| 月动力延伸预测模式业务系统DERF2.0对中国气温和降水的预测性能评估 |
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| 引用本文： | 何慧根,李巧萍,吴统文,唐红玉,胡泽勇.月动力延伸预测模式业务系统DERF2.0对中国气温和降水的预测性能评估[J].大气科学,2014,38(5):950-964. |
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| 作者姓名： | 何慧根 李巧萍 吴统文 唐红玉 胡泽勇 |
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| 作者单位： | 1.重庆市气候中心, 重庆401147;中国科学院寒旱区陆面过程与气候变化重点实验室, 兰州730000 |
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| 基金项目： | 国家重点基础研究发展计划（973 计划）“气候变暖背景下我国南方旱涝灾害的变化规律和机理及其影响与对策”2013CB430204，国家科技支撑项目“持续性异常气象事件预测业务技术研究”2009BAC51B01，中国科学院寒旱区陆面过程与气候变化重点实验室开放基金LPCC201202，中国气象局气象关键技术集成与应用面上项目CMAGJ2013M40，重庆市气象局业务技术攻关面上项目ywgg-201311 |
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| 摘 要： | 基于国家气候中心第二代月动力延伸预测模式业务系统（DERF2.0）开展的1982～2010 年的回报试验结果和国家气象信息中心提供的669 个台站气象观测资料，利用距平相关系数ACC、平均方差技巧评分MSSS、距平符号一致率R 和短期气候预测业务分级检验Pg 等4 种方法综合评估了DERF2.0 系统对中国的气温和降水的预测性能。结果表明，DERF2.0 模式对气温的总体预测效果较好，对气温的预测性能较DERF1.0 模式有了较明显的提升。与过去全国的短期气候预测业务评分相比，DERF2.0 对气温和降水的预测都有所提高。与气温相比，DERF2.0对降水的预测性能相对较差，对降水的预测水平与DERF1.0 相接近。DERF2.0 对发生在1998 年和2006 年的极端旱、涝个例年也有一定的预测能力，且对气温的预测明显好于降水。从空间上来看，DERF2.0 在西南地区的确定性预测效果较差，模式仍然有很大的改进空间。
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| 关 键 词： | BCC_AGCM 月动力延伸 DERF2.0 月预测 预测性能 |
| 收稿时间： | 5/2/2013 12:00:00 AM |
| 修稿时间： | 2014/1/24 0:00:00 |
Temperature and Precipitation Evaluation of Monthly Dynamic Extended Range Forecast Operational System DERF2.0 in China |
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| HE Huigen,LI Qiaoping,WU Tongwen,TANG Hongyu and HU Zeyong.Temperature and Precipitation Evaluation of Monthly Dynamic Extended Range Forecast Operational System DERF2.0 in China[J].Chinese Journal of Atmospheric Sciences,2014,38(5):950-964. |
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| Authors: | HE Huigen LI Qiaoping WU Tongwen TANG Hongyu and HU Zeyong |
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| Institution: | 1.Chongqing Climate Center, Chongqing 401147;Key Laboratory for Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou 7300002.National Climate Center, Beijing 1000813.Chongqing Climate Center, Chongqing 4011474.Key Laboratory for Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou 730000 |
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| Abstract: | On the basis of the data of 669 observed weather stations supplied by the National Meteorological Information Center and hindcast data of the National Climate Centre second-generation monthly Dynamic Extended Range Forecast operational system (DERF2.0) from 1982 to 2010, temperature and precipitation in the prediction performance were evaluated and analyzed by using the anomaly correlation coefficient (ACC), mean square skill score (MSSS), anomaly sign consistency rate (R), and short-term climate prediction operational grading evaluation scores (Pg). The results indicated that the temperature prediction performance of DERF2.0 was significantly better than that of the DERF1.0 operational system in current usage and that the ACC skill score of temperature was noticeably higher than the operational score of the short-range climate forecast. Compared with temperature, the precipitation prediction performance of DERF2.0 was relatively poor. The ACC skill score of precipitation of DERF2.0 was close to that of DERF1.0. DERF2.0 was somewhat skillful in extreme drought and flood years such as 1998 and 2006. Furthermore, the prediction performance of temperature was significantly better than that of precipitation in extreme drought and flood years. From space, the prediction performance of DERF2.0 on the deterministic prediction was poor in the southwest. Thus, DERF2.0 should be improved. |
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| Keywords: | BCC_AGCM Monthly dynamic extended range forecast DERF2 0 Monthly prediction Prediction performance |
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