Abstract

The surface temperature of a land surface measured by a radiometer, Ts,r, and the temperature “felt” by the air, Taero, often differ significantly and are difficult if not impossible to define rigorously. However, recent studies conducted by the principle investigators with several land surface models suggests that this problem can be largely resolved. This project will use several of these models to reconcile the difference between Ts,r and Taero, while maintaining consistency within the models and with theory and data. This will permit remotely sensed surface temperature measurements taken from an arbitrary view angle over a partial canopy cover to be used to produce high quality sensible and latent heat flux estimates, or to validate or update the surface temperature produced by a SVAT in a climate or mesoscale model.

In the first part of the project, theoretical and conceptual differences among several models in the formulations used for surface roughness, Ts,r and Taero, will be investigated.

In the second part of the project, data from several recent field experiments, including FIFE, SGP, ARM-CART, CASES, SALSA, MONSOON, and BOREAS will be used. Remotely-sensed estimates of LAI and Ts,r will be used in conjunction with field data at individual surface flux sites to evaluate self-consistency and robustness of the models. An additional goal is to refine the models by developing superior treatments for Ts,r, Taero, and scalar roughness which provide consistency between models, theory and data.

The third part of the project is to examine the spatial scaling properties of the models and their ability to infer spatial variability of Taero from spatial variations in Ts,r.

This project is funded under NRA 98-OES-11, by the National Aeronautics and Space Administration (NASA). Principal Investigators: Richard Crago, Bucknell University; Mark Friedl, Boston University; Yeqiao Wang, University of Rhode Island; and William Kustas, USDA, Agricultural Research Service. Check for the projectbackground (NASA Research Announcement NRA 98-OES-11).

Selected project publications:

Yang, J. and Wang, Y., 2002. Using an Emissivity Calibration Model and Landsat-7 ETM+ Data to Estimate Land Surface Temperature, Journal of Remote Sensing, 6(Suppl.):104-110.

Yang, J., Y. Wang, and P. August, 2004. Estimation of Land Surface Temperature Using Spatial Interpretation and Satellite-Derived Surface Emissivity, Journal of Environmental Informatics.

Please forward questions to yqwang@uri.edu.