Energy balance based surface flux estimation from satellite data, and its application for surface moisture assimilation

Considerable research efforts have been spent in deriving land surface characteristics from (operational) satellite data. An important aspect of the land surface is its partitioning of available radiative energy over sensible and latent heat, what importantly is determined by the amount of vegetation and available soil moisture. The relation between evaporation and soil moisture content can be used to derive regional or global soil moisture estimates from satellite data. Since these satellite data alone do not contain all necessary information for calculation of surface flux budgets, merging these data with operational meteorological model predictions and data assimilation possibly provides an important step forward in realistic surface flux and soil moisture estimations. Experience with three different satellite algorithms to estimate surface fluxes and/or soil moisture contents are discussed. The first principle explicitly uses the horizontal variability of surface albedo and surface temperature in order to anchor extreme surface evaporation regimes at a given time. It was shown to contain useful signal in a case study carried out over the Iberian Peninsula. Its underlying assumptions require relatively small target areas, limiting operational use. The second algorithm calculates a pixelwise maximum and minimum surface temperature, and uses the remotely sensed temperature to interpolate between extreme evaporation regimes. It is tested at various scales, but appears sensitive to aerodynamic parameterizations, which are difficult to calibrate on the large scale covered in NWP applications. The third scheme is based on the principle that the rate of change of the surface temperature is a function of the surface heat capacity, which depends on vegetation and soil moisture. A case study combining satellite data and a mesoscale model in the Southern Great Plains experiment showed encouraging results. The method is fairly robust, but its sensitivity to the parameterization of the coupling of the surface skin to the atmosphere and the underground is yet to be established.