Climatic controls on the interannual to decadal variability in Saudi Arabian dust activity: Toward the development of a seasonal dust prediction model. Issue 5 (6th March 2015) - Yu, Yan; Notaro, Michael; Liu, Zhengyu; Wang, Fuyao; Alkolibi, Fahad; Fadda, Eyad; Bakhrjy, Fawzieh
Abstract: The observed climatic controls on springtime and summertime Saudi Arabian dust activities during 1975–2012 are analyzed, leading to development of a seasonal dust prediction model. According to empirical orthogonal function analysis, dust storm frequency exhibits a dominantly homogeneous pattern across Saudi Arabia, with distinct interannual and decadal variability. The previously identified positive trend in remotely sensed aerosol optical depth since 2000 is shown to be a segment of the decadal oscillation in dust activity, according to long‐duration station record. Regression and correlation analyses reveal that the interannual variability in Saudi Arabian dust storm frequency is regulated by springtime rainfall across the Arabian Peninsula and summertime Shamal wind intensity. The key drivers of Saudi Arabian dust storm variability are identified. Winter‐to‐spring La Niña enhances subsequent spring dust activity by decreasing rainfall across the country's primary dust source region, the Rub' al Khali Desert. A relatively cool tropical Indian Ocean favors frequent summer dust storms by producing an anomalously anticyclonic circulation over the central Arabian Peninsula, which enhances the Shamal wind. Decadal variability in Saudi Arabian dust storm frequency is associated with North African rainfall and Sahel vegetation, which regulate African dust emissions and transport to Saudi Arabia. Mediterranean sea surface temperatures (SSTs) also regulate decadal dust variability, likely through their influence on Sahel rainfall and Shamal intensity. Using antecedent‐accumulated rainfall over the Arabian Peninsula and North Africa, and Mediterranean SSTs, as low‐frequency predictors, and tropical eastern Pacific and tropical Indian Ocean SSTs as high‐frequency predictors, Saudi Arabia's seasonal dust activity is well predicted. Key Points: Saudi Arabian dust activity has distinct interannual and decadal variability Dust variability is related to springtime rainfall and summertime wind Saudi Arabian dust frequency is well predicted by SSTs and precipitation