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Abstract:
Surface soil temperature estimates at approximately 0.05 m depth are needed to retrieve soil moisture from the planned Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) satellite. Numerical weather prediction (NWP) systems as operated by various weather centers produce global estimates of soil temperature. In this study in situ data collected over the state of Oklahoma are used to assess surface (soil) temperature from three NWP systems: (1) the integrated forecast system from the European Center for Medium range Weather Forecasts (ECMWF), (2) the modern-era retrospective analysis for research and applications (MERRA) from the NASA Global Modeling and Assimilation Office, and (3) the global data assimilation system used by the National Center for Environmental Prediction (NCEP). The results are presented by hour of day with specific attention directed to the SMAP early morning overpass time at around 6 A.M. local time, and the period of 1 April to 1 October 2009. It was found that the NWP systems estimate the 0.05 m soil temperature at this time of day with an overall root mean square error of 1.9 to 2.0 K. It is shown that this error can be reduced to 1.6 to 1.8 K when differences between the modeling and measurement depth are accounted for by synchronizing each NWP set to match the mean phase of the in situ data and adjusting the amplitude in accordance with heat flow principles. These results indicate that with little calibration all products meet the SMAP error budget criteria over Oklahoma.