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An Ensemble Mean and Evaluation of Third Generation Global Climate Reanalysis Models

Climate Change Institute and School of Earth and Climate Sciences, University of Maine, Orono, ME 04473, USA
Department of Earth and Atmospheric Sciences, Metropolitan State University of Denver, Denver, CO 80204, USA
Author to whom correspondence should be addressed.
Atmosphere 2018, 9(6), 236;
Received: 9 February 2018 / Revised: 14 June 2018 / Accepted: 16 June 2018 / Published: 19 June 2018
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
We have produced a global ensemble mean of the four third-generation climate reanalysis models for the years 1981–2010. The reanalysis system models used in this study are National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis Interim (ERA-I), Japan Meteorological Agency (JMA) 55-year Reanalysis (JRA-55), and National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA). Two gridded datasets are used as a baseline, for temperature the Global Historical Climatology Network (GHCN), and for precipitation the Global Precipitation Climatology Centre (GPCC). The reanalysis ensemble mean is used here as a comparison tool of the four reanalysis members. Meteorological fields investigated within the reanalysis models include 2-m air temperature, precipitation, and 500-hPa geopotential heights. Comparing the individual reanalysis models to the ensemble mean, we find that each perform similarly over large domains but exhibit significant differences over particular regions. View Full-Text
Keywords: reanalysis models; temperature; precipitation; geopotential height reanalysis models; temperature; precipitation; geopotential height
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Auger, J.D.; Birkel, S.D.; Maasch, K.A.; Mayewski, P.A.; Schuenemann, K.C. An Ensemble Mean and Evaluation of Third Generation Global Climate Reanalysis Models. Atmosphere 2018, 9, 236.

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