西南区域中心模式SWC-WARMS降水偏差分析
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摘要
本文利用2014—2015年5—10月12(24)h累积降水资料和西南区域模式(SouthWest Center WRF ADAS Real-time Modeling System,SWC-WARMS)36(72 h)预报时效内降水预报资料,从概率和频次角度分析不同海拔高度地区观测和模式降水在量级及空间分布上的特征差异。结果表明,SWC-WARMS模式各预报时效各量级降水的概率密度均比观测偏大,并向10 mm以下雨量集中,且随预报时效延长偏大更显著;模式与观测降水的概率密度曲线差异在盆地小于高原,地形差异小的区域小于地形差异大的区域。SWC-WARMS模式对四川地区降水预报存在雨日较观测明显偏多,量级偏大,降水频次高值区范围偏大、出现虚假高值区等系统性偏差。此外,模式预报在20—08时比08—20时优,24 h累积降水预报优于12 h降水预报,尤以中雨及以上量级降水落区预报为甚。最后,模式极端强降水预报在20—08、20—20时较实况偏大,08—20时,模式预报在盆地较实况偏小,川西高原和攀西地区偏大。
In this paper, using the 12(24 h) cumulative precipitation data from May to October during 2014—2015 and the SWC-WARMS forecast precipitation data within 36(72 h), the characteristic differences in precipitation intensity and spatial distribution between the observed and model precipitations in different altitude areas from the perspective of probability and frequency were analyzed. The results show that the probability density of forecast precipitation by the SWC-WARMS model is higher than that of observations in any forecast time, and the precipitation is concentrated below 10 mm. What's more, with the extension of forecast time, the wet deviation of model predicts is more significant. The difference of probability density curve in basin is smaller than that in plateau, and the difference of probability density curve in the area with small terrain difference is less than that in the area with large terrain difference. The precipitation forecast by SWC-WARMS model has many deviations, including more rainy days, higher precipitation intensity, large area with high precipitation frequency, and false high value areas. In addition, the SWC-WARMS model forecast at night(20—08) is better than daytime(08—20), and the 24 h cumulative precipitation forecast is superior to the 12 h cumulative precipitation forecast, especially in the forecast of precipitation areas with the moderate rain and above. At last, the extreme heavy precipitation forecasted by the model in the 20—08 period and 20—20 period is heavier than the actual precipitation. In terms of regions, the model predications are lower than the actual situation in basin, but higher in the Western Sichuan Plateau and the Panzhihua-Xichang region.
In this paper, using the 12(24 h) cumulative precipitation data from May to October during 2014—2015 and the SWC-WARMS forecast precipitation data within 36(72 h), the characteristic differences in precipitation intensity and spatial distribution between the observed and model precipitations in different altitude areas from the perspective of probability and frequency were analyzed. The results show that the probability density of forecast precipitation by the SWC-WARMS model is higher than that of observations in any forecast time, and the precipitation is concentrated below 10 mm. What's more, with the extension of forecast time, the wet deviation of model predicts is more significant. The difference of probability density curve in basin is smaller than that in plateau, and the difference of probability density curve in the area with small terrain difference is less than that in the area with large terrain difference. The precipitation forecast by SWC-WARMS model has many deviations, including more rainy days, higher precipitation intensity, large area with high precipitation frequency, and false high value areas. In addition, the SWC-WARMS model forecast at night(20—08) is better than daytime(08—20), and the 24 h cumulative precipitation forecast is superior to the 12 h cumulative precipitation forecast, especially in the forecast of precipitation areas with the moderate rain and above. At last, the extreme heavy precipitation forecasted by the model in the 20—08 period and 20—20 period is heavier than the actual precipitation. In terms of regions, the model predications are lower than the actual situation in basin, but higher in the Western Sichuan Plateau and the Panzhihua-Xichang region.
引文
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[18] 刘琳,陈静,程龙,等.基于集合预报的中国极端强降水预报方法研究.气象学报,2013,71(5):853-866.LIU Lin,CHEN Jing,CHENG Long,et al.Study of the ensemble-based forecast of extremely heavy rainfalls in China:Experiments for July 2011 cases.Acta Meteorologica Sinica (in Chinese),2013,71(5):853-866.
