Fowler, H.J., Kilsby, C.G., and O’Connell, P.E. 2000. A stochastic rainfall model for the assessment of regional water resource systems under changed climatic conditions. Hydrol. Earth Sys. Sci., 4, 261-280.
Abstract
A stochastic model is developed for the synthesis of daily precipitation using conditioning by weather types. Daily precipitation statistics at multiple sites within the county of Yorkshire, UK, are linked to objective Lamb weather types (LWTs) and used to split the region into three distinct precipitation sub-regions. Using a variance minimization criterion, the 27 LWTs are grouped into three physically realistic clusters. A semi-Markov chain model is used to synthesize long sequences of weather clusters, maintaining the observed persistence and transition probabilities. The Neyman-Scott Rectangular Pulses (NSRP) model is then fitted for each weather cluster, using a defined summer and winter period. The combined model reproduces key aspects of the historic precipitation regime at temporal resolutions down to the hourly level.
Long synthetic precipitation series are of great utility in the sensitivity analysis of water resource systems under current and changed climatic conditions. This methodology enables investigation into the impact of variations in weather type persistence or frequency. In addition, rainfall model statistics can be altered to simulate instances of increased intensity or proportion of dry days for example, for individual weather clusters. The input of such data into a water resource model, simulating potential atmospheric circulation changes, will provide a valuable tool for future planning of water resource systems. The ability of the model to operate at an hourly level also allows its use in a wide range of hydrological impact studies, e.g. variations in river flows, flood risk estimation