A markov chain model for wet and dry spell probabilities at Yola, Adamawa State.

Abstract

The theoretical probabilities of wet and dry spells were derived from Markov Chain Model using the threshold level of 0.25mm per day for a period of 20 years to predict the length of dry spell and wet spell during the rainy season (April to Sepember) at Gyawana meteorological station on Yola, North Eastern Nigeria. The equilibrum probabilities for the station over 20-year period are pie=(0.76,0.24). This implies that the probability of dry day occurence regardless of the weather conditions of the previous days is 0.76. Th mean weather cycle was 7.44. This information can be used to select the best planting date by avoiding the period of high risk of long dry period near the beginning of the rainy season always experienced in northen Nigeria.