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大气科学  2014 

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

DOI: 10.3878/j.issn.1006-9895.1401.13166

Keywords: BCC_AGCM,月动力延伸,DERF2.0,月预测,预测性能

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Abstract:

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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