Aug 2026· Climate Dynamics· Vol 64· 0 citations· 142 references
Abstract
The EURO-CORDEX initiative provides a comprehensive set of regional climate simulations for the present and future European climate. We assess how well snow cover, a crucial component of the climate system, is represented in this model ensemble. We consider output from 11 regional climate models (RCMs) at 12 km resolution, driven by ERA-Interim and 10 different general circulation models, and compare it with model- and remote-sensing-based reference data sets for the periods 1990–2008 and 1985–2008, respectively. Elevation-resolved evaluations for four mountainous regions indicate that for mean winter snow water equivalent (SWE), the reanalysis-driven RCM ensemble mean agrees well with reference data. However, model spread becomes substantial (ca. ± 50%) at the highest elevations of the regions. For the number of snow-covered days (SCD), the agreement of individual models with reference data is generally better. With GCM-forcing, simulated mean winter SWE and SCD biases are typically larger in all regions except for Scandinavia. Part of this bias can likely be attributed to an overestimation of winter precipitation in the RCM runs. The analysis also reveals that some models indicate perennial snow accumulation at much lower elevations than suggested by proxy data. This bias is likely related to inaccuracies in atmospheric forcing (aforementioned precipitation biases) and shortcomings in the representation of snow cover in the RCMs. Overall, and after spatial masking of spurious grid cells, both the reanalysis-driven and the GCM-driven EURO-CORDEX 12 km ensemble are able to represent the main spatio-temporal characteristics of European snow coverage. The future changes in snow cover characteristics will be the subject of a follow-up study.
Abstract. A 21-member ensemble of regional climate simulations has been produced for Southeast Asia (SEA) by dynamically downscaling Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) under the World Climate Research Programme's Coordinated Regional Climate Downscaling Experiment (CORDEX...
P. Nguyen, Lisa V. Alexander, T. Ngo-Duc et al.· Geoscientific Model Developm...· 1 citation
Understanding regional hydroclimatic variability and its drivers is essential to anticipate the impacts of climate change on water resources and sustainability. Yet, considerable uncertainty remains in the simulation of the coupled land–atmosphere water and energy cycles, largely due to structural model limitations,...
J. Roque, F. P. Da Silva Lopes, J. Giles et al.· International Journal of Cli...· 1 citation
This study presents the first application of the Weather Research and Forecasting (WRF) model for regional climate modelling in Hungary, specifically adapted for the Carpathian Basin. Simulations for the historical (1985–2010) and future (2020–2045) periods were conducted using WRF with a 10 km grid spacing, downscalin...
This paper describes an ensemble of global atmosphere reference simulations covering the period 1980 to 2023 produced with the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). The resulting dataset consists of 6-hourly three-dimensional global outputs from higher- and lowe...
M. Aengenheyster, Christopher D. Roberts, Razvan Aguridan et al.· Scientific Data· 1 citation
We present an evaluation and future projections of ten Global Climate Models (GCMs) dynamically downscaled using Rossby Centre Regional Atmospheric model version 4 (RCA4) under the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. Evaluations were done with Climate Research Unit (CRU) time-series...
Qudsia Zafar, Shahbaz Mehmood, M. Adnan et al.· Discover Atmosphere· 0 citations
High-resolution river discharge provides relevant information for evaluating regional climate models and assessing the hydrological impact of climate change. In this study, we generate high-resolution European river discharges by forcing the Hydrological Discharge (HD) model with runoff fields from the ICON-CLM regio...
S. Hagemann, Beate Geyer, Sergei Petrov et al.· Environmental Research: Clim...· 0 citations
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