Evaluation and Intercomparison of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic Using BSRN Surface Observations

Abstract

With continual advancements in data assimilation systems, new observing systems, and improvements in model parameterizations, several new atmospheric reanalysis datasets have recently become available. Before using these new reanalyses it is important to assess the strengths and underlying biases contained in each dataset. A study has been performed to evaluate and compare cloud fractions (CFs) and surface radiative fluxes in several of these latest reanalyses over the Arctic using 15 years (1994–2008) of high-quality Baseline Surface Radiation Network (BSRN) observations from Barrow (BAR) and Ny-Alesund (NYA) surface stations. The five reanalyses being evaluated in this study are (i) NASA's Modern-Era Retrospective analysis for Research and Applications (MERRA), (ii) NCEP's Climate Forecast System Reanalysis (CFSR), (iii) NOAA's Twentieth Century Reanalysis Project (20CR), (iv) ECMWF's Interim Reanalysis (ERA-I), and (v) NCEP–Department of Energy (DOE)'s Reanalysis II (R2). All of the reanalyses show considerable bias in reanalyzed CF during the year, especially in winter. The large CF biases have been reflected in the surface radiation fields, as monthly biases in shortwave (SW) and longwave (LW) fluxes are more than 90 (June) and 60 W m−2 (March), respectively, in some reanalyses. ERA-I and CFSR performed the best in reanalyzing surface downwelling fluxes with annual mean biases less than 4.7 (SW) and 3.4 W m−2 (LW) over both Arctic sites. Even when producing the observed CF, radiation flux errors were found to exist in the reanalyses suggesting that they may not always be dependent on CF errors but rather on variations of more complex cloud properties, water vapor content, or aerosol loading within the reanalyses.

Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic*

“…The anomaly correlation, for which the monthly interannual mean of each station and each model is first removed, of all of the models is poor in the summer when the cloud fraction is high and there is little variability. The bias in the shortwave radiation is severe for the NCEP-R1 and NCEP-R2 products, rising to almost 100 W m 22 too high, as noted by other researchers (Zib et al 2012). Cullather and Bosilovich (2012) compared the MERRA downwelling shortwave flux to observations and report a negative bias of 12 W m 22 for the year, consistent with the comparisons shown here.…”

“…In a comparison of the seasonal climatology for clouds of eight different reanalyses to different satellite and surface observations, Chernokulsky and Mokhov (2012) report that NCEP-R1, NCEP-R2, and JRA-25 have less total cloud fraction (TCF) than observations during the whole year; other reanalyses are in close agreement with observations during summer and have noticeably higher TCF values than observations during winter. Zib et al (2012) evaluate cloud fraction and radiative fluxes compared to surface observations for five models and also find strong biases. Serreze et al (2012) report that the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA), Climate Forecast System Reanalysis (CFSR), and ERA-Interim have positive cold season humidity and temperature biases below 850 hPa based on comparisons with radiosonde data; these reanalyses also do not capture well the observed low-level humidity and temperature inversions.…”

Evaluation of the Reanalysis Surface Incident Shortwave Radiation Products from NCEP, ECMWF, GSFC, and JMA Using Satellite and Surface Observations

“…Solar transmission is determined primarily by clouds and aerosols (which were not available for comparison in this study). Previous studies have reported that the discrepancies in the reanalysis CF products might be reflected in the surface radiation fields [59,60]. In this study, the CERES CF climatologies for DJF and JJA, and the biases between the reanalyzed CF and the CERES CF (reanalysis minus CERES) from 2001 to 2009 were also examined in this study, as shown in Figures 6 and 7.…”

Investigating the local-scale influence of sea ice on Greenland surface melt

“…MERRA is run on a 1/2 • latitude by 2/3 • longitude global grid with 72 hybrid-sigma vertical levels to produce analyses from 1979 to present. MERRA has been evaluated extensively since its release (Cullather and Bosilovich, 2011b;Kennedy et al, 2011; and has compared favorably with other reanalysis products in the Arctic (Zib et al, 2012;Cullather and Bosilovich, 2011;Lindsay et al, 2014).…”