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Title:   Author  item
                                            Jackson, Thomasitem
                                            BINDLISH, R. - Science Systems, Incitem
                                            CHAN, S. - Jet Propulsion Laboratoryitem
                                            ZHAO, T. - Chinese Academy Of Sciencesitem
                                            Cosh, Michaelitem
                                            O'NEILL, PEGGY - Goddard Space Flight Centeritem
                                            COLLANDER, ANDREAS - Jet Propulsion Laboratoryitem
                                            NJOKU, ENI - Jet Propulsion Laboratoryitem
                                            KERR, Y. - Collaborator
  Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 4/1/2014
                                    Publication  Date: 7/13/2014
                                    Citation: Jackson, T.J., Bindlish, R., Chan, S., Zhao, T., Cosh, M.H., O'Neill, P., Collander, A., Njoku, E., Kerr, Y. 2014. Evaluation of SMAP radiometer level 2 soil moisture algorithms using four years of SMOS data. International Geoscience and Remote Sensing Symposium Proceedings. July 13-18, 2014. 2014 CDROM.Interpretive Summary:
                                Technical Abstract: The objectives of the SMAP (Soil Moisture Active Passive) mission include global measurements of soil moisture at three different spatial resolutions.  SMAP will provide soil moisture with a 3-day revisit time at an accuracy of 0.04 m3/m3   The 36 km gridded soil moisture product (L2_SM_P) is primarily based on the passive microwave observations. In this paper we contribute to the development of the radiometer soil moisture product (L2_SM_P) by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products.  SMOS observations provide us with the opportunity to develop a testbed for the evaluation of different SMAP L2_SM_P retrieval algorithm options. The use of real-world global observations will help in the development and selection of different land surface parameters and ancillary observations needed for the soil moisture algorithms. Output of the potential radiometer-only SMAP algorithms was compared to both in situ measurements and SMOS soil moisture products.  These studies will contribute to both the selection and refinement of the SMAP L2_SM_P pre-launch algorithm.
Microwave observations from the SMOS mission were reprocessed to simulate SMAP microwave radiometer observations at a constant incidence angle of 40o. The reprocessed brightness temperature data provide a basis for evaluating different SMAP L2_SM_P algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval:
(a) Single Channel Algorithm horizontal polarization (SCA-H), which is based on a zero-order approximation to the radiative transfer equation and uses the channel that is most sensitive to soil moisture. Brightness temperature is corrected for the effects of temperature, vegetation, roughness, and soil texture using ancillary data sets. This is the current SMAP L2_SM_P baseline algorithm. 
(b) Single Channel Algorithm vertical polarization (SCA-V) – similar to SCA-H, but uses vertical polarization instead of horizontal polarization observations. 
© Microwave Polarization Ratio Algorithm (MPRA) – a two-parameter retrieval model (soil moisture and vegetation opacity). It uses the microwave polarization ratio at 1.4 GHz and emissivity to parameterize vegetation opacity and estimate soil moisture. 
(d) Dual Channel Algorithm (DCA) – uses both radiometer polarizations to iteratively solve for soil moisture and vegetation opacity.
The outputs of the candidate radiometer-only SMAP algorithms were compared to both in situ measurements and SMOS soil moisture products for a period of four years (2010-2013). 
The global soil moisture spatial patterns obtained from SMOS TB and the SCA-H retrieval algorithm are consistent with geographical features. The estimated soil moisture is very low for desert and arid regions (Africa, Middle East, Central Asia, and Central Australia). High values of soil moisture were observed for forested areas in northern latitudes (Canada and Russia). High soil moisture is also observed over South America.
The SMOS soil moisture estimates using the SCA-H algorithm for January 2010-November 2013 were compared with the in situ observations over USDA ARS watersheds that have been  used in the validation of soil moisture products. The SMOS/SMAP SCA-H retrievals have a low bias and RMSE (RMSE=0.038 m3/m3, Bias=-0.018 m3/m3, R=0.737). The results from the SCA-V algorithm were comparable to the SCA-H retrievals, although the study also suggested the need to have polarization dependent vegetation parameters in the SCA retrievals.  In contrast to the SCA, the soil moisture retrieval performance was not as good with other algorithm options. The use of both polarizations in the other algorithms (MPRA and DCA) resulted in soil moisture retrievals with a positive soil moisture bias and greater range of response than the in situ observations. Initial results indicate the SMAP L2_S


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