{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T13:13:24Z","timestamp":1773926004890,"version":"3.50.1"},"reference-count":82,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T00:00:00Z","timestamp":1562630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Skills in reproducing monthly rainfall over Calabria (southern Italy) have been validated for the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) satellite data, the E-OBS dataset and 13 Global Climate Model-Regional Climate Model (GCM-RCM) combinations, belonging to the ENSEMBLES project output set. To this aim, 73 rainfall series for the period 1951\u20131980 and 79 series for the period 1981\u20132010 have been selected from the database managed by Multi-Risk Functional Centre of the Regional Agency for Environmental Protection (Regione Calabria). The relative mean and standard deviation errors, and the Pearson correlation coefficient have been used as validation metrics. Results showed that CHIRPS satellite data (available only for the 1981\u20132010 validation period) and RCMs based on the ECHAM5 Global Climate performed better both in mean error and standard deviation error compared to other datasets. Moreover, a slight appreciable improvement in performance for all ECHAM5-based models and for the E-OBS dataset has been observed in the 1981\u20132010 time-period. The whole validation-and-assessment procedure applied in this work is general and easily applicable where ground data and gridded data are available. This procedure might help scientists and policy makers to select among available datasets those best suited for further applications, even in regions with complex orography and an inadequate amount of representative stations.<\/jats:p>","DOI":"10.3390\/rs11131625","type":"journal-article","created":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T03:05:26Z","timestamp":1562727926000},"page":"1625","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Validation of Satellite, Reanalysis and RCM Data of Monthly Rainfall in Calabria (Southern Italy)"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7827-7411","authenticated-orcid":false,"given":"Giulio Nils","family":"Caroletti","sequence":"first","affiliation":[{"name":"National Research Council\u2014Research Institute for Geo-Hydrological Protection (CNR-IRPI), 87036 Rende, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2779-1100","authenticated-orcid":false,"given":"Roberto","family":"Coscarelli","sequence":"additional","affiliation":[{"name":"National Research Council\u2014Research Institute for Geo-Hydrological Protection (CNR-IRPI), 87036 Rende, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0393-4592","authenticated-orcid":false,"given":"Tommaso","family":"Caloiero","sequence":"additional","affiliation":[{"name":"National Research Council\u2014Institute for Agricultural and Forest Systems in Mediterranean (CNR-ISAFOM), 87036 Rende, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,9]]},"reference":[{"key":"ref_1","unstructured":"Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.M. 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