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Variability of the Cold Season Climate in Central Asia. Part II: Hydroclimatic Predictability

机译:中亚寒冷季节气候变异性。 第二部分:循环预测性

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Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November-March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Nino. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.
机译:中亚(CA)受到降水的大幅度。本研究提出了一种统计模型,在寒冷的季节(11月至3月)中的三个次区域中的降水异常与前一月的各种预测因子。有希望的预测技能是为覆盖的两个次区域1)乌兹别克斯坦,土库曼斯坦,吉尔吉斯斯坦,塔吉克斯坦和哈萨克斯坦南部和2)伊朗,阿富汗和巴基斯坦。 10月份的ENSO被确定为主要预测因素。欧亚雪盖和准两年期振荡进一步提高了预测性能。为了理解物理机制,对这些预测器与CA之间的冬季循环之间的电连接分析。预测因子和大规模循环指标的相关分析表明热带循环模式的季节性持久性以及雪覆盖欧亚的雪覆盖差异的动力迫使西风循环。压力和湿度图案的EOF分析允许将循环变异与CA分开到西方和热带模式中,并确认所识别的预测因子影响各自的循环特性。根据先前建立的CA天气型分类,在其对区域循环的影响方面调查了预测因子。结果表明,由于ENSO变型,荷兰电池的修改,在El Nino的阿拉伯海湾的水分供应增强。他们进一步表明欧亚雪覆盖对冬季北极振荡(AO)和北半球rossby波轨道的影响。阳性异常利于与干燥条件相关的天气类型,而阴性异常促进了在阳性AO条件期间发生的准静止槽的形成。

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