Predicting Monthly Precipitation in the Wet Season over Saudi Arabia Using a Seasonal Prediction System

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In this study, we evaluated the skill of the Scale Interaction Experiment-Frontier Research Center for Global Change, version 2 (SINTEX-F2), model in predicting precipitation over Saudi Arabia in the wet months (November–April) at 1–3-month lead times. It was found that the SINTEX-F2 model 1-month lead prediction was skillful in predicting precipitation over the southwestern regions of Saudi Arabia in November and February. Analysis revealed that the skillful prediction of precipitation in November was due to the skillful prediction of sea surface temperature anomalies in the midlatitudes of the central North Pacific and the associated atmospheric variability. In February, the skill was associated with the skillful prediction of sea surface temperature anomalies in the equatorial eastern Pacific and the associated teleconnections. Significance Statement We tried to identify the months within the wet season in which precipitation could be predicted with high skill over Saudi Arabia. Analysis showed that the SINTEX-F2 model was skillful in predicting precipitation over the southwestern regions of Saudi Arabia in November and February at a 1-month lead time. The model skill was due to the model predicting the SST anomalies and the atmospheric variable anomalies with high skill.