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Comparison of Two Verification Methods for 6 h Precipitation Forecasts of Regional Models
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摘要: 对我国华东、华南、华北区域气象中心和中国气象局数值预报中心业务运行的区域模式2011年5—9月的6 h降水预报, 采用不同检验结果平均方案进行对比检验。对比结果表明：不同的检验结果平均方案基本不影响与中国气象局数值预报中心模式 (NMC-GRA) 在相同区域关于TS评分比较的相对检验结论，即当两个模式评分差距较大时，评分高的模式在两个方案中是一样的，但评分比较接近时，若有一个模式对该区大尺度降水预报较好时，则可能在新方案中有较高的TS评分，而此模式原方案评分则可能略低于局地小尺度降水预报较好的模式。但对于较少发生的强降水预报的预报偏差的评价有很大不同，当新方案的结果显示多数模式对强降水的预报偏少，原方案则可能显示偏多，说明模式对大尺度的强降水预报较实况偏少，但对小尺度局地降水的预报则可能偏多。Abstract: 6 h precipitation forecast for different lead times of operational models for North China Regional Center, South China Regional Center, East China Regional Center and Numerical Weather Prediction Center of CMA (NWPC) are verified and compared from May to September in 2011. The two methods which are used to average verification results for some period are discussed in detail.The verification results show the forecasting performance is different according to the observational time, the forecasting lead time and coverage area of models. Compared with NWPC GRAPES_Meso model in the same area, the performance for most lead times of operational models of three regional centers is better, particularly for over 24 h lead time forecast. Furthermore, verification score of East China Regional Center model is the best, TS of this model is higher than that of NWPC model except that 0.1 mm or more precipitation of 18 h forecast with 0600 UTC observation and 24 h forecast with 1200 UTC observation, and the bias is close to 1 for most verification grades. Moreover, TS of intense precipitation of three Regional Centers models is higher than that of NWPC model most of the time, but TS of North China regional center model is lower for 6 h and 18 h forecast with 0600 UTC observation and for 6 h forecast with 1800 UTC observation. On the other hand, the verification results derived from the different averaging approaches have few impacts on TS comparison results for regional model and NWPC model, but the TS value by new method is higher than that of the former method, except when the difference of TS between the two models is very small. For the new method, the model performs better for the large-scale rainfall process perhaps getting higher TS than the model that is only good at meso-scale rainfall. But the difference for heavy rain with little probability, especially for precipitation heavier than 13 mm is significant. If there is more false alarms for the forecast of greater grades small meso-scale precipitation, and there is some missing for the large scale rainfall, the differences between the two methods will be larger. Under this condition, the bias of the new method shows that forecast rainfall is less obviously comparing with observation, but that of the former method indicates more. Such situation usually occurs in North China. Because the two averaging approaches show distinct differences, more studies are needed so that users can understand the differences better and make a correct decision on how to use the forecasts of models properly.
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图 1 不同区域中心12:00 6 h观测降水概率及与该观测对应的GRAPES_Meso在各区域中心模式范围24 h降水预报TS评分
Fig. 1 The 6 h rainfall probability for 1200 UTC observation and corresponding TS of GRAPES_Meso rainfall forecast against 24 h forecast in different regional centers
图 2 2011年5—9月华北模式 (简称BJ-WRF) 与中国气象局数值预报中心模式 (简称NMC-GRA)6 h降水检验
Fig. 2 The 6 h rainfall forecast verification results for model of North China Regional Center (BJ-WRF) and model of Numerical Weather Prediction Center of CMA (NMC-GRA) from May to September in 2011
图 3 2011年5—9月华南模式 (简称GZ-GRA) 与中国气象局数值预报中心模式 (简称NMC-GRA)6 h降水检验
Fig. 3 The 6 h rainfall forecast verification results for model of South China Regional Center (GZ-GRA) and model of Numerical Weather Prediction Center of CMA (NMC-GRA) from May to September in 2011
图 4 2011年5—9月华东模式 (简称SH-WRF) 与中国气象局数值预报中心模式 (简称NMC-GRA)6 h降水检验
