Submitted to: American Meteorological Society
Publication Type: Abstract Only
Publication Acceptance Date: March 31, 2008
Publication Date: April 30, 2008
Citation: Kustas, W.P., Anderson, M.C., Crow, W.T., Agam, N. 2008. A paradigm shift in the application of thermal infrared remote sensing for land surface modeling: John Norman's critical contributions [abstract]. American Meteorological Society, 28th Conference on Agricultural and Forest Meteorology and 18th Conference on Atmospheric Biogeosciences. Available: http://ams.confex.com/ams/28Hurricanes/techprogram/paper_137266.htm.
Over 10 years ago, John Norman and co-authors proposed a thermal-based land surface modeling strategy that treated the energy exchange and kinetic temperatures of the soil and vegetated components in a unique “two-source” approach addressing the key factors affecting the convective and radiative exchange between the soil-canopy system and the lower atmosphere. While the model is fairly simple, requiring surface information operationally available from remote sensing, it is physically robust requiring no a priori calibration that has plagued many previous approaches. This modeling strategy also accommodates in a relatively simple way the influence of soil background temperature and energy exchange as well as radiometer viewing angle on the thermal signal. John Norman’s contribution came at a time when thermal-based techniques for large scale land surface flux and evapotranspiration (ET) estimation was generally considered unreliable and not viable for operational remote sensing applications. However, his new paradigm of how to utilize radiometric surface temperature in land surface modeling has converted many skeptics and more importantly rejuvenated many in the research and operational remote sensing community to reconsider the utility of thermal infrared remote sensing for monitoring land surface fluxes from local to regional scales. In fact, Norman’s land surface scheme has recently been incorporated in a continental scale modeling system using GOES and MODIS data. Both ET and a physically-based drought monitoring product are currently being generated for the continental U.S. This presentation will provide an overview of the model and its utility as well as what are likely to be future applications in hydrology, meteorology and agriculture.