Comparison of different global information sources used in surface radiative flux calculation: Radiative properties of the surface

Abstract

Direct estimates of surface radiative fluxes that resolve regional and weather‐scale variability over the whole globe with reasonable accuracy have only become possible with the advent of extensive global, mostly satellite, data sets within the past couple of decades. The accuracy of these fluxes, estimated to be about 10–15 W/m2, is largely limited by the accuracy of the input data sets. The leading uncertainties in the surface fluxes are no longer predominantly induced by clouds but are now as much associated with uncertainties in the surface and near‐surface atmospheric properties. This study presents a fuller, more quantitative evaluation of the uncertainties for the surface albedo and emissivity and surface skin temperatures by comparing the main available global data sets from the Moderate‐Resolution Imaging Spectroradiometer product, the NASA Global Energy and Water Cycle Experiment Surface Radiation Budget project, the European Centre for Medium‐Range Weather Forecasts, the National Aeronautics and Space Administration, the National Centers for Environmental Prediction, the International Satellite Cloud Climatology Project (ISCCP), the Laboratoire de Météorologie Dynamique, NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer project, and the NOAA Optimum Interpolation Sea Surface Temperature Analysis and the Tropical Rainfall Measuring Mission (TRMM) Microwave Image project. The data sets are, in practice, treated as an ensemble of realizations of the actual climate such that their differences represent an estimate of the uncertainty in their measurements because we do not possess global “truth” data sets for these quantities. The results are globally representative and may be taken as a generalization of our previous ISCCP‐based uncertainty estimates for the input data sets. Surface properties have the primary role in determining the surface upward shortwave (SW) and longwave (LW) flux.From this study the following conclusions are obtained. Although land surface albedos in the near‐infrared remain poorly constrained (highly uncertain), they do not cause too much error in total surface SW fluxes; the more subtle regional and seasonal variations associated with vegetation and snow are still in doubt. The uncertainty of the broadband black‐sky SW albedo for land surface from this study is about 7%, which can easily induce 5–10 W/m2 uncertainty in (upwelling) surface SW flux estimates. Even though available surface (broadband) LW emissivity data sets differ significantly (3–5% uncertainty), this disagreement is confined to wavelengths >20 μm so that there is little practical effect (1–3 W/m2) on the surface upwelling LW fluxes. The surface skin temperature is one of two leading factors that cause problems with surface LW fluxes. Even though the differences among the various data sets are generally only 2–4 K, this can easily cause 10–15 W/m2 uncertainty in calculated surface (upwelling) LW fluxes. Significant improvements could be obtained for surface LW flux calculations by improving the retrievals of (in order of decreasing importance): (1) surface skin temperature, (2) surface air and near‐surface‐layer temperature, (3) column precipitable water amount, and (4) broadband emissivity. In addition, for surface SW fluxes, improvements could be obtained (excluding improved cloud treatment) by improving the retrievals of (1) aerosols (from our sensitivity studies but not discussed in this work) and (2) surface (black‐sky) albedo, of which the NIR part of the spectrum has much larger uncertainty.