Articles | Volume 19, issue 8
https://doi.org/10.5194/hess-19-3449-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-3449-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
06 Aug 2015
Research article |
| 06 Aug 2015
The representation of location by a regional climate model in complex terrain
GEOMAR Helmholtz Centre for Ocean Research Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
M. Widmann
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
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39 citations as recorded by crossref.
- A classification algorithm for selective dynamical downscaling of precipitation extremes E. Meredith et al. https://doi.org/10.5194/hess-22-4183-2018
- Process‐based evaluation of the VALUE perfect predictor experiment of statistical downscaling methods P. Soares et al. https://doi.org/10.1002/joc.5911
- Constraining Climate Model Projections of Regional Precipitation Change B. Zhang & B. Soden https://doi.org/10.1029/2019GL083926
- Dynamics of Aboveground Carbon Across Karst Terrestrial Ecosystems in China from 2015 to 2021 J. Shi et al. https://doi.org/10.3390/f15122143
- Cross-validation of bias-corrected climate simulations is misleading D. Maraun & M. Widmann https://doi.org/10.5194/hess-22-4867-2018
- The representation of temperature over Northeast India: assessing the performance of CORDEX‑CORE model experiments R. Ahamed et al. https://doi.org/10.1007/s00704-024-05336-4
- Statistical Postprocessing of Subseasonal Cumulative Precipitation Forecasts Using a Spatial Heterogeneity-aware U-Net S. Liu et al. https://doi.org/10.1016/j.jhydrol.2025.134854
- Multivariate Bias Correction of Climate Model Output: Matching Marginal Distributions and Intervariable Dependence Structure A. Cannon https://doi.org/10.1175/JCLI-D-15-0679.1
- A combined statistical bias correction and stochastic downscaling method for precipitation C. Volosciuk et al. https://doi.org/10.5194/hess-21-1693-2017
- Assessment of climate extremes in future projections downscaled by multiple statistical downscaling methods over Pakistan S. Ali et al. https://doi.org/10.1016/j.atmosres.2019.02.009
- Dynamic downscaling of climate simulations and projected changes in tropical South America using RegCM4.7 M. da Silva et al. https://doi.org/10.1002/joc.8035
- A Robust Method to Update Local River Inundation Maps Using Global Climate Model Output and Weather Typing Based Statistical Downscaling M. Bermúdez et al. https://doi.org/10.1007/s11269-020-02673-7
- A severe landslide event in the Alpine foreland under possible future climate and land-use changes D. Maraun et al. https://doi.org/10.1038/s43247-022-00408-7
- Evaluation of the performance of Euro-CORDEX Regional Climate Models for assessing hydrological climate change impacts in Great Britain: A comparison of different spatial resolutions and quantile mapping bias correction methods E. Pastén-Zapata et al. https://doi.org/10.1016/j.jhydrol.2020.124653
- Frontiers in attributing climate extremes and associated impacts S. Perkins-Kirkpatrick et al. https://doi.org/10.3389/fclim.2024.1455023
- Bias correction of precipitation through Singularity Stochastic Removal: Because occurrences matter M. Vrac et al. https://doi.org/10.1002/2015JD024511
- Climate change increases the number of landslides at the juncture of the Alpine, Pannonian and Mediterranean regions M. Jemec Auflič et al. https://doi.org/10.1038/s41598-023-50314-x
- Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies E. Maurer et al. https://doi.org/10.5194/hess-20-685-2016
- High-resolution climate datasets in hydrological impact studies: Assessing their value in alpine and pre-alpine catchments in southeastern Austria S. Peßenteiner et al. https://doi.org/10.1016/j.ejrh.2021.100962
- Monthly streamflow forecasting at varying spatial scales in the Rhine basin S. Schick et al. https://doi.org/10.5194/hess-22-929-2018
- Subhourly rainfall in a convection-permitting model E. Meredith et al. https://doi.org/10.1088/1748-9326/ab6787
- Climate change perceptions, data, and adaptation in the Garhwal Himalayas of India R. Platt et al. https://doi.org/10.1080/17565529.2020.1724069
- Bias Correcting Climate Change Simulations - a Critical Review D. Maraun https://doi.org/10.1007/s40641-016-0050-x
- Investigating the performance of high-resolution subseasonal precipitation forecasts in support of food insecurity early warning W. Turner et al. https://doi.org/10.1088/2752-5295/adcadf
- A new bias-correction method for precipitation over complex terrain suitable for different climate states: a case study using WRF (version 3.8.1) P. Velasquez et al. https://doi.org/10.5194/gmd-13-5007-2020
- Multiple bias-correction of dynamically downscaled CMIP5 climate models temperature projection: a case study of the transboundary Komadugu-Yobe river basin, Lake Chad region, West Africa O. Adeyeri et al. https://doi.org/10.1007/s42452-020-3009-4
- Evaluation of the performance of global rainfall products in the Fiji Islands A. Pratap et al. https://doi.org/10.1007/s00704-026-06197-9
- Pattern-based downscaling of snowpack variability in the western United States N. Gauthier et al. https://doi.org/10.1007/s00382-021-06094-z
- Spatial Interpolation of Daily Precipitation in a High Mountainous Watershed Based on Gauge Observations and a Regional Climate Model Simulation Y. Wang et al. https://doi.org/10.1175/JHM-D-16-0089.1
- Bias correction and downscaling of future RCM precipitation projections using a MOS‐Analog technique M. Turco et al. https://doi.org/10.1002/2016JD025724
- Temporal evolution of flow-like landslide hazard for a road infrastructure in the municipality of Nocera Inferiore (southern Italy) under the effect of climate change M. Uzielli et al. https://doi.org/10.5194/nhess-18-3019-2018
- Mitigating crop modeling uncertainties through machine learning in drylands M. Nouri & S. Veysi https://doi.org/10.1038/s41598-025-26811-6
- RoCliB– bias‐corrected CORDEX RCMdataset over Romania A. Dumitrescu et al. https://doi.org/10.1002/gdj3.161
- Identifying robust bias adjustment methods for European extreme precipitation in a multi-model pseudo-reality setting T. Schmith et al. https://doi.org/10.5194/hess-25-273-2021
- Towards process-informed bias correction of climate change simulations D. Maraun et al. https://doi.org/10.1038/nclimate3418
- Validation of a 9-km WRF dynamical downscaling of temperature and precipitation for the period 1980–2005 over Central South Chile A. Fernández et al. https://doi.org/10.1007/s00704-020-03416-9
- Climate change amplified the 2009 extreme landslide event in Austria A. Mishra et al. https://doi.org/10.1007/s10584-023-03593-2
- Evaluating the added value of the new Swiss climate scenarios for hydrology: An example from the Thur catchment O. Rössler et al. https://doi.org/10.1016/j.cliser.2019.01.001
- A new efficiency metric for the spatial evaluation and inter-comparison of climate and geoscientific model output A. Karpasitis et al. https://doi.org/10.5194/gmd-19-345-2026
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