| MODES系统对贵州月气温、降水预测初步评估 |
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| 引用本文： | 白慧,高辉.MODES系统对贵州月气温、降水预测初步评估[J].新疆气象,2016,10(5):58-63. |
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| 作者姓名： | 白慧 高辉 |
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| 作者单位： | 贵州省气候中心,国家气候中心 |
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| 摘 要： | 通过对2013年1月—2015年6月(MODES)发布的最优月预测产品在贵州省月平均气温距平和降水距平百分率的预测检验评估,发现MODES对全省平均气温有较好的预报,分析时段内预测与实况的相关系数为0.24,距平同号率为65.5%,且对气温偏高预测的可参考性高于其对气温偏低的预测。相比于气温,MODES对降水预测能力较弱,参考性也相对较低,其中对贵州全省平均降水偏多趋势的预测技巧要优于对全省平均偏少趋势的预报技巧。逐站分析显示,MODES对贵州气温预测效果较好的地区在西部、北部和东部,对降水偏多的预测效果较好的地区位于除西北部和北部边缘地区外的其余大部地区。通过对MODES与预报员综合预报的结果评估发现,MODES月预测总体效果较预报员好,且稳定性高于预报员,可为预报员提供参考信息。
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| 关 键 词： | 多模式解释应用集成预测系统（MODES） 距平同号率 Ps评分 检验评估 |
| 收稿时间： | 2015/12/31 0:00:00 |
| 修稿时间： | 2016/3/22 0:00:00 |
Assessment of Multi-model Downscaling Ensemble Prediction System (MODES) for Monthly Temperature and Precipitation Prediction in Guizhou |
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| baihui and gaohui.Assessment of Multi-model Downscaling Ensemble Prediction System (MODES) for Monthly Temperature and Precipitation Prediction in Guizhou[J].Bimonthly of Xinjiang Meteorology,2016,10(5):58-63. |
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| Authors: | baihui and gaohui |
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| Institution: | Guizhou Climate Center,National Climate Center |
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| Abstract: | Based on the outputs of different climate models, National Climate Center of China Meteorological Administration (CMA) established an multi-model downscaling ensemble prediction system (MODES) in 2011. Since then the system has been used widely in the domestic seasonal prediction operation. By assessing and verifying the prediction of MODES for monthly temperature and precipitation in Guizhou province during January 2013 to June 2015, this paper indicates that the system has a good temperature prediction skill in the province. The correlation coefficient and the total ration of same anomaly symbol between MODES and observation are 0.24 and 65.5%. Prediction skill of positive temperature anomaly is higher than the negative anomaly. Compared to temperature prediction, the prediction skill for precipitation in MODES is lower, but the prediction skill of positive precipitation anomaly is higher than the negative anomaly. Spatial distribution of verification results show that the high skill scores appear in the western, northern and eastern part of Guizhou province for temperature, and in most regions for precipitation except in part of northwestern and northern regions. During the research period, the prediction skill scores are stably higher than the scores of the subjective forecasts made by the forecaster, especially for negative temperature anomaly and for positive precipitation anomaly. |
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| Keywords: | Multi-model Downscaling Ensemble Prediction System (MODES) ratio of the same anomaly symbol Ps score assessment and verification |
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