[19] 陈朝平,冯汉中,陈静.基于贝叶斯方法的四川暴雨集合概率预报产品释用.气象,2010,36(5):32-39.CHEN Chaoping,FENG Hanzhong,CHEN Jing.Application of Sichuan heavy rainfall ensemble prediction probability products based on Bayesian method.Meteorological Monthly (in Chinese),2010,36(5):32-39.
[20] 田付友,郑永光,毛冬艳,等.基于Γ函数的暖季小时降水概率分布.气象,2014,40(7):787-795.TIAN Fuyou,ZHENG Yongguang,MAO Dongyan,et al.Study on probability distribution of warm season hourly rainfall with Γ distribution.Meteorological Monthly (in Chinese),2014,40(7):787-795.
[21] 丁裕国.降水量Γ分布模式的普适性研究.大气科学,1994,18(5):552-560.DING Yuguo.Research of universality for Γ distribution model of precipitation.Scientia Atmospherica Sinica (in Chinese),1994,18(5):552-560.
[22] 梁莉,赵琳娜,巩远发,等.淮河流域汛期20 d内最大日降水量概率分布.应用气象学报,2011,22(4):421-428.LIANG Li,ZHAO Linna,GONG Yuanfa,et al.The probability distribution of the maximum amount of daily precipitation during 20 days in summer of the Huaihe Basins.Journal of Applied Meteorological Science (in Chinese),2011,22(4):421-428.
[2] 卢萍,肖玉华.2010年AREM、GRAPES模式预报性能对比检验分析.高原山地气象研究,2011,31(3):8-12.LU Ping,XIAO Yuhua.Prediction capability verification of AREM and GRAPES models in 2010.Plateau and Mountain Meteorology Research (in Chinese),2011,31(3):8-12.
[3] 闫之辉,邓莲堂.WRF模式中的微物理过程及其预报对比试验.沙漠与绿洲气象,2007,1(6):1-6.YAN Zhihui,DENG Liantang.Description of microphysical processes in WRF model and its prediction experiment.Desert and Oasis Meteorology (in Chinese),2007,1(6):1-6.
[4] 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.应用气象学报,2013,24(2):171-178.WANG Yu,GONG Ying,CHEN Fajing,et al.Comparison of two verification methods for 6 h precipitation forecasts of regional models.Journal of Applied Meteorological Science (in Chinese),2013,24(2):171-178.
[5] Groisman P Y,Karl T R,Easterling D R,et al.Changes in the probability of heavy precipitation:important indicators of climatic change.Climatic Change,1999,42(1):243-283.
[6] Hamill T M,Whitaker J S,Mullen S L.Reforecasts:an important dataset for improving weather predictions.Bull.Amer.Meteor.Soc.,2006,87(1):33-46.
[7] 宋培书,周晶.RSM模式对中国东部夏季降水模拟能力的检验.气象科学,2017,37(1):101-109.SONG Peishu,ZHOU Jing.Simulation on summer monsoon precipitation over eastern China by using regional spectral model.Journal of the Meteorological Sciences (in Chinese),2017,37(1):101-109.
[8] 徐星生,万明,薛谌彬,等.WRF-RUC在2014年江西汛期降水预报中的检验分析.气象与减灾研究,2014,37(3):23-28.XU Xingsheng,WAN Ming,XUE Chenbin,et al.Precipitation numerical validation of Jiangxi WRF-rapid update cycle forecast system during the flood season in 2014.Meteorology and Disaster Reduction Research (in Chinese),2014,37(3):23-28.
[9] 杨关盈,邓学良,王磊,等.基于CUACE模式产品的订正方法比较研究.气象科学,2017,37(6):839-844.YANG Guanying,DENG Xueliang,WANG Lei,et al.Comparative study of three correction methods for the CUACE model product.Journal of the Meteorological Sciences (in Chinese),2017,37(6):839-844.
[10] 何光碧,肖玉华,屠妮妮,等.GRAPES-MESO模式对一次强降水过程的预报及误差分析.高原山地气象研究,2012,32(1):8-17.HE Guangbi,XIAO Yuhua,TU Nini,et al.Prediction and error analysis of a heavy rain process with GRAPES-MESO model.Plateau and Mountain Meteorology Research (in Chinese),2012,32(1):8-17.
