基于SEEPS方法的重庆地区降水数值预报性能分析
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摘要
本研究简要介绍了SEEPS方法的具体计算方案,将该方法应用到重庆地区的降水数值预报检验中,对重庆地区常用的3个业务数值模式2017年全年的预报结果进行了检验评估,并对比分析了3个模式降水预报性能的总体差异及时空分布特征.结果表明,综合各个预报时效2017年全年区域平均SEEPS技巧评分的结果, EC模式的降水预报性能最优,其次是SWC-WARMS, CQMFS最差;综合各个预报时效2017年1-12月逐月区域平均的SEEPS技巧评分的结果, SWC-WARMS各月的预报性能均优于CQMFS. SWC-WARMS和CQMFS的降水预报性能在7月和8月总体而言优于EC模式,其余各月均差于EC模式;对于同一区域全年平均的降水数值预报性能, EC模式最优,其次是SWC-WARMS, CQMFS最差.各个模式的SEEPS技巧评分在四川盆地东部偏东地区均存在大值中心. EC模式总体表现出在重庆的东北部偏东地区和中西部偏北地区的SEEPS技巧评分优于重庆的其他地区. SWC-WARMS总体表现出在重庆东南部地区的SEEPS技巧评分优于重庆的其他地区. CQMFS总体表现出在重庆的东南部地区和重庆的中西部偏北地区的SEEPS技巧评分优于其他地区.
This paper gives a brief account of the specific calculation schemes of the SEEPS(stable equitable error in probability space) method, which is applied to the numerical prediction performance analysis of precipitation in Chongqing area. The annual forecast results of three models, which were operationally implemented and commonly used in Chongqing area in 2017, were tested and evaluated, and the overall difference and temporal and spatial characteristics of the three models were compared and analyzed. The results showed that, in general, based on the results of the regional average SEEPS skill score in 2017, the prediction performance of EC model was the best, followed in sequence by SWC-WARMS and CQMFS; and based on the results of the monthly mean SEEPS skill score in 2017, the prediction performance of SWC-WARMS in each month was better than that of CQMFS. The precipitation forecast performance SWC-WARMS and CQMFS in July and August was, as a whole, better than that of the EC model, but was inferior to that of EC in other months. For the average annual precipitation prediction performance of the same region, the EC model was the best, followed in order by SWC-WARMS and CQMFS. The SEEPS skill score of each model had a large-value center in the eastern part of the Sichuan basin. The EC model showed that the SEEPS skill score was generally higher in the northeast-by-east and mid-west-by-north parts of Chongqing than in the other areas of the city. The SWC-WARMS overall showed that the SEEPS skill score in the southeast of Chongqing was higher than in the other areas. The CQMFS overall showed that the SEEPS skills score in the southeast and mid-west-by-north regions of Chongqing was higher than that in the other regions.
This paper gives a brief account of the specific calculation schemes of the SEEPS(stable equitable error in probability space) method, which is applied to the numerical prediction performance analysis of precipitation in Chongqing area. The annual forecast results of three models, which were operationally implemented and commonly used in Chongqing area in 2017, were tested and evaluated, and the overall difference and temporal and spatial characteristics of the three models were compared and analyzed. The results showed that, in general, based on the results of the regional average SEEPS skill score in 2017, the prediction performance of EC model was the best, followed in sequence by SWC-WARMS and CQMFS; and based on the results of the monthly mean SEEPS skill score in 2017, the prediction performance of SWC-WARMS in each month was better than that of CQMFS. The precipitation forecast performance SWC-WARMS and CQMFS in July and August was, as a whole, better than that of the EC model, but was inferior to that of EC in other months. For the average annual precipitation prediction performance of the same region, the EC model was the best, followed in order by SWC-WARMS and CQMFS. The SEEPS skill score of each model had a large-value center in the eastern part of the Sichuan basin. The EC model showed that the SEEPS skill score was generally higher in the northeast-by-east and mid-west-by-north parts of Chongqing than in the other areas of the city. The SWC-WARMS overall showed that the SEEPS skill score in the southeast of Chongqing was higher than in the other areas. The CQMFS overall showed that the SEEPS skills score in the southeast and mid-west-by-north regions of Chongqing was higher than that in the other regions.
