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Assessment of MERRA-2 Land Surface Energy Flux Estimates
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2018
Source: Journal of Climate, 31(2), 671-691.
Details:
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Journal Title:Journal of Climate
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Personal Author:
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NOAA Program & Office:
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Description:In the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) system the land is forced by replacing the model-generated precipitation with observed precipitation before it reaches the surface. This approach is motivated by the expectation that the resultant improvements in soil moisture will lead to improved land surface latent heating (LH). Here aspects of the MERRA-2 land surface energy budget and 2-m air temperatures T-2m are assessed. For global land annual averages, MERRA-2 appears to overestimate the LH (by 5Wm(-2)), the sensible heating (by 6Wm(-2)), and the downwelling shortwave radiation (by 14Wm(-2)) while underestimating the downwelling and upwelling (absolute) longwave radiation (by 10-15Wm(-2) each). These results differ only slightly from those for NASA's previous reanalysis, MERRA. Comparison to various gridded reference datasets over boreal summer (June-August) suggests that MERRA-2 has particularly large positive biases (>20Wm(-2)) where LH is energy limited and that these biases are associated with evaporative fraction biases rather than radiation biases. For time series of monthly means during boreal summer, the globally averaged anomaly correlations Ranom with reference data were improved from MERRA to MERRA-2, for LH (from 0.39 to 0.48 vs Global Land Evaporation Amsterdam Model data) and the daily maximum T-2m (from 0.69 to 0.75 vs Climatic Research Unit data). In regions where T-2m is particularly sensitive to the precipitation corrections (including the central United States, the Sahel, and parts of South Asia), the changes in the T-2m Ranom are relatively large, suggesting that the observed precipitation influenced the T-2m performance.
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Source:Journal of Climate, 31(2), 671-691.
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Document Type:
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Rights Information:Other
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Compliance:Submitted
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Main Document Checksum:urn:sha256:1fe5afa859dc067818f77914170af917d0bafea0a7117b408f3adb92147f6624
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