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Title:   Author  item
                                            Anderson, Marthaitem
                                            Kustas, William

                                                         - *Bill*item
                                            NORMAN, JOHN - UNIV OF WISCONSIN
  Submitted to: American Geophysical Union
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 4/22/2006
                                    Publication  Date: 12/15/2006
                                    Citation: Anderson, M.C., Kustas, W.P., Norman, J.M. 2006. Mapping evaporative stress at continental scales using GOES thermal imagery [abstract]. EOS Transactions, American Geophysical Union, Joint Assembly Supplements. 87(36):H23F03.Interpretive Summary:
                                Technical Abstract: Robust, operational methodologies for mapping daily evapotranspiration (ET), soil moisture, and moisture stress over large areas using remote sensing will have widespread utility in a variety of resource management and forecasting applications. Here we examine the utility a regional surface energy balance system -" the Atmosphere-Land Exchange Inverse (ALEXI) model -" driven primarily by thermal infrared remote sensing data from the Geostationary Operational Environmental Satellites (GOES), for its potential for routine and long-term mapping of ET and soil moisture stress. GOES is an excellent (albeit underutilized) data source for routine land-surface monitoring because it has high temporal frequency (15min) and continental-scale coverage, and its operational status, integral to national weather forecasting applications, means a long history of archived data and a good likelihood of continuation. Using thermal band imagery from GOES and vegetation cover information from MODIS, the ALEXI algorithm has been executed over a 10-km resolution grid covering the continental U.S. for April-October of 2002-2004. In this paper we look more qualitatively at inter- and intra- annual temporal patterns in maps of ET and the ratio of actual to potential ET (fPET) generated with the ALEXI algorithm over this three-year interval. Here, fPET is interpreted as a signature of soil moisture deficiency. Patterns in fPET will be assessed in comparison with contemporaneous gridded precipitation data and with other standard indices of drought and surface moisture stress to determine whether thermal remote sensing, as interpreted by ALEXI, provides useful information regarding drought conditions at continental scales.


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