Surface flux estimation using radiometric temperature: A dual-temperature-difference method to minimize measurement errors


  • J. M. Norman,

  • W. P. Kustas,

  • J. H. Prueger,

  • G. R. Diak


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.