Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: October 10, 2003
Publication Date: December 8, 2003
Citation: Crow, W.T., Kustas, W.P. 2003. The simultaneous retrieval of surface evaporation fraction and heat transfer coefficients using variational data assimilation and surface radiometric temperature observations. EOS Transactions, American Geophysical Union. Available: http://www.agu.org/cgi-bin/SFgate/SFgate
Recent advances in land data assimilation have yielded data assimilation techniques designed to solve the surface energy balance based on remote observations of surface radiometric temperature and a simple prognostic equation for surface temperature. These approaches have a number of potential advantages over existing diagnostic models, including the ability to make energy flux predictions between satellite overpass times, more physically realistic representations of ground heat flux, and reduced requirements for ancillary parameter estimation. Of particular interest is the variational approach presented by Caparrini et al. (Journal of Hydrometeorology, 2003) which uses a force-restore equation for surface temperature as a constraint for the simultaneous estimation of both evaporative fraction and bulk heat transfer coefficients from sequences of surface radiometric temperature observations.
Using eddy correlation flux tower data and analogous energy balance results obtained from the diagnostic Two-Source Model (TSM), this presentation will examine the performance of the Caparrini et al. algorithm over a range of vegetative and hydrologic conditions in the southern United States. Results identify circumstances under which the simultaneous ' and unambiguous - retrieval of both surface evaporation fraction and heat transfer coefficients is possible and clarify parameter interpretation issues associated with the single-source geometry of the variational approach. Inter-comparison with the TSM model illustrates circumstances under which the increased parameter complexity of the TSM model is justified by its more accurate two-source representation of thermal emission from partial vegetation canopies. Potential improvements to current variational data assimilation techniques will also be discussed.