FORECAST ERROR ANALYSIS OF EC MODEL FOR HEAVY RAINFALL DURING ANNUALLY FIRST RAINY SEASON IN SOUTH CHINA BASED ON CRA METHOD
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摘要: 利用CRA空间检验技术对ECMWF模式36 h时效预报的2016—2018年华南前汛期(4—6月)69个降水目标进行了检验及误差统计分析，并将预报落区偏差相似个例的环流形势及天气尺度影响系统进行了分析。(1) 87% 的强降水目标存在明显落区预报偏差，最大偏差为2.75 °。偏差以经向偏差为主，其中偏北的目标多于偏南的目标，平均偏北0.6 °；无系统性纬向偏差。(2) 模式预报的降水面积较实况偏大的个例多。(3) 不同降水落区预报偏差类型月份分布、对应的环流特征与天气尺度影响系统具有一定的差异性。4月各偏差类型出现的频次相当，5月以西北型个例为主，6月东北型个例最多。西北型个例天气尺度影响系统以长波槽或东北冷涡、冷式切变线为主，西南型、东北型个例主要受南支波动与中纬度短波槽影响，低层低涡、冷、暖式切变线等出现的频次差不多。通过降水预报落区偏差较大和较小的个例对比分析，表明模式强降水落区预报偏差可能与对流组织化发展程度以及暖区是否存在有利于对流发展条件等有关。Abstract: The present study verified the ECMWF model 36-hour forecast of 69 precipitation events from April to June in 2016—2018 during the annually first rainy season in south China and the forecast error was statistically analyzed by using the contiguous rain area (CRA) spatial verification method. Furthermore, analysis of the circulation situation and synoptic scale system of the cases with similar forecast rainfall location error were carried out. The results showed that: (1) 87% forecasts of the heavy rainfall events have obvious error in rainfall location and the maximum error is 2.75° deviation from the observation. The deviation is dominantly meridional ones, in which cases with north rainfall error are more than the south one, with an average of 0.6° northward deviation to the observation. No obvious zonal deviation is seen. (2) There are many cases where the precipitation area predicted by the model is larger than the observed. (3) The monthly distribution of forecast deviation types in different precipitation areas, the corresponding circulation characteristics and the synoptic influence system show certain differences. In April, the cases of different types show uniform distribution. However, the northwest and northeast types are the main types in May and June, respectively. The synoptic system of the northwest type is dominated by long-wave trough or the northeast cold vortex and cold shear line. The northeast and southwest types are mainly affected by the south branch trough and mid-latitude shortwave trough, while the effect by the vortex, cold and warm shear line are almost the same. Finally, comparative analysis of two cases with large and small rainfall location error indicate that predictability of heavy rainfall depends on the development of organization of convective systems and initiation of convective systems in the warm area, etc.
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图 1 模式降水落区质心位置较实况的偏差频次空间分布(a，单位: °)和69个降水目标实况和预报的强度分布散点图(b~e)
b. 大雨及以上量级的降水格点数；c. 大雨及以上量级的平均降水量(单位：mm)；d. 最大降水量(单位：mm)；e. 区域总降水量(单位：103 mm·m2)。图a数字为预报偏差位于每个0.25 °×0.25 °网格内的CRA个数。
