Evaluation of Radiation and Clouds From Five Reanalysis Products in the Northeast Pacific Ocean

• Published in: Journal of geophysical research. Atmospheres 2018-07, Vol.123 (14), p.7238-7253
• Main Authors: Schmeisser, Lauren, Hinkelman, Laura M., Ackerman, Thomas P.
• Format: Article
• Language: English
• Subjects: atmospheric reanalysis; CERES EBAF; cloud fraction; Clouds; Data; Errors; Estimates; Evaluation; Fluxes; Geophysics; Northeast Pacific; Products; Radiation; Satellites; Short wave radiation; surface radiative fluxes
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1029/2018JD028805

Atmospheric reanalyses are valuable tools for studying the atmosphere, as they provide temporally and spatially complete coverage of atmospheric variables. However, some regions are susceptible to large biases in reanalysis products due to the scarce data available to assimilate into the reanalyses. Consequently, evaluation of reanalyses using available measurements is essential for quantifying regional errors. Here we use NASA's CERES satellite estimates to evaluate surface radiative fluxes and total cloud fraction in the Northeast Pacific from five reanalysis products—ERA‐Interim, MERRA2, JRA‐55, NCEP2, and CFSR—from years 2001 to 2015. Results show that biases of surface incident shortwave radiative flux in reanalyses compared to satellite estimates range from 3.8 (CFSR) to 21.2 Wm‐2 (NCEP2), with significant biases in JRA‐55 and NCEP2. Mean surface downward longwave radiative flux in the reanalysis products is biased by −8.9 (MERRA2) to 3.9 Wm−2 (JRA‐55), with significant biases in MERRA2 and NCEP2. Errors in the surface radiative fluxes are partially linked to differences in total cloud fraction in the satellite estimates and reanalyses, which show significant negative biases ranging from −8% (CFSR) to −21.7% (NCEP2). There is not one reanalysis that outperforms the rest in the NE Pacific. The most appropriate data set depends on the variables of interest, subregion of the NE Pacific being studied, time period of interest, and whether the reanalysis data will be used to study long‐term or short‐term climate processes. Using the errors presented for each reanalysis data set can help guide appropriate use and bound uncertainty for the five reanalysis products analyzed. Key Points An evaluation of radiative fluxes and total cloud fraction from five reanalysis products is performed using CERES EBAF satellite estimates Shortwave radiative flux is mostly overestimated in reanalysis data sets, while longwave radiative flux has both negative and positive biases, depending on the reanalysis There is no gold standard reanalysis—the most appropriate data set depends on variables, time period, and subregion of interest