| MOS方法在动力延伸期候平均气温预报中的应用 |
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| 引用本文： | 陈豫英,陈楠,王素艳,邵建,穆建华,纳丽.MOS方法在动力延伸期候平均气温预报中的应用[J].应用气象学报,2011,22(1):86-95. |
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| 作者姓名： | 陈豫英 陈楠 王素艳 邵建 穆建华 纳丽 |
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| 作者单位： | 1.宁夏气象防灾减灾重点实验室，银川 750002 |
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| 基金项目： | 国家自然科学基金，宁夏回族自治区科技攻关项目 |
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| 摘 要： | 利用1982年1月-2010年3月动力延伸预报产品及宁夏候平均气温,采用逐步回归的MOS统计方法,预报宁夏24个测站未来40 d逐候平均气温,为了对比模式直接输出结果与资料按月和按季节划分建立的MOS方法预报效果,对2009年和2010年1-3月的预报效果分别进行了对比检验.结果表明:MOS预报效果较模式直接输出有显著...
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| 关 键 词： | MOS方法 动力延伸预报 候平均气温 效果评估 |
| 收稿时间： | 2010-05-12 |
Application of MOS Method on Pentad Mean Temperature Prediction in Dynamical Extended Range |
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| Chen Yuying,Chen Nan,Wang Suyan,Shao Jian,Mu Jianhua and Na Li.Application of MOS Method on Pentad Mean Temperature Prediction in Dynamical Extended Range[J].Quarterly Journal of Applied Meteorology,2011,22(1):86-95. |
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| Authors: | Chen Yuying Chen Nan Wang Suyan Shao Jian Mu Jianhua and Na Li |
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| Affiliation: | 1.Key Laboratory for Meteorological Disaster Prevention and Reduction of Ningxia, Yinchuan 7500022.Ningxia Meteorological Observatory, Yinchuan 750002 |
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| Abstract: | Stepwise regression MOS statistical method is applied to predict the pentad mean temperature of future 40 days at 24 weather stations in Ningxia, using the pentad mean temperature and dynamical extended range forecasting products from January 1982 to March 2010. In order to evaluate the predicting capability of the direct numerical model output products (DMO) and MOS which use the seasonal and monthly data, the prediction results of DMO and MOS from January to March in 2009 and 2010 are compared.The prediction accuracy and stability of MOS improved remarkably comparing with DMO, MOS method can predict the trend and extent of violent weather changes in temperature. With the drawing near of predicting time and successive correction, its prediction error values decreases gradually, and predicting results can be for the reference of medium term prediction operation.MOS prediction capability is different when using data of different lengths. The prediction capability of MOS using monthly data is better, because the chosen prediction factors using monthly data can better indicate the correlation of prediction objects in this period, and its physical meaning is much distinct. So more monthly data samples lead to better temperature prediction result and stability.MOS method merely applies the output products of dynamical extended range prediction model, so its prediction results thoroughly rely on the accuracy and stability of numerical prediction model. The prediction results may be more accurate if some observation factor, local experimental factor and climatic factor are added. There are 4 aspects which need attentions when establishing MOS equations: The equations should be established based on experimental calculating error values; the establishment of F-test value at each weather station should also consider experimental calculating error values; using data samples of longer temporal scales to verify if MOS prediction results will be better using more monthly data samples; finally, more new data are recommended to improve MOS prediction capability in the future. |
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| Keywords: | MOS method dynamical extended range prediction model pentad mean temperature evaluation of prediction capability |
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