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Title:   Author  item
                                            BOLTEN, J - National Aeronautics And Space Administration (NASA)item
                                            Crow, Wadeitem
                                            ZHAN, X - National Oceanic & Atmospheric Administration (NOAA)item
                                            Jackson, Thomasitem
                                            REYNOLDS, C - Foreign Agricultural Service (FAS, USDA)
  Submitted to: IEEE Transactions on Geoscience and Remote Sensing
                                    Publication Type: Proceedings
                                    Publication Acceptance Date: 5/1/2010
                                    Publication  Date: 6/5/2010
                                    Citation: Bolten, J., Crow, W.T., Zhan, X., Jackson, T.J., Reynolds, C. 2010. Microwave soil moisture retrieval under trees using a modified Tau-Omega Model. In: Proceedings of the International Geoscience and Remote Sensing Symposium, July 25-30, 2010, Honolulu, Hawaii. 2010 CDROM.Interpretive Summary:
                                Technical Abstract: IPAD is to provide timely and accurate estimates of global crop
conditions for use in up-to-date commodity intelligence reports.
A crucial requirement of these global crop yield forecasts is the
regional characterization of surface and sub-surface soil
moisture. However, due to the spatial heterogeneity and
dynamic nature of precipitation events and soil wetness,
accurate estimation of regional land surface-atmosphere
interactions based sparse ground measurements is difficult [1].
Temporal resolution is particularly important for predicting
adequate surface wetting and drying between precipitation
events and is closely integrated with CADRE. We attempt to
improve upon the existing system by applying an Ensemble
Kalman filter (EnKF) data assimilation system to integrate
surface soil moisture retrievals from the NASA Advanced
Microwave Scanning Radiometer (AMSR-E) into the USDA
soil moisture model. The improved temporal resolution and
spatial coverage of the satellite-based EOS Advanced
Microwave Scanning Radiometer (AMSR-E) is envisaged to
provide a better characterization of root zone soil moisture at the
regional scale and enable more accurate crop monitoring in key
agricultural areas. This work aims at evaluating the utility of merging satellite retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a
quantitative analysis of the assimilated soil moisture product
over West Africa (9°N-20°N; 20°W-20°E). This region contains
many key agricultural areas and has a high agro-meteorological
gradient from desert and semi-arid vegetation in the North, to
grassland, trees and crops in the South, thus providing an ideal
location for evaluating the assimilated soil moisture product
over multiple land cover types and conditions. A data denial
experimental approach is utilized to isolate the added utility of
integrating remotely-sensed soil moisture by comparing
assimilated soil moisture results obtained using (relatively) lowquality precipitation products obtained from real-time satellite
imagery to baseline model runs forced with higher quality
rainfall. An analysis of root-zone anomalies for each model
simulation suggests that the assimilation of AMSR-E surface
soil moisture retrievals can add significant value to USDA rootzone
predictions derived from real-time satellite precipitation
products.


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