摘要
使用2014年5~12月西南四省(区)一市每日08时统计的24h雨量观测资料,对SWCWARMS和GRAPES模式降水进行站点统计检验。主要结论为:针对每日08时起报,SWCWARMS模式除24h中雨和48h大暴雨外SWCWARMS模式ETS评分在其它时次及其它量级降水上均高于GRAPES模式,但SWCWARMS模式空报和系统偏差较多;针对每日20时起报,SWCWARMS模式ETS和TS评分均高于GRAPES模式;除小雨外SWCWARMS模式空报率略高于GRAPES模式。从2014年10次西南涡过程统计检验可见,两模式对强降水过程即主要影响贵州的三次过程评分高于四川和云南的西南涡降水过程,24h降水评分在多个时次多个量级上优于GRAPES模式。SWCWARMS模式在汛期表现优于GRAPES模式,SWCWARMS模式对小雨、中雨和大雨有较强的预报能力,但对强降水预报能力有待改进,对中雨及以上量级降水空报率较高,而对小雨漏报多于GRAPES模式。
Precipitation forecast from SWCWARMS model and GRAPES model are verified and compared by using 24 hour observation precipitation data from May to December in 2014 in southwest China. The verification results show that : according to the forecasting begin time at 08 AM, the ETS scores of SWCWARMS model expert 24h moderate rain grade and 48h heavy rain grade are higher than the GRAPES model, but SWCWARMS model have more empty forecast rate and system deviation; according to the forecasting begin time at 20 PM, the ETS and TS scores of SWCWARMS model are higher than those in GRAPES mode; the vacancy rate of SWCWARMS mode is slightly higher than that of GRAPES model except light rain score. From the verification of the ten southwest vortex in 2014, two model have better prediction ability to the strong rainfall process, the 24h precipitation verification of SWCWARMS model is better than GRAPES model in multiple times and multiple orders of precipitation magnitude. SWCWARMS model performs better than the GRAPES model in the flood season, SWCWARMS model has a strong ability of light rain, moderate rain and heavy rain prediction, but the heavy rainfall prediction ability needs to be improved, and SWCWARMS model has more precipitation vacancy rate to moderate rain and above level, and predict light rain missing more than GRAPES model.
出处
《高原山地气象研究》
2015年第4期1-9,共9页
Plateau and Mountain Meteorology Research
基金
973项目(2012CB417202)