Verification of the EURO-CORDEX RCM Historical Run Results over the Pannonian Basin for the Summer Season
| Autor: | Milica Tošić, Vladimir Djurdjevic, Irida Lazić |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Atmospheric Science
Spatial correlation 010504 meteorology & atmospheric sciences Mean squared error Pannonian basin 0207 environmental engineering 02 engineering and technology Environmental Science (miscellaneous) precipitation 01 natural sciences Standard deviation summer drying problem Meteorology. Climatology Pannonian Basin regional climate model evaluation Precipitation 020701 environmental engineering 0105 earth and related environmental sciences temperature Summer season 13. Climate action Climatology Environmental science Climate model EURO-CORDEX QC851-999 Downscaling E-OBS |
| Zdroj: | Atmosphere Volume 12 Issue 6 Atmosphere, Vol 12, Iss 714, p 714 (2021) |
| ISSN: | 2073-4433 |
| DOI: | 10.3390/atmos12060714 |
| Popis: | In previous projects that focused on dynamical downscaling over Europe, e.g., PRUDENCE and ENSEMBLES, many regional climate models (RCMs) tended to overestimate summer air temperature and underestimate precipitation in this season in Southern and Southeastern Europe, leading to the so-called summer drying problem. This bias pattern occurred not only in the RCM results but also in the global climate model (GCM) results, so knowledge of the model uncertainties and their cascade is crucial for understanding and interpreting future climate. Our intention with this study was to examine whether a warm-and-dry bias is also present in the state-of-the-art EURO-CORDEX multi-model ensemble results in the summer season over the Pannonian Basin. Verification of EURO-CORDEX RCMs was carried out by using the E-OBS gridded dataset of daily mean, minimum, and maximum near-surface air temperature and total precipitation amount with a horizontal resolution of 0.1 degrees (approximately 12 km × 12 km) over the 1971–2000 time period. The model skill for selected period was expressed in terms of four verification scores: bias, centered root mean square error (RMSE), spatial correlation coefficient, and standard deviation. The main findings led us to conclude that most of the RCMs that overestimate temperature also underestimate precipitation. For some models, the positive temperature and negative precipitation bias were more emphasized, which led us to conclude that the problem was still present in most of the analyzed simulations. |
| Databáze: | OpenAIRE |
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