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Assessment of GEWEX/SRB version 3.0 monthly global radiation dataset over China |
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| Authors: | Futing Wu Congbin Fu |
| Institution: | 1. START/TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China 2. Graduate University of Chinese Academy of Sciences, Beijing, 100049, China 3. Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing, 210093, China |
| Abstract: | NASA/GEWEX (National Aeronautics and Space Administration/Global Energy and Water Cycle Experiment) Surface Radiation Budget (SRB) has released its latest radiation dataset, version 3.0. We examine the accuracy of the monthly mean global radiation in China using surface-observed radiation (SOR) data at 42 stations during the period 1984?C2004. Overall comparison shows a general overestimation of satellite retrieval radiation data with a bias of 14.6?W?m?2 and a root mean square error of 25.9?W?m?2. Differences at individual stations suggested satellite data are consistently higher than surface measurements over eastern China (110°E), but occasional underestimation occurs in Western China, especially Southwest China. Intra-annual variation analysis indicates that SRB satellite radiation can capture the annual cycle well. For trend of global radiations, there are evident discrepancies between satellite retrievals and surface measurements for both the entire period and segmental terms. For the entire period from 1984 to 2004, most stations show a positive trend based on surface measurements, while the majority of collocated pixels show a negative trend. Segmental trends demonstrated that the principal difference occurred during the first period of 1981?C1994. After 1994, the two datasets change similarly. Therefore, trend analysis in terms of detecting global dimming/brightening remains very difficult as surface measurements and satellite products do not agree yet. In addition, some proposals are made towards better understanding of the bias of satellite products and to improve further the satellite retrieval algorithm with better representation of both cloud and aerosol properties. |
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