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中国科学院东亚区域气候-环境重点实验室是经中国科学院批准,在原中国科学院大气物理研究所全球变化东亚区域研究中心基础上成立的开放实验室。研究领域包括东亚区域环境、气候变化等全球变化研究的诸多方面,多学科交叉研究是本实验室的基本特色。同时,实验室还承...
【学术报告】Prof. Jian-Hua Qian,Department of Environmental, Earth & Atmospheric Sciences, University of Massachusetts

报告题目:Regional Weather and Climate Modeling and Analysis

报  告  人:Prof. Jian-Hua Qian

单        位:Department of Environmental, Earth & Atmospheric Sciences,

                   University of Massachusetts

时        间:2016年8月4日上午10:00-11:00

地        点:大气所40号楼319会议室

 

We try to build a linkage between daily weather and long-term climate in these studies. We have done regional weather and climate modeling, weather typing analysis, and multi-scale climate process studies over a tropical region of the Maritime Continent in Southeast Asia and a mid-latitude region of Northeast United States.  

For the Maritime Continent, six weather types (WTs) are computed across the Maritime Continent during austral summer (September-April) using cluster analysis of unfiltered, daily, low-level winds at 850 hPa, by a k-means algorithm. 

The WTs are interpreted either as snapshots of the intraseasonal Madden-Julian Oscillation (MJO); or as seasonal features, such as the transition between boreal- and austral-summer monsoons; or as slow variations associated with the El NiñoSouthern Oscillation (ENSO). Scale interactions are analyzed in terms of the different phenomena that modulate regional-scale wind speed and direction, or the diurnal-cycle of rainfall. The diurnal cycle is shown to play an important role in determining the rainfall over islands, particularly in the case of the quiescent WT that is more frequent during El Niño and the suppressed phase of the MJO; both of these lead to more rainfall over the mountainous southern Java, western Sumatra, and western Borneo due to the monsoonal-damping-effect and the island-wake-effect on the strength of the diurnal cycle.

For Northeast U.S., we classified daily weather types in the winter season by a kmeans clustering method, and analyzed the relationship between the frequency of typical and extreme weather types and large-scale teleconnection patterns such as ENSO, North Atlantic Oscillation, Arctic Oscillation, Pacific North American Pattern, etc


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