“频率匹配法”在集合降水预报中的应用研究
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摘要
基于"频率匹配法"的思路,采用两种方法进行了集合降水预报的订正研究,一种方法是利用集合成员降水频率订正简单集合平均平滑效应的"概率匹配平均"法,另一种方法是利用实况降水频率订正集合成员降水预报系统偏差的"预报偏差订正"法,通过个例和批量试验,结果表明:(1)概率匹配平均法可以矫正简单集合平均的平滑作用所造成的小量级降水分布范围增大而强降水被削弱的负作用,这种改进对强降水区更显著,并且集合系统离散度越大这种改进也越大;但该方法对预报区域内总降水量的预报没有改进作用,不能改善预报的系统性偏差。(2)虽然预报偏差订正法对降水落区预报的改进有限,但可以订正模式降水预报的系统性误差,改进雨量预报以及集合预报系统的离散度特征和概率预报技巧;直接对集合平均预报进行偏差订正的效果优于单个成员偏差订正后的简单算术平均。(3)在对每个集合成员的降水预报进行偏差订正后,概率匹配平均仍可改善其简单平均的效果,因此在实际业务中,应该综合采用上述两种方法,以获得在消除系统性偏差的同时各量级降水分布又合理的集合平均降水预报。
Following the "frequency matching" concept,two approaches have been tested to improve ensemble-based precipitation forecasts for the case of Beijing "7.21"(21 July 2012) severe rainstorm and the period of rainy season from 1 May to 31 July 2010 in China.One approach is "probability-matched ensemble mean(PM)",which uses ensemble member-based precipitation frequency to calibrate the frequency of simple ensemble mean to correct smoothing effect caused by ensemble averaging;another is "bias correction",which uses observed precipitation frequency to calibrate the precipitation frequency of each ensemble member to remove systematic forecast bias caused by model deficiency.The results show that(1) PM can effectively correct the problem of "too-wide-spread light precipitation and too-much-reduced heavy precipitation" in a simple ensemble mean,especially so for extremely heavy rains.The larger ensemble spread is,the more improvement will be achieved.However,PM can barely improve total precipitation amount forecasts and has no ability to correct the systematic bias of the model.(2) Although bias correction is not effective in correcting precipitation position errors,it can effectively remove systematic bias in precipitation amount forecasts and,consequently,improve ensemble spread and probabilistic forecasts significantly.Bias correction of ensemble mean forecast needs to be done independently rather than through bias-corrected ensemble members via simple averaging.(3) PM approach also works well even after each ensemble member's bias has been removed in advance.Therefore,both PM and bias correction need to be done jointly to maximize benefit through model forecast post-processing in an operational environment.
Following the "frequency matching" concept,two approaches have been tested to improve ensemble-based precipitation forecasts for the case of Beijing "7.21"(21 July 2012) severe rainstorm and the period of rainy season from 1 May to 31 July 2010 in China.One approach is "probability-matched ensemble mean(PM)",which uses ensemble member-based precipitation frequency to calibrate the frequency of simple ensemble mean to correct smoothing effect caused by ensemble averaging;another is "bias correction",which uses observed precipitation frequency to calibrate the precipitation frequency of each ensemble member to remove systematic forecast bias caused by model deficiency.The results show that(1) PM can effectively correct the problem of "too-wide-spread light precipitation and too-much-reduced heavy precipitation" in a simple ensemble mean,especially so for extremely heavy rains.The larger ensemble spread is,the more improvement will be achieved.However,PM can barely improve total precipitation amount forecasts and has no ability to correct the systematic bias of the model.(2) Although bias correction is not effective in correcting precipitation position errors,it can effectively remove systematic bias in precipitation amount forecasts and,consequently,improve ensemble spread and probabilistic forecasts significantly.Bias correction of ensemble mean forecast needs to be done independently rather than through bias-corrected ensemble members via simple averaging.(3) PM approach also works well even after each ensemble member's bias has been removed in advance.Therefore,both PM and bias correction need to be done jointly to maximize benefit through model forecast post-processing in an operational environment.
引文
陈朝平,冯汉中,陈静.2010.基于贝叶斯方法的四川暴雨集合概率预报产品释用.气象,36(5):32-39.
陈法敬,矫梅燕,陈静.2011.一种温度集合预报产品释用方法的初步研究.气象,37(1):14-20.
陈良吕,陈静,陈德辉,等.2014.基于T213集合预报的延伸期产品释用方法及初步检验.气象,40(11):1293-1301.
