Uncertainty in Satellite-Derived Surface Irradiances and Challenges in Producing Surface Radiation Budget Climate Data Record

• Main Authors: Seiji Kato, David A. Rutan, Fred G. Rose, Thomas E. Caldwell, Seung-Hee Ham, Alexander Radkevich, Tyler J. Thorsen, Antonio Viudez-Mora, David Fillmore, Xianglei Huang
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Remote Sensing
• Subjects: surface radiation budget; regional monthly mean; variability
• Online Access: https://www.mdpi.com/2072-4292/12/12/1950

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.1 data product provides global surface irradiances. Uncertainties in the global and regional monthly and annual mean all-sky net shortwave, longwave, and shortwave plus longwave (total) irradiances are estimated using ground-based observations. Error covariance is derived from surface irradiance sensitivity to surface, atmospheric, cloud and aerosol property perturbations. Uncertainties in global annual mean net shortwave, longwave, and total irradiances at the surface are, respectively, 5.7 Wm⁻², 6.7 Wm⁻², and 9.7 Wm⁻². In addition, the uncertainty in surface downward irradiance monthly anomalies and their trends are estimated based on the difference derived from EBAF surface irradiances and observations. The uncertainty in the decadal trend suggests that when differences of decadal global mean downward shortwave and longwave irradiances are, respectively, greater than 0.45 Wm⁻² and 0.52 Wm⁻², the difference is larger than 1σ uncertainties. However, surface irradiance observation sites are located predominately over tropical oceans and the northern hemisphere mid-latitude. As a consequence, the effect of a discontinuity introduced by using multiple geostationary satellites in deriving cloud properties is likely to be excluded from these trend and decadal change uncertainty estimates. Nevertheless, the monthly anomaly timeseries of radiative cooling in the atmosphere (multiplied by −1) agrees reasonably well with the anomaly time series of diabatic heating derived from global mean precipitation and sensible heat flux with a correlation coefficient of 0.46.