[1]张东方,成青燕,何慧根,等.CFSv2模式资料在成都市延伸期降水预测中的应用评估[J].气象研究与应用,2021,42(02):1-6.[doi:10.19849/j.cnki.CN45-1356/P.2021.2.01]
　Zhang Dongfang,Cheng Qingyan,He Huigen,et al.Application and evaluation of CFSv2 model data in extended precipitation forecast of Chengdu[J].Journal of Meteorological Research and Application,2021,42(02):1-6.[doi:10.19849/j.cnki.CN45-1356/P.2021.2.01]
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CFSv2模式资料在成都市延伸期降水预测中的应用评估()
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气象研究与应用[ISSN:1673-8411/CN:45-1356/P]

卷:
第42卷
期数:
2021年02期
页码:
1-6
栏目:
研究论文
出版日期:
2021-07-06

文章信息/Info

Title:
Application and evaluation of CFSv2 model data in extended precipitation forecast of Chengdu
作者:
张东方1;  成青燕1; 2;  何慧根3;  杨蓉1;  韦玮1;  汪玲1
1. 成都市气象局, 成都 611133;
2. 高原与盆地暴雨旱涝灾害四川省重点实验室, 成都 611133;
3. 重庆市气候中心, 重庆 401147
Author(s):
Zhang Dongfang1;  Cheng Qingyan1; 2;  He Huigen3;  Yang Rong1;  Wei Wei1;  Wang Ling1
1. Chengdu Meteorological Bureau, Chengdu 611133;
2. Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Chengdu 611133;
3. Chongqing Climate Center, Chongqing 401147
关键词:
CFSv2模式; 延伸期降水预测; 应用检验
Keywords:
CFSv2 model; extended precipitation forecast; test of application
分类号:
P456
DOI:
10.19849/j.cnki.CN45-1356/P.2021.2.01
摘要:
将CFSv2模式的延伸期预测资料应用于成都市14个国家站的延伸期降水预测，采用距平相关系数ACC、趋势异常综合检验Ps及Cs/Zs评分对2016年1月至2020年12月的预测回算进行预测效果评估，通过改进的消除偏差一元线性回归方法对模式预测进行订正和预测再回算、再评估。结果表明，CFSv2的延伸期预测与成都地区实际降水的ACC为0.13，略高于目前省级和国家级发布的月预测平均成绩，对成都西南部和东南部的预报效果较好； Ps评分平均为65.7分；期间主要降水过程的Cs评分为0.48，Zs评分为0.64，空报率为38%，漏报率为34%。经过订正后，预测效果的空间差异无明显变化，ACC提高0.04，Ps评分提高4.3分，Cs评分提高0.05分，Zs评分提高0.14分，空报率降低22%，漏报率降低5%，预测准确率明显提升。
Abstract:
The prediction data of the extended prediction model of the US Environmental Weather Center (CFSv2) was used in the extended precipitation prediction of 14 national stations in Chengdu by using the bilinear interpolation method. After re-calculate from January 2016 to December 2020, the prediction effect of the model itself was comprehensively evaluated and contrast with the simultaneous observation data by using Anomaly Correlation Coefficient (ACC), tendency anomaly evaluation scores(Ps), and the Cs/Zs score. Then the model prediction was revised by using the rolling linear regression method, and the prediction was re-calculated and re-evaluated. The results showed that ACC between the CFSv2 prediction data and the actual precipitation in Chengdu was 0.13, which was equivalent to the current prediction issued by the provincial and national level. It was more accurate on the southwest and southeast of Chengdu. The averages PS score was 65.7, the score of Cs was 0.48, and the score of Zs was 0.64. The empty forecast rate was 38%, and the missing forecast rate was 34%. After the revision, there was no significant change in the predicted spatial differences, the ACC increased 0.04, the Ps score increased by 4.3 points, the score of Cs increased by 0.05 points, the score of Zs increased by 0.14 points, the empty forecast rate decreased by 22%, and the missing forecast rate decreased by 5%. The prediction accuracy rate improved significantly.

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备注/Memo

备注/Memo:
收稿日期:2021-04-15。
基金项目:高原与盆地暴雨旱涝灾害四川省重点实验室开放基金青年专项（SCQXKJQN2019027）、成都市气象局业务技术科研课题短平快项目（2017-2018-2）
作者简介:张东方(1985-),男,工程师,主要从事天气预报及气候相关业务和科研工作。
通讯作者:成青燕(1985-),女,高级工程师,主要从事气候相关综合决策业务和科研工作。E-mail:chqy0810@163.com
更新日期/Last Update: 1900-01-01