On the information content of surface meteorology for downward atmospheric long-wave radiation synthesis

One of the key uncertainties in site-based evaluations of land surface, hydrological or ecological models stems from the lack of availability of downward long-wave radiation, even at observational stations where tens of other key variables are measured. State of the art techniques for its synthesis are typically functionally dependent on surface temperature, vapour pressure and some representation of cloudiness. Here we show that existing functional forms for downward long-wave synthesis underutilise information in these key predictor variables, and that in fact cloudiness variables may be redundant. By using an empirical model at a range of sites globally, we examine the contribution of each of the predictor variables and conclude that an extremely simple empirical model may provide more defensible prediction where no a priori knowledge of site behavior exists