Evaluating the effect of ocean-atmospheric indices on drought in Iran
This study investigated the relationship between ocean-atmospheric indices and drought in Iran. Using > 30-year precipitation data from 37 synoptic stations (ending 2015), standard precipitation index (SPI) was calculated for periods of 1-, 3-, 6-, 9-, 12-, 15-, 18-, 24-, and 48-month time scales. A set of monthly ocean-atmospheric oscillations (OA) indices including Antarctic Oscillation (AAO), Arctic Oscillation (AO), Atlantic Multi-Decadal Oscillation (AMO), North Atlantic Oscillation (NAO), El Nino Southern Oscillation (ENSO): (NINO 1.2, NINO 3, NINO 3.4, NINO 4, SOI), and Western Mediterranean Oscillation (WeMo) were also included in our analysis. The simultaneous relationship between SPI and ocean-atmospheric oscillations was investigated using Spearman’s correlation test. The cross correlation function (CCF) coefficient was also utilized to investigate their asynchronous relationships at 1-, 3-, 6-, 9-, 12-, 15-, 18-, 24-, 48-month lag time. Finally, the multivariate linear regression was used to model the end relationships among SPI time-scales and OA indices. AMO and NINO 4 had the most significant and most frequent relationship with SPI in the western and northern parts of Iran. Except for southeastern parts, AMO, NINO 3.4, and NINO 4 had the most significant and most frequent relationship with SPI. Moreover, results showed that asynchronous relationships outperformed simultaneous ones. AMO was recognized as the most important index in modeling the relationship between drought and OA indices across all stations with high potentials to be used for predicting climatic conditions and drought management in Iran.