The data assimilation system and initial performance evaluation of the ECMWF pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C)

TitleThe data assimilation system and initial performance evaluation of the ECMWF pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C)
Publication TypeReport
Date Published09/2013
Series/CollectionERA Report Series
Document Number14
Pagination59
AuthorsPoli, P, Hersbach, H, Tan, DGH, Dee, DP, Thépaut, J-N, Simmons, A, Peubey, C, Laloyaux, P, Komori, T, Berrisford, P, Dragani, R, Trémolet, Y, Hólm, EV, Bonavita, M, Isaksen, L, Fisher, M
Event Series/CollectionERA Report
InstitutionECMWF
Place of publicationShinfield Park, Reading
Abstract

Within the ERA-CLIM project, ECMWF is producing a pilot reanalysis of the 20th-century assimilating surface observations only (ERA-20C). This pilot reanalysis complements a model-only integration (ERA-20CM) and a land-surface reanalysis (ERA-20CL). The prime target of ERA-20C is the study of the feasibility of reanalysing the century using new data assimilation methods to tackle the problem of observing system changes, assimilating here only surface observations. The data assimilation system in ERA-20C is an Ensemble of Data Assimilations (EDA) of 10 members. They are forced by HadISST2.1.0.0 ensemble of sea-surface temperature and sea-ice conditions. Each ERA-20C member employs a 24-hour four-dimensional variational (4D-Var) analysis scheme. The ISPD 3.2.6 and ICOADS 2.5.1 databases provide input observations of surface pressures (assimilated with a variational bias correction) and, over oceans, surface winds. The global background error covariances employed by the 4D-Var are updated automatically every 10 days, using a 90-day sample drawn from the ensemble. The local background errors in vorticity are modulated daily, by the ensemble spread. Over time, the background error horizontal correlations become more narrow and the background error variances become smaller. This fits with expectations that a loose observing network can only help make large-scale adjustments to an analysis, while a more dense observing network can help capture smaller-scale errors. However, we find that mean temperature analysis increments vary in strength over time with height. This introduces unwanted spurious trends in upper-air temperatures. From the present initial assessment, the long-term climate trends in ERA-20C are incorrect in most places. However, there are indications that meteorological events, including extremes, are well represented on a daily basis. The report concludes with a list of major issues to be addressed in an upcoming rerun of the ERA-20C control experiment.

URLhttps://www.ecmwf.int/node/11699
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