| 区域随机动力统计气候模式及其预报试验 |
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| 引用本文： | 黄嘉佑,宋玉梅,王绍武.区域随机动力统计气候模式及其预报试验[J].气象学报,1993,51(3):315-324. |
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| 作者姓名： | 黄嘉佑 宋玉梅 王绍武 |
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| 作者单位： | 北京大学地球物理系 100871
(黄嘉佑)，北京大学地球物理系 100871中国气象学会
(宋玉梅)，北京大学地球物理系 100871(王绍武) |
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| 摘 要： | 本文从大气热力学与动力学原理出发,设计并推导了一个以高度场和海温场为主要变量的多网格点的海气耦合随机动力模式,用此模式作500hPa平均高度场的预报试验。预报以春季月份(2月)为初始场,取西太平洋副热带高压活动地区(10°N-40°N,110°E-170°W)6月500hPa高度场作为预报场。另外取赤道东太平洋地区5°S—10°S范围内海温场作为耦合场,把该模式中的微分方程组化为差分形式,以前期月平均高度场和海温场为初始场,以时间步长1天进行积分,积分系数是用依赖资料(1951—1980年)反演估计出来的,然后对独立样本(1981—1986年)作预报试验。方程中的随机项假设为白噪音,并对不同的白噪音量级作了一系列试验。结果表明,加上白噪音的效果均比未加时要好,说明次要因素的随机作用在海气相互作用中是不可忽视的。
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| 关 键 词： | 随机气候模式 动力统计预报 西太平洋副热带高压 |
| 收稿时间： | 5/6/1991 12:00:00 AM |
| 修稿时间： | 1991/8/19 0:00:00 |
A LOCAL STOCHASTIC DYNAMIC CLIMATIC MODEL AND ITS FORECASTING EXPERIMENTS |
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| Huang Jiayou,Song Yumei and Wang Shaowu.A LOCAL STOCHASTIC DYNAMIC CLIMATIC MODEL AND ITS FORECASTING EXPERIMENTS[J].Acta Meteorologica Sinica,1993,51(3):315-324. |
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| Authors: | Huang Jiayou Song Yumei and Wang Shaowu |
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| Institution: | Department of Geophysics, Peking University, Beijing 100871;Department of Geophysics, Peking University, Beijing 100871;Department of Geophysics, Peking University, Beijing 100871 |
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| Abstract: | In this paper, a multiple-grid aia-sea coupled stochastic dynamic model whose main variables are height field and sea temperature field is designed and deduced according to the principles of dynamics and thermeodynamics of the atmosphere, moreover, and used for forecasting experiments on 500hPa height field. The integral coefficients in this model are valued out by inversion from historical data, and the samples of the forecasting experiments are independent. Presuming the stochastic terms in the equations to be white noises, a series of tests on different orders of magnitude of white noises is performed. The results-show that the model is more efficient when it adds white noises than it doesn't, which means that the stochastic effects of secondary factors in the process of air-sea interaction should not be ignored. This model is of certain forecasting ability and suitable for long-term forecast to atmospheric elements in local districts. |
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| Keywords: | Stochastic climatic model Statistical-dynamical prediction subtropical high of the west Pacific |
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