邓国,龚建东,邓莲堂,等.2010.国家级区域集合预报系统研发和性能检验.应用气象学报,21(5):513-523.
杜钧.2002.集合预报的现状和前景.应用气象学报,13(1):16-28.
杜钧,陈静.2010.单一值预报向概率预报转变的基础:谈谈集合预报及其带来的变革.气象,36(11);1-11.
杜钧,康志明.2014a.天气预报中不确定性问题的调查分析.气象科技进展,4(1):58-67.
杜钧,李俊.2014b.集合预报方法在暴雨研究和预报中的应用.气象科技进展,4(5):6-20.
段明铿,王盘兴.2006.一种新的集合预报权重平均方法.应用气象学报,17(4):488-493.
李俊,杜钧,陈超君.2014.降水偏差订正的频率(或面积)匹配方法介绍和分析.气象,40(5):580-588.
李俊,杜钧,刘羽.2015.北京“7.21”特大暴雨不同集合预报方案的对比试验.气象学报,73(1):50-71.
李俊,杜钧,王明欢,等.2009.中尺度暴雨集合预报系统研发中的初值扰动试验.高原气象,28(6):1365-1375.
李俊,杜钧,王明欢,等.2010a.AREM模式两种初值扰动方案的集合降水预报试验及检验.热带气象学报,26(6):217-228.
李俊,王明欢,公颖,等.2010b.AREM短期集合预报系统及其降水预报检验.暴雨灾害,29(1):30-37.
李莉,李应林,田华,等.2011.T213全球集合预报系统性误差订正研究.气象,37(1):31-38.
林春泽,智协飞,韩艳,等.2009.基于TIGGE资料的地面气温多模式超级集合预报.应用气象学报,20(6):706-712.
马清,龚建东,李莉,等.2008.超级集合预报的误差订正与集成研究.气象,34(3):42-48.
魏凤英.1999.全国夏季降水区域动态权重集成预报试验.应用气象学报,10(4):402-409.
杨学胜.2001.业务集合预报系统的现状及展望.气象,27(6):3-9.
宇如聪,薛纪善,徐幼平.2004.AREMS中尺度暴雨数值预报模式系统.北京:气象出版社,3-7.
Brier G W.1950.Verification of forecasts expressed in terms of probability.Mon Wea Rev,78:l-3.
Chen Jing,Tian Hua,Guo Deng,et al.2012.The global ensemble prediction system(GEPS)and regional ensemble prediction system(REPS)at CMA and its application in monsoon season.92nd American Meteorological Society Annual Meeting,January 22—26,New Orleans,LA.
Chen Jing,Wang Yu,Li Li,et al.2013.A unified verification system for operational models from Regional Meteorological Centres of China Meteorological Administration.Meteor Appl,20:140-149.
Du Jun,Steven L M,Frederick Sanders.1997.Short-range ensemble forecasting of quantitative precipitation.Mon Wea Rev,125:2427-2459.
Du Jun,Steve T.2001.Implementation of a real-time short-range ensemble forecasting system at NCEP:An update.Preprints,9th Conference on Mesoscale Processes,Ft.Lauderdale,Florida,Amer Meteor Soc,355-356.
Duan Yihong,Gong Jiandong,Du Jun,et al.2012.An overview of the Beijing 2008 Olympics Research and Development Project(B08RDP).Bull Amer Meteor Soc,93:381-403.
Ebert E E.2001a.Ability of a poor man's ensemble to predict the probability and distribution of precipitation.Mon Wea Rev,129:2461-2479.
Ebert E E.2001b.Probability-matched ensemble mean.Available online at http://www.cawcr.gov.au/staff/eee/etrap/probmatch.html.
Murphy A H.1973.A new vector partition of the probability score.J Appl Meteor,12(4):595-600.
Toth Zoltan,Kalnay E.1993.Ensemble forecasting at NMC:The generation of perturbations.Bull Amer Meteor Soc,74:2317-2330.
Toth Zoltan,Kalnay E.1997.Ensemble forecasting at NCEP and the breeding method.Mon Wea Rev,125:3297-3319.
Talagrand O,Vautard R.1997.Evaluation of probabilistic prediction system.Workshop on Predictability ECMWF,10:20-22.
①定义为AB=F/O-1,这儿F(O)为满足某一阈值的预报(观测)降水面积或格点或站点数.AB>,=,<0.0分别对应为湿、无和干偏差。
陈法敬,矫梅燕,陈静.2011.一种温度集合预报产品释用方法的初步研究.气象,37(1):14-20.
