A Markov Chain Model For The Probabilities Of Wet And Dry Spells (Case Study For Location Karachi)

Abstract

Markov Chain model was used to evaluate probabilities of getting a sequence of wet and dry days, which is essential for many practical applications such as to design and predict the yields of different crops. One of the challenging problems for agricultural experts is the random nature of rainfall. The intensity of the rainfall is greatly influenced by the local climatical condition. This model is used to predict the long term weather condition using the previous data 1987-2006 for location Karachi.