J1.6 Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses

Tuesday, 8 January 2019: 9:45 AM
North 127ABC (Phoenix Convention Center - West and North Buildings)
Clara Draper, CIRES, Boulder, CO; and R. H. Reichle

A newly developed, weakly coupled land and atmosphere data assimilation system for NASA's Global Earth Observing System model is presented. It is then used to demonstrate the benefit of assimilating satellite soil moisture from the Advanced Scatterometer and the Soil Moisture Ocean Salinity mission into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The land surface flux partition, and hence daytime evolution of the boundary layer, are sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally the soil moisture assimilation could induce substantial improvements. Compared to a control experiment in which only the atmospheric observations were assimilated, assimilating the soil moisture together with the atmospheric observations decreased the RMSE against independent observations of daily maximum 2-m temperature (T2m) from the Global Historical Climatology Network (GHCN), by up to 0.5K in a large region spanning from western Europe across southern Russia. Globally, the mean daily maximum T2m RMSE vs. GHCN was reduced from 2.82 to 2.79 K. For the land fluxes, the soil moisture assimilation reduced the mean RMSE across 29 Fluxnet-2015 sites from 34.2 W/m2 to 32.6 W/m2 for latent heating, and from 37.7 W/m2 to 36.5 W/m2 for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.
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