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Title:   Author  item
                                            BRUSCANTINI, C - Collaboratoritem
                                            Crow, Wadeitem
                                            GRINGIS, F - Collaboratoritem
                                            PERNA, P - Collaboratoritem
                                            MAAS, M - Collaboratoritem
                                            KARSZENBAUM, H - Collaborator
  Submitted to: IEEE Transactions on Geoscience and Remote Sensing
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 12/1/2013
                                    Publication  Date: 1/27/2014
                                    Publication URL: http://handle.nal.usda.gov/10113/60024Citation: Bruscantini, C., Crow, W.T., Gringis, F., Perna, P., Maas, M., Karszenbaum, H. 2014. An observing system simulation experiment (OSSE) for the aquarius/SAC-D soil moisture product. IEEE Transactions on Geoscience and Remote Sensing. 50(10):6086-6094. DOI:10.1109/TGARS.2013.2294915.Interpretive Summary: Remotely-sensed surface soil moisture retrievals have the potential to contribute to a wide range of important agricultural applications including: fertilizer application, drought monitoring, yield forecasting, and irrigation scheduling. However, the value of current satellite-based soil moisture products is reduced by relatively high amounts of error in these retrievals. Observing System Simulation Experiments (OSSEs) are powerful tools for examining - and potentially addressing - error sources that exist in current satellite data products. This paper describes the application of an OSSE to soil moisture products derived from the NASA Aquarius satellite mission. Results in the study highlight the important role of land surface heterogeneity in magnifying soil moisture retrieval errors. A potential solution to this problem is developed and tested. Results from this study will eventually lead to more accurate soil moisture retrieval products over heterogeneous agricultural landscapes.
                                Technical Abstract: An Observing System Simulation Experiment for the Aquarius/SAC-D mission has been developed for assessing the accuracy of soil moisture retrievals from passive L-band remote sensing. The implementation of the OSSE is based on: a 1-km land surface model over the Red-Arkansas River Basin, a forward microwave emission model to simulate the radiometer observations, a realistic orbital and sensor model to resample the measurements mimicking Aquarius operation, and an inverse soil moisture retrieval model. The simulation implements a zero-order radiative transfer model. Retrieval is done by direct inversion of the forward model. The Aquarius OSSE attempts to capture the influence of different error sources: land surface heterogeneity, instrument noise and retrieval ancillary parameter uncertainty on the accuracy of Aquarius surface soil moisture retrievals. In order to assess the impact of these error sources on the estimated volumetric soil moisture, a quantitative error analysis is performed via the comparison of footprint-scale synthetic soil moisture with ’true’ soil moisture fields obtained from the direct aggregation of the original 1-km soil moisture field fed into the forward model. Results show that, in heavily vegetated areas, soil moisture retrievals present a positive bias that can be suppressed with an alternative aggregation strategy for ancillary parameter vegetation water content (VWC). Retrieval accuracy was also evaluated when adding errors on 1-km VWC (which are intended to account for errors in VWC derived from remote sensing data). For soil moisture retrieval RMSE of the order of 0.05%vol/vol, relative error bias on VWC should be less than 12%.


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