First-order 4-D data assimilation in a distributed model of surface temperature and energy fluxes

Reviews a first-order four-dimensional (4D) data assimilation exercise carried out as part of an investigation into the spatial scaling of surface temperature and energy fluxes in a semi-arid watershed, the upper San Pedro (~7600 km²), in SE Arizona. Realistic estimates of several spatial and temporal data sets were required prior to calculating surface fluxes. The choice of these parameters presents several challenges related to: typical model assumptions, scarcity of data, spatial resolution and model validation. Some of these problems, and ways to address them, are described