A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation

The major bottlenecks of existing algorithms to estimate the spatially distributed surface energy balance in composite terrain by means of remote sensing data are briefly summarised. The relationship between visible and thermal infrared spectral radiances of areas with a sufficiently large hydrological contrast (dry and wet land surface types, vegetative cover is not essential) constitute the basis for the formulation of the new Surface Energy Balance Algorithm for Land (SEBAL). The new algorithm (i) estimates the spatial variation of most essential hydro-meteorological parameters empirically, (ii) requires only field information on short wave atmospheric transmittance, surface temperature and vegetation height, (iii) does not involve numerical simulation models, (iv) calculates the fluxes independently from land cover and (v) can handle thermal infrared images at resolutions between a few meters to a few kilometers. The empirical relationships are adjusted to different geogra-phical regions and time of image acquisition. Actual satellite data is inserted in the derivation of the regression coefficients. Par