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Title:   Author  item
                                            MOLERO, B. - Collaboratoritem
                                            MERLIN, O. - Collaboratoritem
                                            MALBETEAU, Y. - Collaboratoritem
                                            AL BITAR, A. - Collaboratoritem
                                            CABOT, F. - Collaboratoritem
                                            STEFAN, V. - Collaboratoritem
                                            KERR, Y. - Collaboratoritem
                                            BACON, S. - Collaboratoritem
                                            Cosh, Michaelitem
                                            BINDLISH, R. - Collaboratoritem
                                            Jackson, Thomas
  Submitted to: Remote Sensing of Environment
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 5/1/2016
                                    Publication  Date: 7/1/2016
                                    Citation: Molero, B., Merlin, O., Malbeteau, Y., Al Bitar, A., Cabot, F., Stefan, V., Kerr, Y., Bacon, S., Cosh, M.H., Bindlish, R., Jackson, T.J. 2016. SMOS disaggregated soil moisture product at 1 km resolution: processor overview and first validation results. Remote Sensing of Environment. 180:361-376. doi:10.1016/j.rse.2016.02.045Interpretive Summary: A new methodology for disaggregating coarse spatial resolution soil moisture information provided by the Soil Moisture Ocean Salinity satellite was assessed. The approach utilizes high resolution soil temperature data. Performance  was  assessed  by comparing  the  disaggregated and  non-disaggregated  SM  (L3)  datasets  against  the  in  situ measurements in both the spatial and temporal domains. Sites included study areas in the U.S. and Australia.  The evaluation of this network brought to view that the algorithm needs to be improved to adapt to all types of soil. Future improvements should include more ancillary information. The methodology will be implemented for routine processing and use in hydrologic applications.
                                Technical Abstract: The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of ~50 km. However, agricultural applications (irrigation, crop monitoring) and some  hydrological  applications  (floods  and  modeling of  small  basins) require  higher  resolution SM information. In order to overcome this spatial mismatch, a disaggregation algorithm called Disaggregation based on Physical And Theoretical scale Change (DISPATCH) combines higher-resolution data from optical/thermal sensors with the SM retrieved from microwave sensors like SMOS, producing higher-resolution SM as the output. A DISPATCH-based processor has been implemented for the whole globe (emerged  lands)  in  the  Centre  Aval  de  Traitement  des  Données  SMOS  (CATDS),  the  French  data processing center for SMOS  Level  3 products. This new CATDS  Level-4 Disaggregation processor (C4DIS)  generates  SM  maps  at  1  km  resolution.  This  paper  provides  an  overview  of  the  C4DIS architecture, algorithms and output products. Differences with the original DISPATCH prototype are explained and major processing parameters are presented. The C4DIS SM product is compared against L3 and in situ SM data during a one year period over the Murrumbidgee catchment and the Yanco area (Australia), and during a four and a half year period over the Little Washita and the Walnut Gulch watersheds (USA). The four validation areas represent highly contrasting climate regions with different landscape properties. According to this analysis, the C4DIS SM product improves the spatio-temporal correlation with in situ measurements in the semi-arid regions with substantial SM spatial variability mainly driven by precipitation and irrigation. In sub-humid regions like the Little Washita watershed, the performance of the algorithm is poor except for summer, as result of the weak moisture-evaporation	coupling. Disaggregated products do not succeed to have and additional benefit in the Walnut Gulch	watershed, which is also semi-arid but with well-drained soils that are likely to cancel the spatial contrast needed  by  DISPATCH.  Although  further  validation  studies  are  still  needed  to  better  assess  the performance of DISPATCH in a range of surface and atmospheric conditions, the new C4DIS product is expected to provide satisfying results over regions having medium to high SM spatial variability.


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