Abstract The atmospheric low frequency variability at a regional or global scale is represented by teleconnection. Using monthly dataset of the Climatic Research Unit (CRU) for the period 1971–2016, the impacts of four large-scale teleconnection patterns on the climate variability over Southwest Asia are investigated. The large-scale features include the El Nino-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the East Atlantic (EA) teleconnection patterns, as well as western tropical Indian Ocean (WTIO) sea surface temperature anomaly index. Results indicate that ENSO and EA are the first leading modes that explain variation of Southwest Asian precipitation, with positive (negative) anomalies during El Nino (La Nina) and the negative (positive) phase of EA. Variation of Southwest Asian near-surface temperature is most strongly related to WTIO index, with above-average (below-average) temperature during the positive (negative) phase of WTIO index, although the negative (positive) phase of NAO also favours the above-average (below-average) temperature. On the other hand, temperature (precipitation) over Southwest Asia shows the least response to ENSO (WTIO). ENSO and EA individually explain 13 percent annual variance of precipitation, while WTIO index explains 36 percent annual variance of near-surface temperature over Southwest Asia. Analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis Interim (ERA-Interim) data indicated establishments of negative (positive) geopotential height anomalies in the middle troposphere over Southwest Asia during El Nino (La Nina) or the negative (positive) phase of NAO, EA and WTIO. The response of precipitation variability over Southwest Asia to NAO is opposite to that expected from the geopotential height anomalies, but the correlation between precipitation and NAO is not statistically significant. Due to predictability of large-scale teleconnections, results of this study are encouraging for improvement of the state-of-the-art seasonal prediction of the climate over Southwest Asia.

中文翻译：

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大规模遥相关对西南亚气候变率的影响

摘要 区域或全球尺度的大气低频变化以遥相关为代表。使用气候研究单位 (CRU) 1971-2016 年期间的月度数据集，研究了四种大规模遥相关模式对西南亚气候变率的影响。大尺度特征包括厄尔尼诺-南方涛动（ENSO）、北大西洋涛动（NAO）和东大西洋（EA）遥相关模式，以及西热带印度洋（WTIO）海面温度异常指数。结果表明ENSO和EA是解释西南亚降水变化的首要模式，厄尔尼诺（拉尼娜）和EA的负（正）期为正（负）异常。西南亚近地表温度的变化与 WTIO 指数的相关性最强，在 WTIO 指数的正（负）阶段温度高于平均（低于平均），尽管 NAO 的负（正）阶段也有利于上述- 平均（低于平均）温度。另一方面，西南亚的温度（降水）对ENSO（WTIO）的反应最小。ENSO 和 EA 分别解释了 13% 的年降水变化，而 WTIO 指数解释了西南亚近地表温度的 36% 年变化。对欧洲中期天气预报中心 (ECMWF) 再分析中期 (ERA-Interim) 数据的分析表明，在厄尔尼诺 (La Nina) 或负 ( NAO、EA 和 WTIO 的正）阶段。西南亚降水变率对NAO的响应与位势高度异常的预期相反，但降水与NAO的相关性不显着。由于大规模遥相关的可预测性，这项研究的结果对于改进西南亚最先进的气候季节性预测是令人鼓舞的。西南亚降水变率对NAO的响应与位势高度异常的预期相反，但降水与NAO的相关性不显着。由于大规模遥相关的可预测性，这项研究的结果对于改进西南亚最先进的气候季节性预测是令人鼓舞的。西南亚降水变率对NAO的响应与位势高度异常的预期相反，但降水与NAO的相关性不显着。由于大规模遥相关的可预测性，这项研究的结果对于改进西南亚最先进的气候季节性预测是令人鼓舞的。