Determination of Markov Chain Transition Probabilities for Daily Rainfall Data in Jordan
Keywords:
rainfall, daily rainfall, Markov chain, transition probabilities, equilibrium probabilities, spell lengths, JordanAbstract
This study aims to determine Markov chain transition probabilities for daily rainfall data of 39 meteorological stations across Jordan. Two states were imposed to the chains, namely dry and wet, and first order was used as the dependence structure. This leads to four transition probabilities for each station in each month, namely dry-to-dry (pdd), dry-to-wet (pdw), wet-to-dry (pwd), and wet-to-wet (pww). In the end of the study, it is concluded that pdd > pdw for all stations in all months, and pww ? pwd in only 15.1% of the times, which are concentrated in the middle of the rainy season (i.e., December–March) at North of Jordan. Also, all months tend to be dry in the long term, especially October, November, April, and May. Most of the expected dry spell lengths range from 5 to 100 days, while the expected wet spell lengths range mostly from 1 to 2 days, which indicates the tendency of the Jordanian weather to be dry across the country.
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