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气象:2013,39(6):665-674
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大气变量物理分解法在极端温度事件前期信号提取中的应用
(北京大学物理学院大气海洋科学系,北京100871)
Application of Physical Decomposition of Atmospheric Variables to the Prediction of Extreme Temperature Events
(Department of Atmospheric and Oceanic Sciences, Peking University, Beijing 100871)
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投稿时间:2012-12-11    修订日期:2013-03-28
中文摘要: 观测的高空大气位势高度和温度可以应用物理分解的思路估算出纬圈平均的对称气候态、非对称气候态、纬圈平均的瞬变对称扰动和非对称扰动等四个分量。本文用美国NCEP/NCAR再分析资料分解出的非对称高度扰动和温度扰动可以作为发生在华北的2005年6月区域热浪和12月区域低温事件的早期信号。结果得到:地面区域极端气温事件是对流层和平流层大气扰动在地面的表现。这次热浪最强日对流层上部(250 hPa)正的高度扰动和对流层低层(850 hPa)正的温度扰动是在7 d前从欧洲传播而来的,而这次低温最强日对流层上部(300 hPa)负的高度扰动和对流层低层(850 hPa)负的温度扰动也是在13 d前从欧洲传播而来的。物理分解后的瞬变扰动天气图是地面热浪和低温事件预报的一种可用工具。
Abstract:The observed geopotential height and temperature in the troposphere stratosphere can be physically decomposed into four components to estimate climatic states and anomalies, namely zonal mean symmetric climate, asymmetric climate, zonal mean instantaneous symmetric anomaly and instantaneous asymmetric anomaly. In this paper, the asymmetric anomaly was extracted from the NCEP/NCAR reanalysis data and used as early signals to indicate the regional heat wave and low temperature events that occurred in North China in June and December 2005, respectively. The result shows that the surface temperature events are some responses to atmospheric disturbances in troposphere and stratosphere. For the heat wave event, its early signals of positive temperature anomaly at 850 hPa and positive height anomaly at 250 hPa can be traced from Europe 7 days ahead, while the early signals of low temperature event are negative temperature anomaly at 850 hPa and negative height anomaly at 300 hPa which are also from Europe with a lead of 13 days. The anomalous synoptic chart provided by this physical decomposition is a useful tool to predict the surface temperature events.
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基金项目:国家科技支撑计划(2009BAC51B04)和公益性行业(气象)科研专项(GYHY201006018)共同资助
引用文本:
钱维宏,于甜甜,2013.大气变量物理分解法在极端温度事件前期信号提取中的应用[J].气象,39(6):665-674.
QIAN Weihong,YU Tiantian,2013.Application of Physical Decomposition of Atmospheric Variables to the Prediction of Extreme Temperature Events[J].Meteor Mon,39(6):665-674.