MODELING DAILY RAINFALL USING A SEMI-MARKOV REPRESENTATION OF CIRCULATION PATTERN OCCURRENCE

The daily rainfall occurrence process is modeled as a process coupled to atmospheric circulation. Atmospheric circulations are classified into a finite number of circulation patterns. Time series of circulation patterns are modeled with the help of a semi-Markov field. Rainfall is linked to the circulation patterns using conditional probabilities. The model is applied using the classification scheme of the German Weather Service for the time period 1881-1988. Precipitation data measured at different locations for a period of 34 years are linked to the circulation patterns. Using the model several series of circulation patterns and corresponding rainfall occurrences are simulated. Statistics of the simulated and the observed sequences are similar. The model is also applicable for the simulation of nonstationary atmospheric conditions like climate change.