[11] 肖玉华,康岚,徐琳娜,等.西南区域中尺度数值模式预报性能及其与天气过程关系初探.气象,2013,39(10):1257-1264.XIAO Yuhua,KANG Lan,XU Linna,et al.Discussion on relationship between prediction performance of mesoscale numerical model and weather process in Southwest China.Meteorological Monthly (in Chinese),2013,39(10):1257-1264.
[12] 李超,裘薇,娄小芬,等.浙江省温度和相对湿度释用技术及其效果检验分析.气象科学,2016,36(4):556-561.LI Chao,QIU Wei,LOU Xiaofen,et al.Interpretation method and effect validation of temperature and relative humility forecast in Zhejiang province.Journal of the Meteorological Sciences (in Chinese),2016,36(4):556-561.
[13] 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.高原山地气象研究,2015,35(4):1-9.TU Nini,HENG Zhiwei,WU Pengping,et al.The verification of precipitation forecast for southwest region between SWCWARMS model and GRAPES model.Plateau and Mountain Meteorology Research (in Chinese),2015,35(4):1-9.
[14] YUAN Huiling,GAO Xiaogang,Mullen S L,et al.Calibration of probabilistic quantitative precipitation forecasts with an artificial neural network.Wea.Forecasting,2007,22(6):1287-1303.
[15] Gemmer M,Fischer T,Jiang T,et al.Trends in precipitation extremes in the Zhujiang River Basin,South China.J.Climate,2011,24(3):750-761.
[16] 周天军,钱永甫.地形效应影响数值预报结果的试验研究.大气科学,1996,20(4):452-462.ZHOU Tianjun,QIAN Yongfu.An experimental study on the effects of topography on numerical prediction.Scientia Atmospherica Sinica (in Chinese),1996,20(4):452-462.
[17] 曾庆存,宇如聪,彭贵康,等.“雅安天漏”研究Ⅲ:特征、物理量结构及其形成机制.大气科学,1994,18(6):649-659.ZENG Qingcun,YU Rucong,PENG Guikang,et al.Research on “Ya-An-Tian-Lou”.Part III:the physical structure and possible mechanism.Scientia Atmospherica Sinica (in Chinese),1994,18(6):649-659.
[18] 刘琳,陈静,程龙,等.基于集合预报的中国极端强降水预报方法研究.气象学报,2013,71(5):853-866.LIU Lin,CHEN Jing,CHENG Long,et al.Study of the ensemble-based forecast of extremely heavy rainfalls in China:Experiments for July 2011 cases.Acta Meteorologica Sinica (in Chinese),2013,71(5):853-866.
[19] 陈朝平,冯汉中,陈静.基于贝叶斯方法的四川暴雨集合概率预报产品释用.气象,2010,36(5):32-39.CHEN Chaoping,FENG Hanzhong,CHEN Jing.Application of Sichuan heavy rainfall ensemble prediction probability products based on Bayesian method.Meteorological Monthly (in Chinese),2010,36(5):32-39.
[20] 田付友,郑永光,毛冬艳,等.基于Γ函数的暖季小时降水概率分布.气象,2014,40(7):787-795.TIAN Fuyou,ZHENG Yongguang,MAO Dongyan,et al.Study on probability distribution of warm season hourly rainfall with Γ distribution.Meteorological Monthly (in Chinese),2014,40(7):787-795.
[21] 丁裕国.降水量Γ分布模式的普适性研究.大气科学,1994,18(5):552-560.DING Yuguo.Research of universality for Γ distribution model of precipitation.Scientia Atmospherica Sinica (in Chinese),1994,18(5):552-560.
[22] 梁莉,赵琳娜,巩远发,等.淮河流域汛期20 d内最大日降水量概率分布.应用气象学报,2011,22(4):421-428.LIANG Li,ZHAO Linna,GONG Yuanfa,et al.The probability distribution of the maximum amount of daily precipitation during 20 days in summer of the Huaihe Basins.Journal of Applied Meteorological Science (in Chinese),2011,22(4):421-428.