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齐铎, 崔晓鹏, 陈力强, 黄丽君, 刘松涛, 卜文慧, 王承伟. 基于主客观环流分型的强降水数值预报MODE检验——方法及其在2019年暖季东北地区的应用[J]. 大气科学. DOI: 10.3878/j.issn.1006-9895.2210.22107
引用本文: 齐铎, 崔晓鹏, 陈力强, 黄丽君, 刘松涛, 卜文慧, 王承伟. 基于主客观环流分型的强降水数值预报MODE检验——方法及其在2019年暖季东北地区的应用[J]. 大气科学. DOI: 10.3878/j.issn.1006-9895.2210.22107
Evaluation of heavy rainfall numerical prediction based on subjective and objective circulation classification as well as method for object-based diagnostic evaluation ——method and its application over Northeast China during the warm season of 2019[J]. Chinese Journal of Atmospheric Sciences. DOI: 10.3878/j.issn.1006-9895.2210.22107
Citation: Evaluation of heavy rainfall numerical prediction based on subjective and objective circulation classification as well as method for object-based diagnostic evaluation ——method and its application over Northeast China during the warm season of 2019[J]. Chinese Journal of Atmospheric Sciences. DOI: 10.3878/j.issn.1006-9895.2210.22107

基于主客观环流分型的强降水数值预报MODE检验——方法及其在2019年暖季东北地区的应用

Evaluation of heavy rainfall numerical prediction based on subjective and objective circulation classification as well as method for object-based diagnostic evaluation ——method and its application over Northeast China during the warm season of 2019

  • 摘要: 本文构建了基于主客观环流分型的强降水数值预报空间检验(MODE)方法框架,并利用该框架对欧洲中期天气预报中心全球模式(ECMWF)和中国气象局区域中尺度数值天气预报模式(CMA_MESO)的2019年暖季东北地区强降水预报进行检验。结果表明:2019年暖季东北地区54个强降水日的环流型可分为:西风槽型(15个)、副高影响型(13个)、急流型(5个)、西部(12个)和东部冷涡型(9个)。其中,西风槽型和急流型以区域性强降水为主,模式对其强降水发生与否的预报能力强,TS评分较高;西部、东部冷涡型强降水的局地性强,模式对其强降水发生与否的预报能力差,TS评分低;副高影响型也以区域性强降水为主,模式对其强降水发生与否的预报能力也比较强,但是对其强降水质心位置、强度、面积等属性预报偏差较大,TS评分也相对较低。另外,从两种模式预报性能对比看,CMA_MESO对强降水强度和面积预报较实况普遍偏强,虽然其预报的TS评分一般高于ECMWF,但其对强降水预报的空报率也都比ECMWF大,对强降水的属性预报偏差一致性一般也低于ECMWF,其预报的可订正性整体上不及ECMWF。

     

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