陈良吕,陈静,陈德辉,等.2014.基于T213集合预报的延伸期产品释用方法及初步检验.气象,40(11):1293-1301.
邓国,龚建东,邓莲堂,等.2010.国家级区域集合预报系统研发和性能检验.应用气象学报,21(5):513-523.
杜钧.2002.集合预报的现状和前景.应用气象学报,13(1):16-28.
杜钧,陈静.2010.单一值预报向概率预报转变的基础:谈谈集合预报及其带来的变革.气象,36(11);1-11.
杜钧,康志明.2014a.天气预报中不确定性问题的调查分析.气象科技进展,4(1):58-67.
杜钧,李俊.2014b.集合预报方法在暴雨研究和预报中的应用.气象科技进展,4(5):6-20.
段明铿,王盘兴.2006.一种新的集合预报权重平均方法.应用气象学报,17(4):488-493.
李俊,杜钧,陈超君.2014.降水偏差订正的频率(或面积)匹配方法介绍和分析.气象,40(5):580-588.
李俊,杜钧,刘羽.2015.北京“7.21”特大暴雨不同集合预报方案的对比试验.气象学报,73(1):50-71.
李俊,杜钧,王明欢,等.2009.中尺度暴雨集合预报系统研发中的初值扰动试验.高原气象,28(6):1365-1375.
李俊,杜钧,王明欢,等.2010a.AREM模式两种初值扰动方案的集合降水预报试验及检验.热带气象学报,26(6):217-228.
李俊,王明欢,公颖,等.2010b.AREM短期集合预报系统及其降水预报检验.暴雨灾害,29(1):30-37.
李莉,李应林,田华,等.2011.T213全球集合预报系统性误差订正研究.气象,37(1):31-38.
林春泽,智协飞,韩艳,等.2009.基于TIGGE资料的地面气温多模式超级集合预报.应用气象学报,20(6):706-712.
马清,龚建东,李莉,等.2008.超级集合预报的误差订正与集成研究.气象,34(3):42-48.
魏凤英.1999.全国夏季降水区域动态权重集成预报试验.应用气象学报,10(4):402-409.
杨学胜.2001.业务集合预报系统的现状及展望.气象,27(6):3-9.
宇如聪,薛纪善,徐幼平.2004.AREMS中尺度暴雨数值预报模式系统.北京:气象出版社,3-7.
Brier G W.1950.Verification of forecasts expressed in terms of probability.Mon Wea Rev,78:l-3.
Chen Jing,Tian Hua,Guo Deng,et al.2012.The global ensemble prediction system(GEPS)and regional ensemble prediction system(REPS)at CMA and its application in monsoon season.92nd American Meteorological Society Annual Meeting,January 22—26,New Orleans,LA.
Chen Jing,Wang Yu,Li Li,et al.2013.A unified verification system for operational models from Regional Meteorological Centres of China Meteorological Administration.Meteor Appl,20:140-149.
Du Jun,Steven L M,Frederick Sanders.1997.Short-range ensemble forecasting of quantitative precipitation.Mon Wea Rev,125:2427-2459.
Du Jun,Steve T.2001.Implementation of a real-time short-range ensemble forecasting system at NCEP:An update.Preprints,9th Conference on Mesoscale Processes,Ft.Lauderdale,Florida,Amer Meteor Soc,355-356.
Duan Yihong,Gong Jiandong,Du Jun,et al.2012.An overview of the Beijing 2008 Olympics Research and Development Project(B08RDP).Bull Amer Meteor Soc,93:381-403.
Ebert E E.2001a.Ability of a poor man's ensemble to predict the probability and distribution of precipitation.Mon Wea Rev,129:2461-2479.
Ebert E E.2001b.Probability-matched ensemble mean.Available online at http://www.cawcr.gov.au/staff/eee/etrap/probmatch.html.
Murphy A H.1973.A new vector partition of the probability score.J Appl Meteor,12(4):595-600.
Toth Zoltan,Kalnay E.1993.Ensemble forecasting at NMC:The generation of perturbations.Bull Amer Meteor Soc,74:2317-2330.
Toth Zoltan,Kalnay E.1997.Ensemble forecasting at NCEP and the breeding method.Mon Wea Rev,125:3297-3319.
Talagrand O,Vautard R.1997.Evaluation of probabilistic prediction system.Workshop on Predictability ECMWF,10:20-22.
①定义为AB=F/O-1,这儿F(O)为满足某一阈值的预报(观测)降水面积或格点或站点数.AB>,=,<0.0分别对应为湿、无和干偏差。