2022-2023年黑龙江省1月延伸期强降温过程预报检验  

Forecast and Test of Strong Cooling Process During January Extension Period in Heilongjiang Province from 2022 to 2023

作　　者：王营 李永生[1] 赵佳莹[1] 马舒扬 班晋[1] 宋成玉 王昊 WANG Ying;LI Yong-sheng;ZHAO Jia-ying;MA Shu-yang;BAN Jin;SONG Cheng-yu;WANG Hao(Climate Center of Heilongjiang Province,Heilongjiang Harbin 150036)

机构地区：[1]黑龙江省气候中心,黑龙江哈尔滨150036

出　　处：《黑龙江气象》2023年第2期10-12,24,共4页Heilongjiang Meteorology

摘　　要：利用黑龙江省83个气象观测站2022年和2023年1月的逐日温度资料,以单站日平均温度24 h内降温幅度>8℃为标准,对强降温事件进行统计,并对CFSv2延伸期预报进行检验。结果表明:两年共发生6次强降温过程,发布延伸期强降温过程12次,预报准确率为33%,空报过程10次,漏报4次,2023年预报准确率高于2022年。对比不同预报时效的结果,发现延伸期预报效果与起报时间并没有显著联系。CFSv2模式对大范围强降温过程的预报有一定技巧,超前10 d预报的旬气温距平也具有参考价值,与实况相比,延伸期强降温过程预报的时段和强度略有偏差,但是预报的变化趋势基本一致,可以为黑龙江省1月强降温预报提供参考。Based on the daily temperature data of 83 meteorological observation stations in Heilongjiang Province in January 2022 and 2023,based on the standard that daily average temperature of a single station drops by more than 8℃within 24 hours,statistical analysis is conducted on strong cooling events and compared with the CFSv2 extended period forecast.The results show that there are 6 strong cooling processes in the two years,12 strong cooling processes in the extended period are released,and the forecast accuracy is 33%.The forecast accuracy of 2023 is higher than that of 2022.By comparing the results of different forecasting efficiency,it is found that there is no significant relationship between forecasting effectiveness and start time of forecasting.The CFSv2 model has certain skills for the prediction of large-scale strong cooling process,and the ten-day temperature anomaly predicted by 10 days in advance also has reference value.Compared with the actual situation,the prediction period and intensity of the extended period strong cooling process are slightly different,but the change trend of the prediction is basically the same,which can provide a reference for the January strong cooling forecast in Heilongjiang Province.

关 键 词：延伸期 强降温 模式检验 

分 类 号：P456.7[天文地球—大气科学及气象学]