引文
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[16] 屠妮妮,衡志炜,吴蓬萍,等.SWCWARMS模式及GRAPES模式对西南区域降水预报检验对比分析 [J].高原山地气象研究,2015,35(4):1-9.
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[18] 陈良吕,吴钲,高松.重庆中尺度集合预报系统预报性能分析 [J].高原山地气象研究,2017,37(4):21-27.
[19] 陈法敬,陈静.“SEEPS”降水预报检验评分方法在我国降水预报中的应用试验 [J].气象科技进展,2015,5(5):6-13.
[2] 王雨,闫之辉.降水检验方案变化对降水检验评估效果的影响分析 [J].气象,2007,33(12):53-61.
[3] 王雨,公颖,陈法敬,等.区域业务模式6 h降水预报检验方案比较 [J].应用气象学报,2013,24(2):171-178.
[4] 张晓惠,谢世友,任伟.1951年-2014年重庆市主城区降水变化特征分析——以沙坪坝区为例 [J].西南大学学报(自然科学版),2016,38(4):104-109.
[5] 吴俞,冯文,李勋,等.ECMWF细网格10 m风场产品在南海海域的预报检验 [J].西南师范大学学报(自然科学版),2015,40(9):204-212.
[6] 戴劲,何宁,袁红松,等.湘潭低空急流暴雨天气分型及雷达回波特征分析 [J].三峡生态环境监测,2018,3(1):47-52.
[7] EBERT E E.Fuzzy Verification of High Resolution Gridded Forecasts:A Review and Proposed Fraework [J].Meteorological Applications,2008,15(1):51-64.
[8] CASATI B.New Developments of the Intensity-Scale Technique within the Spatial Verification Methods Intercomparison Project [J].Weather and Forecasting,2010,25(1):113-143.
[9] DAVIS C,BROWN B,BULLOCK R.Object-Based Verification of Precipitation Forecasts.Part I:Methodology and Application to Mesoscale Rain Areas [J].Monthly Weather Review,2006,134(7):1772-1784.
[10] DAVIS C,BROWN B,BULLOCK R.Object-Based Verification of Precipitation Forecasts.Part II:Application to Convective Rain Systems [J].Monthly Weather Review,2006,134(7):1785-1795.
[11] DAVIS C A,BROWN B G,BULLOCK R,et al.The Method for Object-Based Diagnostic Evaluation (MODE) Applied to Numerical Forecasts from the 2005 NSSL/SPC Spring Program [J].Weather and Forecasting,2009,24(5):1252-1267.
[12] RICHARDSON D S.Skill and Relative Economic Value of the ECMWF Ensemble Prediction System [J].Quarterly Journal of the Royal Meteorological Society,2000,126(563):649-667.
[13] FERRO C A T,STEPHENSON D B.Extremal Dependence Indices:Improved Verification Measures for Deterministic Forecasts of Rare Binary Events [J].Weather and Forecasting,2011,26(5):699-713.
[14] RODWELL M J,RICHARDSON D S,HEWSON T D,et al.A New Equitable Score Suitable for Verifying Precipitation in Numerical Weather Prediction [J].Quarterly Journal of the Royal Meteorological Society,2010,136:1344-1363.
[15] 麻巨慧,朱跃建,王盘兴,等.NCEP、 ECMWF及CMC全球集合预报业务系统发展综述 [J].大气科学学报,2011,34(3):370-380.
[16] 屠妮妮,衡志炜,吴蓬萍,等.SWCWARMS模式及GRAPES模式对西南区域降水预报检验对比分析 [J].高原山地气象研究,2015,35(4):1-9.
[17] 陈良吕,杜钦.SWC-WARMS在重庆地区的降水预报性能分析 [J].高原山地气象研究,2016,36(3):1-6.
[18] 陈良吕,吴钲,高松.重庆中尺度集合预报系统预报性能分析 [J].高原山地气象研究,2017,37(4):21-27.
[19] 陈法敬,陈静.“SEEPS”降水预报检验评分方法在我国降水预报中的应用试验 [J].气象科技进展,2015,5(5):6-13.