ABSTRACT In this research, the Bayesian quantile regression model is applied to investigate the teleconnections between large oceanic–atmospheric indices and drought standardized precipitation index (SPI) in Iran. The 12-month SPI time series from 138 synoptic stations for 1952–2014 were selected as the drought index. Three oceanic–atmospheric indices, the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI) and the Multivariate El Niño/Southern Oscillation Index (MEI), were selected as covariates. The results show that NAO has the weakest impact on drought in different quantiles and different regions in Iran. La Niña conditions amplified droughts through all SPI quantiles in western, Caspian Sea coastal regions and southern regions. The positive phase of MEI significantly modulates low SPI quantiles (i.e. drought conditions) throughout the Zagros region, Caspian Sea coastal regions and southern regions. The study shows that the effect of large oceanic–atmospheric indices have heterogeneous impacts on extreme dry and wet conditions.

中文翻译：

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使用分位数回归分析海洋-大气指数与伊朗干旱之​​间的遥相关

摘要 在这项研究中，贝叶斯分位数回归模型被应用于研究大型海洋-大气指数与伊朗干旱标准化降水指数 (SPI) 之间的遥相关关系。选择1952-2014年138个天气站的12个月SPI时间序列作为干旱指数。三个海洋-大气指数，北大西洋涛动 (NAO)、南方涛动指数 (SOI) 和多元厄尔尼诺/南方涛动指数 (MEI)，被选为协变量。结果表明，NAO对伊朗不同分位数和不同地区的干旱影响最弱。拉尼娜现象通过西部、里海沿海地区和南部地区的所有 SPI 分位数放大了干旱。MEI 的正相位显着调节低 SPI 分位数（即 干旱条件）整个扎格罗斯地区、里海沿海地区和南部地区。研究表明，大型海洋-大气指数的影响对极端干燥和潮湿条件具有异质性影响。