Estimating surface energy fluxes: A key component for estimating potential evaporation

A model has been developed that can predict the solar and infrared downwelling radiation fluxes using ground based measurements of the air temperature, relative humidity and the cloud cover. The algorithm has been validated using several years of ground-based data for 15 sites across the globe (13 sites from the Baseline Surface Radiation Network (BSRN), as well as data for two sites in Crete). These stations cover a wide range of climatic conditions, including those of arctic, desert, sub-tropical, Mediterranean, as well as elevated sites. The RMS residual for the monthly mean short wave (SW) solar flux (approximately 0.2 to 3 µm) is typically 12 Wm^-2 (mean observed daily SW flux across all stations is 305 Wm^-2), while the thermal IR flux (roughly 4-50 µm) derived using the algorithms gives RMS residuals of approximately 8 Wm^-2 (mean observed daily IR flux across all stations is 180 Wm^-2). Daily observed and modelled fluxes, as well as residuals are shown for 8 of the stations in Figure 1. As well as the radiation fluxes, the model also estimates the atmospheric water vapour content, which has been tested using available radiosonde data for 8 of the stations. In comparison with the observed mean water vapour content, the values derived by the algorithms have typical values for bias of 0.01 g cm^-2 and RMS residual of 0.15 g cm^-2 (mean across all stations is 1.65 g cm^-2), accounting for 80 % of the observed variation. Since the model uses readily available meteorological data, the net radiation flux at the surface can readily be calculated (given the surface albedo), providing an estimate of a dominant term in estimating potential evaporation and evapotranspiration.