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Open AccessArticle

Merging Satellite Retrievals and Reanalyses to Produce Global Long-Term and Consistent Surface Incident Solar Radiation Datasets

College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
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Remote Sens. 2018, 10(1), 115; https://doi.org/10.3390/rs10010115
Received: 11 November 2017 / Revised: 12 January 2018 / Accepted: 13 January 2018 / Published: 16 January 2018
(This article belongs to the Special Issue Remote Sensing of Land-Atmosphere Interactions)
Surface incident solar radiation (Rs) is a key parameter in many climatic and ecological processes. The data from satellites and reanalysis have been widely used. However, for reanalysis, Rs data has been shown to have substantial spatial bias, and the time span of reliable satellite Rs is too short for climatic and ecological studies. Combining reanalysis and satellite data would be an effective method for generating long-term and consistent Rs datasets. Here, we apply a cumulative probability density function-based (CPDF) method to merge eight reanalyses with the latest available satellite Rs data from Clouds and Earth’s Radiant Energy System Energy Balanced and Filled (CERES EBAF) surface retrievals. The CPDF method not only reduces the spatial bias of the reanalysis Rs data, but also makes the Rs datasets in a global, long-term and consistent way. The observed Rs data collected at 54 Baseline Surface Radiation Network (BSRN) stations from 1992 to 2016 are used to evaluate the method. Results show that the CPDF method could reduce the mean absolute biases (MAB) of the reanalysis Rs effectively by 21.24–64.36%. The European Centre for Medium-Range Weather Forecasts Re-Analysis interim (ERA-interim) reanalysis Rs data, which are available for 1979 onward, perform the best before MAB = 13.20 W·m−2 and after MAB = 10.40 W·m−2 merging. This small post-merging MAB of the ERA-interim reanalysis is caused by the MAB of 9.90 W·m−2 in the satellite Rs retrievals. The Japanese 55-year reanalysis provides Rs values back to 1958, and CPDF can reduce its MAB by 32.87%, to 11.17 W·m−2. The National Oceanic and Atmospheric Administration (NOAA)-CIRES twentieth-century reanalysis (CIRES) and the ECMWF twentieth-century reanalysis (ERA20CM) provide century-long Rs estimates. CIRES performs better after merging. The MAB of CIRES can be reduced by 32.10%, to 12.99 W·m−2, while ERA20CM’s can be reduced by 12.51%, to 16.40 W·m−2. View Full-Text
Keywords: surface incident solar radiation; data fusion; CERES EBAF; reanalyses; bias correction surface incident solar radiation; data fusion; CERES EBAF; reanalyses; bias correction
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Feng, F.; Wang, K. Merging Satellite Retrievals and Reanalyses to Produce Global Long-Term and Consistent Surface Incident Solar Radiation Datasets. Remote Sens. 2018, 10, 115.

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