This work aims at characterizing the conditional probability of single or consecutive dry and wet days in West Africa using the first-order Markov chain approach during the monsoon season (June to October). The results show that the probabilities of having a wet day (PW), a wet day preceded by another wet day (PWW) and a wet day preceded by a dry day (PDW) are stronger in regions where the rainfall is maximum (mountain regions). In contrast, the probabilities of having a dry day (PD), a dry day preceded by a wet day (PWD) and a dry day preceded by another dry day (PDD) are lower in the regions with higher precipitation. The seasonal cycle of PWW (PDD) is consistent with that of PW (PD), respectively in Western Sahel and Central Sahel regions. At the interannual timescale, MK test results show that PW and PDW (PD and PDD) exhibit statistically significant increasing (decreasing) trends the Western Sahel and the Central Sahel. Besides, the shorter dry spells (3 days) show statistically significant decreasing trends only in the Western Sahel. The longer dry spells (5, 7 and 10 days) show statistically significant downward trends over the Western and Central Sahel. Wet spells probabilities show non-significant decreasing trends in all sub-domains, except in the Western Sahel for the 10 days spells. Knowledge of theses probabilities will contribute to develop efficient strategies for water resources management and agricultural decision making in West African countries.
Key words: Markov chain, rainfall, occurrence, wet spell, dry spell, West Africa.
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