Abstract In this relatively unprecedented study, the effects of thirty-four leading teleconnection Patterns (indices) of atmospheric circulation- on regional-scale for the Middle East- along with precipitation over Iran have been investigated. Different types of data including teleconnection Indices from NOAA (NCEP/NCAR, BOM) and monthly precipitation data from thirty-six synoptic stations of Iran were applied. The data have been investigated with various types of statistical and synoptical methods. The results indicate that El Nino–Southern Oscillation (ENSO) is the most effective factor and it could possibly influence the spatiotemporal variation of precipitation on all types of climate regimes in Iran. ENSO (nino3.4), The Atlantic Multidecadal Oscillation (AMO) and The Arctic oscillation (AO) are known as the first three important indices, determined by Principal component analysis (PCA) method. The research has clarified that a combination of warm phase of ENSO and a predominant Southeastern (SE) wind over the Indian Ocean can result in a significant moisture transport from the Indian Ocean to the Middle East and to Iran; a combination of cold phase of ENSO and a predominant Northwestern (NW) wind over the Indian Ocean can be followed by a widespread drought over the Middle East and Iran. The results also indicate that a combination of the first three important above-mentioned indices and the Indian Ocean Dipole (IOD) can provide a much better explanation for spatial and temporal variation of precipitation of Iran. Finally, the results of this study will enable us to present a new approach and new graphical-conceptual modeling, called "Teleconnection-Synoptic Method (TSM)"to clarify the underlying mechanism that can explain the spatial and temporal variations of global atmospheric circulation and precipitation of Iran. According to the correlation of different patterns with precipitation, the strongest relationships are related to the Scandinavia Index (SCN), Pressure Change in East Pacific (dPEPac) and Trade Wind Index at the 850 hPa (TrdWnd850), respectively.

中文翻译：

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伊朗使用主要遥相关力 (MTF) 天气建模的降水分析

摘要 在这项相对史无前例的研究中，研究了大气环流的 34 个主要遥相关模式（指数）对中东区域尺度以及伊朗降水的影响。应用了不同类型的数据，包括来自 NOAA (NCEP/NCAR, BOM) 的遥相关指数和来自伊朗 36 个天气站的月降水数据。已使用各种类型的统计和天气方法对数据进行了调查。结果表明，厄尔尼诺-南方涛动（ENSO）是最有效的因素，它可能会影响伊朗所有类型气候制度的降水时空变化。ENSO (nino3.4)、大西洋多年代际振荡 (AMO) 和北极振荡 (AO) 被称为前三个重要指标，通过主成分分析 (PCA) 方法确定。研究已经阐明，ENSO 的暖相和印度洋上空的主导东南 (SE) 风相结合，可以导致从印度洋到中东和伊朗的大量水分输送；ENSO 的寒冷阶段和印度洋上空的主导西北 (NW) 风相结合，随后中东和伊朗将出现大面积干旱。结果还表明，将上述前三个重要指数与印度洋偶极子（IOD）相结合，可以更好地解释伊朗降水的时空变化。最后，这项研究的结果将使我们能够提出一种新方法和新的图形概念建模，称为“