Evaluating E-OBS, AgERA5, MARS-STAT, ERA5, and ERA5-Land for Daily Minimum and Maximum Temperature Across Four Mediterranean European Countries

Abstract

Gridded-dataset suitability varies by support, season, variable, and application. This study evaluated E-OBS, AgERA5, MARS-STAT/JRC Agri4Cast, ERA5, and ERA5-Land against observations from 624 European Climate Assessment & Dataset (ECA&D) and Hellenic National Meteorological Service (HNMS/EMY) stations, using 18.18 million source-station-day records containing minimum (TN) and maximum (TX) temperatures. Derived variables included mean temperature (Tmean), diurnal temperature range (DTR), and growing degree days (GDD). Identical-support rankings and station bootstraps assessed daily and GDD performance; Fisher's z transformation summarized seasonal correlations; temporal and network tests screened trends. E-OBS minimized daily and monthly-climatology-removed anomaly root mean square error (RMSE) for TN, TX, Tmean, and DTR in all 16 country-variable comparisons. With at least 10 matched years, E-OBS led 42 of 64 seasonal RMSE comparisons and 59 of 64 correlation comparisons; MARS-STAT/JRC Agri4Cast led the remaining 22 and five, respectively. E-OBS minimized GDD RMSE in Spain and Italy, whereas MARS-STAT/JRC Agri4Cast led in Greece and narrowly led in France. GDD RMSE equaled 3.3-7.2% of observed mean GDD. Robustness tests supported increases in Spanish annual DTR, French annual TX, and French growing-season GDD. The lapse-rate correction improved 22 of 40 comparisons but usually worsened TN. Dataset choice should reflect support, variable, season, terrain, and application.