| MDERF产品在贵州月气候预测中的释用 |
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| 引用本文： | 严小冬,古书鸿,吴战平.MDERF产品在贵州月气候预测中的释用[J].气象科学,2009,29(6):804-809. |
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| 作者姓名： | 严小冬 古书鸿 吴战平 |
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| 作者单位： | 贵州省气象局,贵阳,550002 |
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| 基金项目： | 中国气象局多轨道业务建设项目"气候模式产品在成都区域气候预测业务中的应用";贵州省气象局2007年业务技术体制改革项目"动力模式产品释用业务系统"、贵州国际合作重点项目 |
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| 摘 要： | 基于MDERF(Monthly Dynamic Extension Range Forecast)模式输出500hPa位势高度场资料和贵州各月干旱综合指数、降水和气温等历史样本,利用秩序回归降尺度法,研究该方法对贵州月干旱综合指数、降水和气温的预报技巧和预测效果.结果表明:该方法从穷尽所有因子组合中选出彼此独立的3个最佳组合因子共同作为预报因子,从而增强可预报性;模型5 a回报试验和2007年8月试报结果表明该方法在实际预测业务中的应用潜力;各气候要素多年的距平相关系数评分比较稳定,其中月干旱综合指数、降水距平百分率、气温距平全年平均距平相关系数评分分别为0.14、0.15和0.14;各气候要素中月气温预报的Pc最高,平均为73%.综合分析表明,该方法在月动力延伸预报产品对贵州月气候要素预测释用中具有较好的应用前景.
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| 关 键 词： | 秩序回归 MDERF产品 月气候预测 |
| 收稿时间： | 3/3/2008 12:00:00 AM |
The application of the MDERF product to Guizhou month climate forecast |
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| Yan Xiaodong,Gu Shuhong and Wu Zhanping.The application of the MDERF product to Guizhou month climate forecast[J].Scientia Meteorologica Sinica,2009,29(6):804-809. |
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| Authors: | Yan Xiaodong Gu Shuhong and Wu Zhanping |
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| Abstract: | Based on the 500 hPa geo-potential height field, which is the output data of the monthly dynamical extension range forecast (MI)ERF) model, and the drought composite index, precipitation and temperature of the monthly data in Guizhou province, the rank regression downscaling method has been used to forecast drought, precipitation and temperature in Guizhou. The results show that the method can elect independent optimal combination of three factors from all the possible combinations of factors as a pre-diction factor, in order to enhance predictability. The five years result of the model experiment and the forecast test of Guizhou climate factors in August 2007 show that the method has the potential application in the prediction business. All of the climate factors in many years had the stable Acc grade, drought composite index, anomaly precipitation percentage and temperature anomalies correlation coefficients amount to 0. 14, 0. 15 and 0. 14, respectively. The month temperature forecast Pc in the entire climate factors had the highest score, and the average score is 73 percent. The analyses show that the application of the rank regression in the MDERF product to expound and apply the Guizhou month climate forecast has good prospects. |
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| Keywords: | Rank regression MDERF products Monthly climate forecast |
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