图 7 a. 2017年5月8日08时—9日08时(北京时，下同)24 h累计降水量(等值线为EC预报，填色为实况，单位：mm)；b.同a，但为2018年5月26日08时—27日08时；c.2017年5月8日08时的500 hPa高度场(等值线，单位：dagpm)和925 hPa风场(风向杆)，填色为实况降水(单位：mm)；d.同c，但为2018年5月26日；e. 2017年5月8日08时的CAPE(等值线，单位：J/ kg)和PWAT(填色，单位：mm)；f. 同e，但为2018年5月26日08时。
图 8 a. 2017年5月8日18时沿113 °E的垂直速度(黑色虚线，单位：pa/s)、比湿(蓝色实线，单位：g/kg)、假相当位温(填色，单位：K)和风场(风向杆)经向-高度剖面图；b. 2018年5月26日23时沿106.0 °E，25.2 °N至107.7 °E，22.2 °N的垂直速度(黑色虚线，单位：pa/s)、比湿(蓝色实线，单位：g/kg)、假相当位温(填色，单位：K)和风场(风向杆)剖面图；c. 2017年5月8日18时沿113 °E的小时降水量(单位：mm)；d. 2018年5月26日23时沿106.0 °E，25.2 °N至107.7 °E，22.2 °N的小时降水量(单位：mm)。
表 2 各类预报偏差类型个例的环流形势及天气尺度影响系统“√”符号表示出现某类型环流形势和天气尺度系统，日期160410表示2016年4月9日08时—10日08时。
偏差类型 日期 东亚中岛纬度环流形势 中低纬度环流形势 天气尺度系统 多波动 一槽一脊 南支槽或波动 副高 长波槽或东北冷涡 中纬度短波槽、南支槽或波动 低涡 冷式切变线 暖式切变线 低空急流 西南型 160410 √ √ √ √ √ √ 160413 √ √ √ √ √ √ 160424 √ √ √ √ √ √ 160505 √ √ √ √ √ 160616 √ √ √ √ √ 1S0510 √ √ √ √ √ 西北型 160416 √ √ √ √ √ √ 160418 √ √ √ √ √ 160501 √ √ √ √ √ √ 160507 √ √ √ √ 160508 √ √ √ √ √ √ 160510 √ √ √ √ √ 170515 √ √ √ √ 170524 √ √ √ √ 170626 √ √ √ √ 170627 √ √ √ 170628 √ √ √ 180508 √ √ √ √ √ 180624 √ √ √ 东北型 160411 √ √ √ √ √ √ 160528 √ √ √ √ √ 160606 √ √ √ √ 170425 √ √ √ 170509 √ √ √ √ √ 170604 √ √ √ √ √ √ 170607 √ √ 170617 √ √ √ √ √ √ 170620 √ √ √ 170621 √ √ √ √ √ √ 180613 √ √ √ √ 
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[1] 黄士松. 华南前汛期暴雨[M]. 广州: 广东科技出版社, 1986. [2] 周秀骥, 薛纪善, 陶祖钰, 等'. 98'华南暴雨科学试验研究[M]. 北京: 气象出版社, 2003. [3] 倪允琪, 张人禾, 刘黎平, 等. 中国南方暴雨野外科学试验(SCHeREX)[M]. 北京: 气象出版社, 2013. [4] ZHANG R, NI Y, LIU L, et al. South China Heavy Rainfall Experiments (SCHeREX)[J]. J Meteor Soc Japan, 2011, 89(2): 153-166. [5] LUO Y, ZHANG R, WAN Q, et al. The Southern China Monsoon Rainfall Experiment (SCMREX)[J]. Bull Amer Meteor Soc, 2017, 98(5): 999-1013. [6] WU M W, LUO Y L. Mesoscale observational analysis of lifting mechanism of a warm-sector convective system producing the maximal daily precipitation in China mainland during pre-summer rainy season of 2015[J]. J Meteor Res, 2016, 30(5): 719-736. [7] DU Y, CHEN G X. Heavy rainfall associated with double low-level jets over southern China. Part Ⅰ: Ensemble-based analysis[J]. Mon Wea Rev, 2018, 146(11): 3 827-3 844. [8] 张亚妮, 姚秀萍, 于超. 高层动力强迫对回流型华南暖区暴雨影响的个例研究[J]. 热带气象学报, 2019, 35(2): 166-176 [9] 胡宁, 汪会. 华南一次强对流天气过程中环境条件对MCS形态特征的影响[J]. 热带气象学报, 2019, 35(5): 681-693. [10] 何立富, 陈涛, 孔期. 华南暖区暴雨研究进展[J]. 应用气象学报, 2016, 27(5): 559-569. [11] SUN J H, ZHANG Y C, LIU R X, et al. A review of research on warm-sector heavy rainfall in China[J]. Adv Atmos Sci, 2019, 36(12): 1 299-1 307. [12] 陈茂钦, 徐海明. 江淮锋面和华南暖区两次暴雨过程可预报性对比[J]. 南京信息工程大学学报, 2011, 3(2): 118-127. [13] 孔期, 林建. 2015年5月19—20日华南地区不同性质暴雨成因和预报分析[J]. 