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.
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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16 citations as recorded by crossref.
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16 citations as recorded by crossref.
- Investigation of Uncertainties in Multi-variable Bias Adjustment in Multi-model Ensemble S. Kelkar & K. Dairaku 10.5194/piahs-386-55-2024
- Observed and predicted trends in Icelandic snow conditions for the period 1930–2100 D. Eythorsson et al. 10.5194/tc-17-51-2023
- The CryoGrid community model (version 1.0) – a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere S. Westermann et al. 10.5194/gmd-16-2607-2023
- Climate projections of human thermal comfort for indoor workplaces M. Sulzer & A. Christen 10.1007/s10584-024-03685-7
- HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor C. Steger et al. 10.5194/gmd-15-6817-2022
- Retrieving snow depth distribution by downscaling ERA5 Reanalysis with ICESat-2 laser altimetry Z. Liu et al. 10.1016/j.coldregions.2025.104580
- A review of future weather data for assessing climate change impacts on buildings and energy systems Z. Zeng et al. 10.1016/j.rser.2024.115213
- TopoPyScale: A Python Package for Hillslope Climate Downscaling S. Filhol et al. 10.21105/joss.05059
- Evaluation of the Accuracy and Applicability of Reanalysis Precipitation Products in the Lower Yarlung Zangbo Basin A. Tan et al. 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. 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. 10.5194/gmd-18-1067-2025
- Flood hazard assessment using design rainfall under climate change scenarios in the Kelantan River Basin, Malaysia T. Tam et al. 10.1108/IJDRBE-05-2022-0048
- MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al. 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. 10.1063/5.0254669
- The Multiple Snow Data Assimilation System (MuSA v1.0) E. Alonso-González et al. 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. 10.1016/j.hydroa.2024.100190
Latest update: 12 Jul 2025
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...