Modelling, interpolation and stochastic simulation in space and time of global solar radiation

Global solar radiation data used as daily inputs for most cropping systems and water budget models are frequently available from only a few weather stations and over short periods of time. To overcome this limitation, the Campbell–Donatelli model relates daily maximum and minimum air temperatures to solar radiation. In this study, calibrated values of model site specific parameters and efficiencies of radiation estimates are reported for 29 stations in northern Italy. Their average root mean squared error equals 2.9 MJ m−2 per day. Model inputs and model output show a clear spatial and temporal structure. For large scale model application, atmospheric transmissivity is calculated with ‘calculate first, interpolate later’ (CI) procedures and ‘interpolate the inputs, calculate later’ (IC) procedures. The mean squared error for CI equals 0.0359, whereas that for IC equals 0.0636. Comparison of ‘calculate first, simulate later’ (CS) procedures with ‘simulate the inputs, calculate later’ (SC) procedures shows a higher spatial sensitivity of SC procedures. The study shows how the model can be best applied to estimate global solar radiation, both at visited and unvisited locations, over a large and productive agricultural area in Italy, and hence, to better use water budget/crop productivity models. In addition, CS procedures show the associated error.