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Submitted to: Annual Land Advanced Very High Resolution Radiometer Workshop
Publication Type: Proceedings Publication Acceptance Date: 10/10/2000 Publication Date: N/A Citation: N/A Interpretive Summary: The temperature of the air near the surface and the temperature of the surface itself reflect the balance of the various surface energy flux components. The surface heat fluxes strongly interact with the overlying atmosphere and influence the characteristics of the planetary boundary layer, ultimately influencing local and regional weather patterns. For these reasons, major efforts have focused on developing techniques to use surface and air temperatures to infer magnitudes of the components of the surface energy budget. The performance of these schemes vary widely, due to several factors. These include atmospheric correction and sensor calibration, non-uniqueness of the surface-air temperature relationship to heat transfer, and errors in defining meteorological variables for each satellite pixel from a sparse network of weather station observations. A simple modeling approach is developed which minimizes the impact of these limiting factors. Examples from recent field studies illustrate its utility, and application with satellite imagery indicates its operational capability for regional scale applications. Output from this model will prove useful for assessing agro-ecosystem productivity and health at regional scales. Technical Abstract: Satellite remote sensing data have provided regional and global coverage of landscape properties relevant for monitoring land surface fluxes. This has prompted the development of land-atmosphere exchange models that can use remotely sensed inputs to derive surface heat fluxes. Many of these approaches use radiometric surface temperature as the key boundary condition since surface-air temperature differences reflect the overall balance of the various surface energy flux components. The performance of these schemes vary widely, due to several factors. These include: 1) uncertainties in atmospheric correction, surface emissivity, and radiometer calibration; 2) non-uniqueness of the radiometric-aerodynamic temperature relationship; 3) errors in defining meteorological variables for each satellite pixel from a sparse network of weather station observations. A simple modeling approach will be described which attempts to minimize the impact of these limiting factors. Examples from recent field studies will illustrate its utility. |
