A Markov chain model for daily rainfall occurrence at Tel Aviv

TLDR

Earlier studies have characterized the distributions of dry and wet spells and weather cycles in the region. The model derives the distribution of rainy days per week, month, or other period. A Markov chain model accurately fits daily rainfall occurrence data, reproduces rainfall patterns, and shows that rainy day counts in different months are independent.

Abstract

Abstract A Markov chain probability model is found to fit Tel Aviv data of daily rainfall occurrence. This accounts for the form of the distributions of dry and of wet spells and of weather ‘cycles’ which have been presented in earlier papers. Further aspects of rainfall occurrence patterns may be derived as well, and are found to fit the data. In particular, the distribution of the number of rainy days per week, month or other period is obtained. Numbers of rainy days in different months are apparently independent.