Prediction of bimodal monsoonal rainfall in the central dry zone of Myanmar using teleconnections with global sea surface temperatures

In the central dry zone of Myanmar, mean annual rainfall is less than 1000 mm. Although rainfed agriculture commonly practiced there, feasibility farming compromised by large fluctuations and frequent occurrence years. The monthly distribution follows a bimodal pattern. intensity monsoonal from May to October characterized two peaks, an early peak (May-June) late (August–October), separated inter-monsoon (July). return times wet years make management problematic. There very little correlation between (r=–0.257). However, teleconnected sea surface temperatures (SSTs) in certain areas Pacific Ocean real time. Furthermore, at lag 6–9 months, there are teleconnections monsoonal, inter-monsoonal, SSTs Indian Atlantic Ocean. We used Elman artificial neural network model predict based on with oceans months before occurred. coefficient predicted observed exceeded 0.7 all three cases.