Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: March 12, 2010
Publication Date: April 21, 2010
Citation: Holmes, T.R., Jackson, T.J., Reichle, R., Basara, J. 2010. The temperature in microwave soil moisture retrieval [abstract]. Abs. 17. BARC Poster Day. Technical Abstract: In the near future two dedicated soil moisture satellites will be launched, the Soil Moisture and Ocean Salinity (SMOS) satellite and the Soil Moisture Active Passive (SMAP) satellite that are expected to contribute to our understanding of the global hydrological cycle. It is well known that microwave soil moisture retrieval algorithms must account for the physical temperature of the emitting surface. Solutions to this include: difference, or ratio indices; forecast model products; thermal infrared satellite observations; and high frequency passive microwave estimates. The availability of multifrequency observations in the same data stream has made the use of high frequency temperature estimates, specifically 37 GHz (Ka-band), an attractive option. SMOS and SMAP will not include a 37 GHz (Ka-band) microwave radiometer. Therefore, alternative algorithms and data sources will be utilized and explored. One proposed approach is the use of temperature output from numerical weather prediction (NWP) models. This temperature estimate will need to closely match the spatial resolution and the overpass time of SMOS and SMAP (between 6 and 7 am/pm local time). To date, very little analysis has been performed to assess the accuracy of the NWP forecasts in terms of land surface temperature. In addition, the relationship between the model products and the requirements of radiative transfer and soil moisture retrieval algorithm temperature requirements needs to be assessed. The goal of this paper is to set up a validation framework that can be applied to NWP outputs. In this investigation, we use in situ data from the Oklahoma Mesonet (at 5 cm) to assess the near surface soil temperature from the Modern Era Retrospective-analysis for Research and Applications (MERRA). A radiative transfer model as implemented in the most commonly used soil moisture retrieval algorithms will be used to assess sensitivity to errors in the estimated surface temperature. These results should contribute to improved algorithm design and implementation for the new L-band satellite missions.