The weather generation game: a review of stochastic weather models

This article reviews the historical development of statistical weather mode ls, from simple analyses of runs of consecutive rainy and dry days at singl e sites, through to multisite models of daily precipitation. Weather genera tors have been used extensively in water engineering design and in agricult ural, ecosystem and hydrological impact studies as a means of in-filling mi ssing data or for producing indefinitely long synthetic weather series from finite station records. We begin by describing the statistical properties of the rainfall occurrence and amount processes which are necessary precurs ors to the simulation of other (dependent) meteorological variables. The re lationship between these daily weather models and lower-frequency variation s in climate statistics is considered next, noting that conventional weathe r generator techniques often fail to capture wholly interannual variability Possible solutions to this deficiency - such as the use of mixtures of slo wly and rapidly varying conditioning variables are discussed. Common applic ations of weather generators are then described. These include the modellin g of climate-sensitive systems, the simulation of missing weather data and statistical downscaling of regional climate change scenarios. Finally, we c onclude by considering ongoing advances in the simulation of spatially corr elated weather series at multiple sites, the downscaling of interannual cli mate variability and the scope for using nonparametric techniques to synthe size weather series.