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Title:   Author  item
                                            Anderson, Marthaitem
                                            Kustas, William

                                                         - *Bill*item
                                            NORMAN, JOHN - University Of Wisconsinitem
                                            HAIN, CHRISTOPHER - National Oceanic & Atmospheric Administration (NOAA)item
                                            MECIKALSKI, JOHN - University Of Alabamaitem
                                            SCHULTZ, LORI - University Of Alabamaitem
                                            GONZALEZ-DUGO, MARIA - Venta Del Llano Ifapa Centeritem
                                            CAMMALLERI, CARMELLO - Collaboratoritem
                                            D'URSO, GUIDO - University Of Naplesitem
                                            PIMSTEIN, AGUSTIN - Collaborator
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 8/16/2010
                                    Publication  Date: 9/15/2010
                                    Citation: Anderson, M.C., Kustas, W.P., Norman, J., Hain, C., Mecikalski, J., Schultz, L., Gonzalez-Dugo, M.P., Cammalleri, C., D'Urso, G., Pimstein, A. 2010. Mapping daily evapotranspiration at field to global scales using geostationary and polar orbiting satellite imagery [abstract]. Surface analysis SAF-2010 User Workshop. 2010 CDROM.Interpretive Summary:
                                Technical Abstract: Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (soil moisture, advection, air temperature) are affecting plant stress. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5-10 km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI), spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites.  An overview of this modeling approach will be presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions of 30 m.  The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the U.S. Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites . Work is underway to further evaluate multi-scale ALEXI implementations over the U.S., Europe and, Africa and other continents with geostationary satellite coverage.


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