Aalstad
Department of Geosciences, University of Oslo, P.O. Box 1047, Blindern, 0316 Oslo, Norway
Michael Lehning
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
CRYOS, School of Architecture, Civil and Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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- A review of future weather data for assessing climate change impacts on buildings and energy systems Z. Zeng et al. https://doi.org/10.1016/j.rser.2024.115213
- Complex climatic, CO2, and grazing controls on the net primary productivity and carbon stocks in grasslands of the Tibetan Plateau L. Zheng et al. https://doi.org/10.1016/j.catena.2025.109376
- TopoPyScale: A Python Package for Hillslope Climate Downscaling S. Filhol et al. https://doi.org/10.21105/joss.05059
- Evaluation of the Accuracy and Applicability of Reanalysis Precipitation Products in the Lower Yarlung Zangbo Basin A. Tan et al. https://doi.org/10.3390/rs17142396
- Simulating the effect of subsurface drainage on the thermal regime and ground ice in blocky terrain in Norway C. Renette et al. https://doi.org/10.5194/esurf-11-33-2023
- CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment F. Zabel et al. https://doi.org/10.5194/gmd-18-1067-2025
- Hourly potential light availability maps at 10 m resolution over Switzerland C. Webster et al. https://doi.org/10.1038/s41597-025-06152-9
- Spatio-temporal snow data assimilation with the ICESat-2 laser altimeter M. Mazzolini et al. https://doi.org/10.5194/tc-19-3831-2025
- Flood hazard assessment using design rainfall under climate change scenarios in the Kelantan River Basin, Malaysia T. Tam et al. https://doi.org/10.1108/IJDRBE-05-2022-0048
- MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al. https://doi.org/10.5194/gmd-15-6165-2022
- Framework for generating high-resolution Hong Kong local climate projections to support building energy simulations J. Wang et al. https://doi.org/10.1063/5.0254669
- The Multiple Snow Data Assimilation System (MuSA v1.0) E. Alonso-González et al. https://doi.org/10.5194/gmd-15-9127-2022
- A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks M. Guidicelli et al. https://doi.org/10.1016/j.hydroa.2024.100190
- Modelling the temporal dynamics of subarctic surface temperature inversions from atmospheric reanalysis for producing point-scale multi-decade meteorological time series in mountains V. Pozsgay & S. Gruber https://doi.org/10.1139/as-2025-0027
Saved (final revised paper)
Latest update: 27 Jun 2026
Short summary
This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
This study describes and evaluates a new downscaling scheme that addresses the need for...