气象, 2017, 43(7): 792-803. [14] GILLELAND E, AHIJEVYCH D, BROWN B, et al. Intercomparison of spatial forecast verification methods[J]. Wea Forecasting, 2009, 24(5): 1 416-1 430. [15] EBERT E E, MCBRIDE J L. Verification of precipitation in weather systems: Determination of systematic errors[J]. J Hydrol, 2000, 239(1): 179-202. [16] EBERT E E, GALLUS W A. Toward better understanding of the contiguous rain area (CRA) method for spatial forecast verification[J]. Wea Forecasting, 2009, 24(5): 1 401-1 415. [17] 姜晓曼, 袁慧玲, 薛明, 等. 北京"7.21"特大暴雨高分辨率模式分析场及预报分析[J]. 气象学报, 2014, 72(2): 207-219. [18] DUBE A, ASHRIT R, ASHISH A, et al. Forecasting the heavy rainfall during Himalayan flooding—June 2013[J]. Weather and Climate Extremes, 2014, 4(C): 22-34. [19] 符娇兰, 代刊. 基于CRA空间检验技术的西南地区东部强降水EC模式预报误差分析[J]. 气象, 2016, 42(12): 1 456-1 464. [20] ASHRIT R, EBERT E, MITRA A, et al. Verification of Met Office Unified Model (UM) quantitative precipitation forecasts during the Indian monsoon using the contiguous rain areas (CRA) method[R]. Noida, U.P., India: National Centre for Medium Range Weather Forecasting Ministry of Earth Sciences, Government of India, 2015. [21] SHARMA K, ASHRIT R, EBERT E, et al. NGFS rainfall forecast verification over India using the contiguous rain area (CRA) method[J]. Mausam, 2015, 66, 415-422. [22] SHARMA K, ASHRIT R, EBERT E, et al. Assessment of Met Office Unified Model (UM) quantitative precipitation forecasts during the Indian summer monsoon: Contiguous Rain Area (CRA) approach[J]. J Earth Syst Sci, 2019, 128, 4. doi:10.1007/s12040-018-1023-3. [23] MOISE A F, DELAGE F P. New climate model metrics based on object ‐ orientated pattern matching of rainfall[J]. J Geophys Res, 2011, 116, D12108. [24] CHEN Y, EBERT E E, DAVIDSON N E, et al. Application of contiguous rain area (CRA) methods to tropical cyclone rainfall forecast verifi cation[J]. Earth and Space Science, 2018, 5(11): 736-752. [25] 刘凑华, 曹勇, 符娇兰. 基于变分法的客观分析算法及应用[J]. 气象学报, 2013, 71(6): 1 172-1 182. [26] RODWELL M J, RICHARDSON D S, PARSONS D B, et al. Flow-Dependent Reliability: A Path to More Skillful Ensemble Forecasts[J]. Bull Amer Meteor Soc, 2018, 99(5): 1 015-1 026. [27] 广东省气象局《广东省天气预报技术手册》编写组. 广东省天气预报技术手册2009年修订版[R]. 广东省气象局, 2009. [28] WU D C, MENG Z Y, YAN D C. The predictability of a squall line in South China on 23 April 2007[J]. Adv Atmos Sci, 2013, 30(2): 485-502. [29] 钱维宏, 李进, 单晓龙. 中期模式扰动风在2010年区域暴雨预报中的天气学释用[J]. 中国科学: 地球科学, 2013, 43: 862-873. [30] JIANG N, QIAN W, DU J, et al. A comprehensive approach from the raw and normalized anomalies to the analysis and prediction of the Beijing extreme rainfall on July 21, 2012[J]. Natural Hazards, 2016, 84(3): 1 551-1 567. -
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