Articles | Volume 15, issue 15
https://doi.org/10.5194/gmd-15-6165-2022
© 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-15-6165-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
05 Aug 2022
Methods for assessment of models |
| 05 Aug 2022
| 05 Aug 2022
MIdASv0.2.1 – MultI-scale bias AdjuStment
Hydrology Research Unit, Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 601 76 Norrköping, Sweden
Thomas Bosshard
Hydrology Research Unit, Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 601 76 Norrköping, Sweden
Hydrology Research Unit, Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 601 76 Norrköping, Sweden
Klaus Zimmermann
Hydrology Research Unit, Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 601 76 Norrköping, Sweden
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- Building on quicksand: the paradox of AI advances and declining in situ networks in hydrometeorology J. Olsson et al. https://doi.org/10.1038/s44304-026-00237-0
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- Toward more efficiency of some MERRA-2 reanalysis products in the central Algerian steppe: Zahrez watershed case K. Fatima et al. https://doi.org/10.1007/s41207-025-00770-w
- Intercomparison of bias correction methods for precipitation of multiple GCMs across six continents Y. Song & E. Chung https://doi.org/10.5194/gmd-18-8017-2025
- Late spring frost may hinder Scandinavian farmers from making advantage of the longer vegetation period G. Strandberg et al. https://doi.org/10.1038/s44458-026-00141-8
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- Short-term forecasts and long-term regional scenarios of climate change effects on Swedish forest phenology O. Langvall & G. Strandberg https://doi.org/10.1007/s00484-026-03259-5
17 citations as recorded by crossref.
- Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations E. Holmgren & E. Kjellström https://doi.org/10.5194/nhess-24-2875-2024
- Modeling water demand for crop irrigation in Sweden under climate change H. Rudebeck et al. https://doi.org/10.1016/j.ejrh.2026.103288
- Probabilistic analysis of the impact of climate change on local scour under bridge piers: A case study in southern Sweden A. Nasr & T. Mohamed https://doi.org/10.1016/j.ress.2026.113351
- Robust handling of extremes in quantile mapping – “Murder your darlings” P. Berg et al. https://doi.org/10.5194/gmd-17-8173-2024
- Building on quicksand: the paradox of AI advances and declining in situ networks in hydrometeorology J. Olsson et al. https://doi.org/10.1038/s44304-026-00237-0
- An interdisciplinary model chain quantifies the footprint of global change on reservoir sedimentation K. Mouris et al. https://doi.org/10.1038/s41598-023-47501-1
- Projected climate change in Fennoscandia – and its relation to ensemble spread and global trends G. Strandberg et al. https://doi.org/10.5194/wcd-7-185-2026
- Plant pathogen infection risk and climate change in the Nordic and Baltic countries G. Strandberg et al. https://doi.org/10.1088/2515-7620/ad352a
- Implications of a Paris-proof scenario for future supply of weather-dependent variable renewable energy in Europe J. Hu et al. https://doi.org/10.1016/j.adapen.2023.100134
- Toward more efficiency of some MERRA-2 reanalysis products in the central Algerian steppe: Zahrez watershed case K. Fatima et al. https://doi.org/10.1007/s41207-025-00770-w
- Intercomparison of bias correction methods for precipitation of multiple GCMs across six continents Y. Song & E. Chung https://doi.org/10.5194/gmd-18-8017-2025
- Late spring frost may hinder Scandinavian farmers from making advantage of the longer vegetation period G. Strandberg et al. https://doi.org/10.1038/s44458-026-00141-8
- Development of localized climate projections for Vietnam’s Mekong Delta using univariate and multivariate bias corrections of CMIP6 simulations D. Dong Phuong et al. https://doi.org/10.1007/s00382-026-08347-1
- ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1) F. Spuler et al. https://doi.org/10.5194/gmd-17-1249-2024
- Navigating towards strengthened climate service processes L. Wiréhn & G. Strandberg https://doi.org/10.1007/s13280-025-02136-6
- From global glacier modeling to catchment hydrology: bridging the gap with the WaSiM-OGGM coupling scheme M. Pesci et al. https://doi.org/10.3389/frwa.2023.1296344
- Short-term forecasts and long-term regional scenarios of climate change effects on Swedish forest phenology O. Langvall & G. Strandberg https://doi.org/10.1007/s00484-026-03259-5
Saved (final revised paper)
Latest update: 14 Sep 2026
Short summary
When performing impact analyses with climate models, one is often confronted with the issue that the models have significant bias. Commonly, the modelled climatological temperature deviates from the observed climate by a few degrees or it rains excessively in the model. MIdAS employs a novel statistical model to translate the model climatology toward that observed using novel methodologies and modern tools. The coding platform allows opportunities to develop methods for high-resolution models.
When performing impact analyses with climate models, one is often confronted with the issue that...
