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Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5
Stockholm Univ, Dept Phys Geog, Bolin Ctr Climate Res, Stockholm, Sweden..
Univ Oulu, Fac Technol, Water Energy & Environm Engn Res Unit, Oulu, Finland..
Univ Stuttgart, Inst Geodesy GIS, Stuttgart, Germany..
Univ Arizona, Dept Hydrol & Atmospher Sci, Tucson, AZ USA..
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2022 (engelsk)Inngår i: Earth and Space Science, E-ISSN 2333-5084, Vol. 9, nr 10, artikkel-id e2022EA002352Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

European Center for Medium-Range Weather Forecasts Reanalysis (ERA), one of the most widely used precipitation products, has evolved from ERA-40 to ERA-20CM, ERA-20C, ERA-Interim, and ERA5. Studies evaluating the performance of individual ERA products cannot adequately assess the evolution of the products. We compared the performance of all ERA precipitation products at daily, monthly, and annual data (1980-2018) using more than 2100 Iran precipitation gauges. Results indicated that ERA-40 performed worst, followed by ERA-20CM, which showed only minor improvements over ERA-40. ERA-20C considerably outperformed its predecessors, benefiting from the assimilation of observational data. Although several previous studies have reported full superiority of ERA5 over ERA-Interim, our results revealed several shortcomings in ERA5 compared with the ERA-Interim estimates. Both ERA-Interim and ERA5 performed best overall, with ERA-Interim showing better statistical and categorical skill scores, and ERA5 performing better in estimating extreme precipitations. These results suggest that the accuracy of ERA precipitation products has improved from ERA-40 to ERA-Interim, but not consistently from ERA-Interim to ERA5. This study employed a grid-grid comparison approach by first creating a gridded reference data set through the spatial aggregation of point source observations, however, the results from a point-grid approach showed no change in the overall ranking of products (despite the slight changes in the error index values). These findings are useful for model development at a global scale and for hydrological applications in Iran.

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American Geophysical Union (AGU) , 2022. Vol. 9, nr 10, artikkel-id e2022EA002352
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URN: urn:nbn:se:kth:diva-320480DOI: 10.1029/2022EA002352ISI: 000864684100001Scopus ID: 2-s2.0-85141661949OAI: oai:DiVA.org:kth-320480DiVA, id: diva2:1706365
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QC 20221026

Tilgjengelig fra: 2022-10-26 Laget: 2022-10-26 Sist oppdatert: 2023-01-23bibliografisk kontrollert

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