Abstract
Mapping surface all-wave net radiation (Rn) is critically needed for various applications. Several existing Rn products from numerical models and satellite observations have coarse spatial resolutions and their accuracies may not meet the requirements of land applications. In this study, we develop the Global LAnd Surface Satellite (GLASS) daytime Rn product at a 5 km spatial resolution. Its algorithm for converting shortwave radiation to all-wave net radiation using the Multivariate Adaptive Regression Splines (MARS) model is determined after comparison with three other algorithms. The validation of the GLASS Rn product based on high-quality in situ measurements in the United States shows a coefficient of determination value of 0.879, an average root mean square error value of 31.61 Wm−2, and an average bias of −17.59 Wm−2. We also compare our product/algorithm with another satellite product (CERES-SYN) and two reanalysis products (MERRA and JRA55), and find that the accuracy of the much higher spatial resolution GLASS Rn product is satisfactory. The GLASS Rn product from 2000 to the present is operational and freely available to the public.
Highlights
Surface all-wave net radiation (Rn ), characterizing the available radiative energy at the Earth’s surface that is usually called surface radiation budget, is the difference between total upward and total downward radiation
A new Rn product that offers high spatiotemporal resolution, high accuracy, and global coverage over long time periods is urgently needed for a variety of applications
We developed the Global LAnd Surface Satellite (GLASS) daytime Rn product
Summary
Surface all-wave net radiation (Rn ), characterizing the available radiative energy at the Earth’s surface that is usually called surface radiation budget, is the difference between total upward and total downward radiation. Where Rns is the net shortwave radiation, Rnl is the net longwave radiation, Rsi is the incident shortwave radiation, Rso is the reflected shortwave radiation calculated by Rso = α*Rsi where α is shortwave broadband albedo, Rli is the downward longwave radiation, and Rlo is the outgoing longwave radiation. Rn drives the processes of evapotranspiration and air and soil heat fluxes, as well as other smaller energy-consuming processes such as photosynthesis [1,2]. The net surface radiation controls the energy and water exchanges between the biosphere and the atmosphere, and has major influences on the Earth’s weather and climate [6,7].
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