Drought may affect more people than any other climate extremes worldwide, especially in (semi)arid climates such as Iran. In this paper, the empirical Multivariate Standardized Drought Index (MSDI) that incorporates the meteorological and agricultural drought conditions is first computed. The wavelet analysis is then used to identify teleconnections between ocean–atmosphere oscillations from Atlantic (AMO, AO, and NAO) and Pacific (ENSO, PDO, and PNA) oceans and Iran’s drought at a highly dense network of regularly gridded points (2485) during 1979–2016. It is found that among the droughts of 1980, 1985–86, 1990–91, 1998–99, 2000, 2007–08, and 2010–11, both the 2007–08 and 2000 are the broadest and strongest across the country. Overall, those droughts that occurred in the 2000–2016 period (average MSDI = -1.14) were, on the whole, stronger than those happened over the latest 20 years of the 20th century (average MSDI = -0.77), reflecting the strengthening of the influence that ENSO has on the Middle East climate in the most recent decades. According to the wavelet coherence results, unlike the Atlantic-based oscillations that almost have an anti-correlation with droughts, there is a positive correlation between Pacific-based oscillations and Iran’s drought. It is also identified that the severe historical droughts across the country were usually associated with a strong La Niña coupled with cold PDO and positive NAO phases in the latest 30 years. Overall, droughts in Iran tend to be substantially controlled by multiple interacting of climate indices since three-coupled indices have stronger coherence with drought than either two-coupled indices or single ones. A combination of the three indices of ENSO, PDO, and NAO has the strongest coherence with Iran’s drought compared to all the other three- and two-coupled, and all single indices, indicating that integrated impact of climate indices can better capture hydroclimate teleconnections. These multiple interacting impacts from the different large-scale climate circulation patterns mark a significant step towards an improved prediction of severe droughts across Iran and can also be used for other parts of the world.

与全球任何其他极端气候事件相比，干旱可能影响更多人，尤其是在（半）干旱气候中，例如伊朗。在本文中，首先计算了结合气象和农业干旱条件的经验多元标准化干旱指数 (MSDI)。然后使用小波分析来识别来自大西洋（AMO、AO 和 NAO）和太平洋（ENSO、PDO 和 PNA）海洋的海洋-大气振荡与伊朗在规则网格点的高密度网络中的干旱之间的遥相关 (2485) 1979-2016 年期间。研究发现，在1980年、1985-86年、1990-91年、1998-99年、2000年、2007-08年和2010-11年的干旱中，2007-08年和2000年都是全国范围最广、强度最大的干旱。总体而言，2000-2016 年期间发生的干旱（平均 MSDI = -1.14）总体上 强于 20 世纪最近 20 年发生的情况（平均 MSDI = -0.77），反映了 ENSO 在最近几十年对中东气候的影响加强。根据小波相干结果，与几乎与干旱反相关的大西洋振荡不同，太平洋振荡与伊朗干旱呈正相关。还确定，过去 30 年来，全国发生的严重历史性干旱通常与强拉尼娜、寒冷的 PDO 和正 NAO 阶段有关。总体而言，伊朗的干旱在很大程度上受到气候指数多重相互作用的控制，因为三耦合指数与干旱的相关性强于两耦合指数或单一指数。ENSO、PDO 和 NAO 三个指数的组合与所有其他三联和两联指数以及所有单一指数相比，与伊朗干旱的一致性最强，表明气候指数的综合影响可以更好地捕捉水文气候遥相关。来自不同大规模气候环流模式的这些多重相互作用的影响标志着朝着改进伊朗严重干旱预测迈出的重要一步，也可用于世界其他地区。