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[1] Many applications exist within the fields of agriculture, forestry, land management, and hydrologic assessment for routine estimation of surface energy fluxes, particularly evapotranspiration (ET), at spatial resolutions of the order of 10 1 m. A new two-step approach (called the disaggregated atmosphere land exchange inverse model, or DisALEXI) has been developed to combine low-and high-resolution remote sensing data to estimate ET on the 10 1 -10 2 m scale without requiring any local observations. The first step uses surface brightness-temperature-change measurements made over a 4-hour morning interval from the GOES satellite to estimate average surface fluxes on the scale of about 5 km with an algorithm known as ALEXI. The second step disaggregates the GOES 5-km surface flux estimates by using high-spatial-resolution images of vegetation index and surface temperature, such as from ASTER, Landsat, MODIS, or aircraft, to produce high-spatial-resolution maps of surface fluxes. Using data from the Southern Great Plains field experiment of 1997, the root-mean-square difference between remote estimates of surface fluxes and ground-based measurements is about 40 W m À2 , comparable to uncertainties associated with micrometeorological surface flux measurement techniques. The DisALEXI approach was useful for estimating field-scale, surface energy fluxes in a heterogeneous area of central Oklahoma without using any local observations, thus providing a means for scaling kilometer-scale flux estimates down to a surface flux-tower footprint. Although the DisALEXI approach is promising for general applicability, further tests with varying surface conditions are necessary to establish greater confidence.

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Abstract. Surface temperature serves as a key boundary condition that defines the partitioning of surface radiation into sensible and latent heat fluxes. Surface brightness temperature measurements from satellites offer the unique possibility of mapping surface heat fluxes at regional scales. Because uncertainties in satellite measurements of surface radiometric temperature arise from atmospheric corrections, surface emissivity, and instrument calibrations, a number of studies have found significant discrepancies between modeled and measured heat fluxes when using radiometric temperature. Recent research efforts have overcome these uncertainties and in addition have accounted for the difference between radiometric and aerodynamic temperature by considering soil and vegetative-canopy aerodynamic resistances. The major remaining obstacle to using satellite data for regional heat flux estimation is inadequate density of near-surface air temperature observations. In this paper we describe a simple, operational, double-difference approach for relating surface sensible heat flux to remote observations of surface brightness temperature, vegetative cover and type, and measurements of near-surface wind speed and air temperature from the synoptic weather network. A double difference of the time rate of change in radiometric and air temperature observations is related to heat flux. This double-difference approach reduces both the errors associated with deriving a radiometric temperature and with defining meteorological quantities at large scales. The scheme is simpler than other recent approaches because it requires minimal ground-based data and does not require modeling boundary layer development. The utility of this scheme is tested with ground-based radiometric temperature observations from several arid and subhumid climates with a wide range of vegetative cover and meteorological conditions. In a recent review on monitoring evaporation with remote sensing, Kustas and Norman [1996] conclude that obtaining reliable estimates of the heat fluxes using remotely sensed surface radiometric temperature TR(0) at a viewing angle 0 from remote brightness temperature measurements has been hampered by several factors. These include correcting the remotely sensed brightness temperatures for atmospheric and emissivity effects, calibration issues, and the nonuniqueness of the aerodynamic-radiometric temperature relationship due to 2263