ENSO Teleconnections and Seasonal Forecasts of Wet Season Droughts in the Arabian Peninsula

Seasonal drought forecasting is critical for the hyper-arid, water-stressed Arabian Peninsula (AP), where droughts have become more frequent and intense as manifestations of long-term regional aridification. The region depends heavily on cold-season rainfall to sustain agriculture and livestock, making rainfall deficits particularly disruptive in vulnerable areas. Here, forecasts from the North American Multi-Model Ensemble (NMME) and observations are used to produce Standardized Precipitation Index (SPI) data over the AP for 1991–2020, focusing on six overlapping 3-month wet seasons from October–December to March–May. Covariability between AP SPI and Pacific sea surface temperatures (SSTs) is examined using singular value decomposition. The leading mode represents approximately 27–38% of the shared and 37–57% of the individual variability and is linked to ENSO-related SST anomalies. Leading SVD SPI pattern is associated with well-organized 500 mb height anomalies. NMME forecast skill for the 3-month SPI was evaluated across multiple lead times, revealing pronounced spatial and temporal variability through both deterministic and probabilistic metrics. The models demonstrate skill linked to ENSO teleconnections, particularly in La Niña-linked droughts. Deterministic forecast skill, measured through anomaly correlation, is highest at the shortest lead times, where combining observed data with model forecasts provides the greatest added value, and declines sharply at longer leads. Skill is higher in early wet-season periods (October–December, November–January, and December–February) and decreases in later periods, with March–May showing the lowest skill relative to persistence forecasts. Assessments based on reliability diagrams and ranked probability skill score also reveal that probabilistic forecast skill is strongest during the early wet season, decreases in subsequent periods, and is minimal in March–May. These findings suggest that NMME-based seasonal forecasts could offer useful early warning information for drought across the AP, especially at short lead times and during ENSO-active periods.