Fig. 4 The 6 h rainfall forecast verification results for model of East China Regional Center (SH-WRF) and model of Numerical Weather Prediction Center of CMA (NMC-GRA) from May to September in 2011
表 1 各区域中心模式参数表
Table 1 The model parameter table of different regional center
区域中心 业务模式 同化系统 资料应用 检验区域及分辨率 物理过程说明 预报时效/h 华北 WRF2.2 3DVAR 地面、探空、
GPS，GTS33.89°~45.5°N，
107.19°~125.1°E,
水平9 km, 垂直37层WSM6, YSU, Kain-
Frainch72 华东 WRF3.1 ADAS同化
技术地面探空、雷达、
卫星、船舶浮标、小球
测风、飞机报21°~45°N，
102°~132°E，
水平9 km, 垂直35层WSM6，RTTM，
Dudhia, PBL, NOAH72 华南 GRAPES_
TMM3DVAR 地面、船舶、探空、
BOGUS，ATOVS
和云导风等11.2°~33.76°N，
97.4°~128.84°E，
水平0.36°，垂直
31层，顶高28.5 kmWSM6，RRTM，
ECMWF，M-O相似理论，
MRF，SLAB，KFETA120 数值预报中心 GRAPES_
Meso3.03DVAR 地面探空 15°~65°N，70°~
145°E, 水平0.15°，垂直
31层, 顶高20 kmWSM6，RRTM，Dudhia，
Monin-Obukhov，
Noah，MRF，BM60 
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表 2 不同观测时次各区域中心模式覆盖的有效观测站数及检验站表站数
Table 2 The number of verification stations and valid observational station of four times for different regional center models
区域 华北 华东 华南 全国 00：00有效观测站数 322~700 1312~1753 746~1082 1618~2111 06：00有效观测站数 717~720 1915~1965 1169~1220 2334~2385 12：00有效观测站数 716~720 1909~1965 1164~1220 2329~2385 18：00有效观测站数 179~181 592~595 399~401 825~827 检验站表站数 751 2070 1298 2510
下载: 导出CSV
表 3 降水检验公式分量定义
Table 3 The contingency table of rainfall verification
实况 预报 有 无 有 h m 无 f c
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[1] 王雨, 李莉.GRAPES_MESO V3.0模式预报效果检验.应用气象学报, 2010, 21(5):524-533. doi: 10.11898/1001-7313.20100502 [2] David A Olson, Norman W Junker, Brian Korty. 美国国家气象中心33年定量降水预报的评估. 林明智, 彭广, 译. 气象科技, 1996, 24(4): 12-22. [3] 陈明轩, 俞小鼎, 谭晓光, 等.对流天气临近预报技术的发展与研究进展.应用气象学报, 2004, 15(4):754-766. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20040693&flag=1 [4] 矫梅燕, 龚建东, 周兵, 等.天气预报技术的业务技术进展.应用气象学报, 2006, 17(5):594-601. doi: 10.11898/1001-7313.20060502 [5] 王改利, 刘黎平, 阮征.多普勒雷达资料在暴雨临近预报中的应用.应用气象学报, 2007, 18(3):388-395. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070363&flag=1 [6] Urs Germann, Isztar Zawadzki. Scale-dependence of the predictability of precipitation from continental radar images. Part I: Description of the methodology. Mon Wea Rev, 2002, 130(12):2859-2873. doi: 10.1175/1520-0493(2002)130<2859:SDOTPO>2.0.CO;2 [7] 陈德辉, 杨学胜, 张宏光, 等.多尺度非静力通用模式框架的设计策略.应用气象学报, 2003, 14(4):452-461. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20030456&flag=1 [8] 陈德辉, 沈学顺.新一代数值预报系统GRAPES的研究进展.应用气象学报, 2006, 17(6):773-777. doi: 10.11898/1001-7313.20060614 [9] 胡江林, 沈学顺, 张宏亮, 等.GRAPES模式动力框架的长期积分特征.应用气象学报, 2007, 18(3):276-284. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20070349&flag=1 [10] 陈峰峰, 王光辉, 沈学顺, 等.Cascade特征量法在GRAPES模式中的应用.应用气象学报, 2009, 20(2):164-170. doi: 10.11898/1001-7313.20090205 [11] 彭新东, 李兴良.多尺度大气数值预报的技术进展.应用气象学报, 2010, 21(2):129-138. doi: 10.11898/1001-7313.20100201 [12] 王雨.降水检验方案变化对降水检验评估效果的影响分析.气象, 2007, 33(12):53-61. doi: 10.7519/j.issn.1000-0526.2007.12.008 [13] Betts A K.A new convective adjustment scheme.Part I: Observational and theoretical basis.Quart J Roy Meteor Soc, 1986, 112:677-691. doi: 10.1002/qj.49711247307/full [14] Betts A K, Miller M J.A new convective adjustment scheme. Part Ⅱ:Single column tests using GATE wave, BOMEX, ATEX and arctic air-mass data sets.Quart J Roy Meteor Soc, 1986, 112:693-709. doi: 10.1002/qj.49711247308/pdf [15] Betts A K, Miller M J.The Betts-Miller Scheme.The Representation of Cumulus Convection in Numerical Models, Meteor Monogr, Amer Meteor Soc, 1993, 24(46):107-121. doi: 10.1007/978-1-935704-13-3_9 [16] Kain J S, Fritsch J M.A one-dimensional entraining/detraining plume model and its application in convective parameterization.J Atmos Sci, 1990, 47:2784-2802. doi: 10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2 [17] Kain J S, Fritsch J M.Convective Parameterization for Mesoscale Models:The Kain-Fritsch Scheme.The Representation of Cumulus Convection in Numerical Models, Meteor Monogr, Amer Meteor Soc, 1993, 24(46):165-170. doi: 10.1007/978-1-935704-13-3_16 -
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