Evaluation of daily precipitation analyses in E‐OBS (v19.0e) and ERA5 by comparison to regional high‐resolution datasets in European regions

• Published in: International Journal of Climatology
• Main Authors: Bandhauer, Moritz, Isotta, Francesco, Lakatos, Mónika, Lussana, Cristian, Båserud, Line, Izsák, Beatrix, Szentes, Olivér, Tveito, Ole Einar, Frei, Christoph
• Other Authors: European Commission
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2021
• Subjects: Fennoscandia
• Online Access: http://dx.doi.org/10.1002/joc.7269; https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.7269; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.7269; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.7269

Abstract Gridded analyses of observed precipitation are an important data resource for environmental modelling, climate model evaluation and climate monitoring. In Europe, datasets that resolve the rich mesoscale variations widely exist for the national territories, but similar datasets covering the entire continent are more recent. Here, we evaluate daily precipitation in two newly available pan‐European datasets: E‐OBS (v19.0e), a statistical analysis from rain‐gauge data, and ERA5, the new global reanalysis from ECMWF. Special interest is on how the refinements of grid spacing, the methodological upgrades and the quantification of uncertainty (ensemble), bear on capabilities at the mesoscale. The evaluation is conducted in three subregions, the Alps, the Carpathians and Fennoscandia, and involves as reference high‐quality regional datasets derived from dense rain‐gauge data. The study suggests that E‐OBS and ERA5 agree qualitatively well with the reference datasets. Major mesoscale patterns in the climatology (mean, wet‐day frequency, 95% quantile) are reproduced. The improvement over earlier versions of the datasets is evident. ERA5 was found to overestimate mean precipitation in all regions, related to too many wet days. The accuracy of E‐OBS was found to depend on station density, with spatial and temporal variations clearly less accurate in data sparse regions. In comparison, E‐OBS turned out to be superior to ERA5 in regions with dense data, but the two datasets are on a par in regions with sparse data, and partly ERA5 has advantages. For both datasets we find that the spatial resolution is coarser than the grid spacing, with overly smooth fields and an underestimation of high quantiles. Also, both datasets were found to be clearly overconfident in their uncertainty characterization (too small ensemble spread). Overall, the two datasets advance the characterization of precipitation on a pan‐European scale, but users are advised to take residual limitations into account in applications.