Markov chain as a tool for forecasting daily precipitation in the vicinity of the city of Bydgoszcz, Poland

Abstract

The crop yield depends on numerous weather factors, but mainly on the rainfall pattern and course of air temperature during vegetation period. Investigating the dependence of yields on rainfall, apart from its amount, there also should be taken into account dry spell periods. The two-state Markov chain was considered as a precipitation pattern in the investigation, since it is generally recognized as a simple and effective model of the precipitation occurrence. Based on the daily precipitation totals from the period 1971—2013, the Markov chain was designated. The data were derived from a measuring point of the University of Science and Technology in Bydgoszcz, Poland. As one of the objectives was to determine the order of the Markov chain examined describing the change of precipitation in subsequent days. Another aim was to investigate rainfall dependencies on a month of a year. An analysis of this data leads to the conclusion that the chain is second order. This is confirmed by the two criteria used: BIC (Bayesian Information Criteria) and AIC (Akaike Information Criteria). The research regarded the precipitation volume dependence on a month of the year.