主客观融合定量降水预报方法及平台实现
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摘要
随着天气预报业务现代化的发展,预报员面临气象数据爆发增长、服务前端需求不断提高以及客观预报技术广泛应用带来的挑战。传统以手工绘制降水落区为主的定量降水预报(QPF)技术流程已经不能帮助预报员在更高层面体现附加值。为支撑预报员在QPF流程中的核心作用,设计和开发了主客观融合QPF平台。该平台从海量预报数据选取、多源QPF集成、QPF调整和订正、格点化处理和服务产品制作五个方面帮助预报员控制数字化预报全流程。发展了多项关键技术支持平台的智能化,包括多模式QPF数据集构建技术、多模式QPF集成技术、QPF预报场调整和订正技术以及格点场后处理技术。基于MICAPS4系统,实现了主客观融合QPF平台的主要功能,发布了"QPF Master Blender 1.0"版本,并在2017年5月投入业务应用,取得良好反馈和效果。最后,对平台的未来发展进行了展望,包括发展数值模式检验评估工具支持预报员做出最优判断,研究多尺度模式信息的融合技术等。
With the development of the weather forecast modernization, forecasters are facing challenges brought by meteorological data explosion, the increasing demand of the service front end as well as the wide use of objective forecasting technology. Traditional quantitative precipitation forecast(QPF) technology, which is mainly based on manually plotting precipitation areas, can no longer assist forecasters to demonstrate added value at higher levels. To support the forecasters' central role in the QPF procedure, a subjective and objective QPF blender was designed and developed. This platform helps forecasters to take control of the whole process of numerical forecast from the following five aspects: selection from mass forecast data, integration of multi-source QPF, adjustment and correction of QPF, grid processing and service product production. The intelligence of the platform is secured by the development of a number of key supporting techniques, including multi-model QPF dataset construction technology, multi-model QPF integration technology,QPF field adjustment and correction techniques and gridded QPF post-processing technology. Based on MICAPS4, the main functions of this QPF platform has been realized. The "QPF Master Blender 1. 0" version was released and put into operation in May 2017, which has obtained good feedback and effectiveness. By the end of this paper, the future development of the platform is prospected,including the development of numerical model verification tools to support forecasters to make the best judgments, and research on the fusion technologies of multi-scale model information.
With the development of the weather forecast modernization, forecasters are facing challenges brought by meteorological data explosion, the increasing demand of the service front end as well as the wide use of objective forecasting technology. Traditional quantitative precipitation forecast(QPF) technology, which is mainly based on manually plotting precipitation areas, can no longer assist forecasters to demonstrate added value at higher levels. To support the forecasters' central role in the QPF procedure, a subjective and objective QPF blender was designed and developed. This platform helps forecasters to take control of the whole process of numerical forecast from the following five aspects: selection from mass forecast data, integration of multi-source QPF, adjustment and correction of QPF, grid processing and service product production. The intelligence of the platform is secured by the development of a number of key supporting techniques, including multi-model QPF dataset construction technology, multi-model QPF integration technology,QPF field adjustment and correction techniques and gridded QPF post-processing technology. Based on MICAPS4, the main functions of this QPF platform has been realized. The "QPF Master Blender 1. 0" version was released and put into operation in May 2017, which has obtained good feedback and effectiveness. By the end of this paper, the future development of the platform is prospected,including the development of numerical model verification tools to support forecasters to make the best judgments, and research on the fusion technologies of multi-scale model information.
引文
毕宝贵,代刊,王毅,等,2016.定量降水预报技术进展[J].应用气象学报,27(5):534-549.
曹勇,刘凑华,宗志平,等,2016.国家级格点化定量降水预报系统[J]·气象,42(12):1476-1482.
陈德辉,沈学顺,2006.新一代数值预报系统GRAPES研究进展[J].应用气象学报,17(6):773-777.
陈德辉,薛纪善,杨学胜,等,2008.GRAPES新一代全球/区域多尺度统一数值预报模式总体设计研究[J].科学通报,53(20):2396-2407.
陈力强,周小珊,杨森,2005.短期集合预报中定量降水预报集合方法初探[J].南京气象学院学报,28(4):543-548.
代刊,曹勇,钱奇峰,等,2016.中短期数字化天气预报技术现状及趋势[J].气象,42(12):1445-1455.
高嵩,毕宝贵,李月安,等,2017.MICAPS4预报业务系统建设进展与未来发展[J].应用气象学报,28(5):513-531.
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[J].气象,40(5):580-588.
林建,宗志平,蒋星,2013.2010—2011年多模式集成定量降水预报产品检验报告[J].天气预报,1(5):67-74.
王凤娇,吴书君,王立静,等,2011.海盐生产的降水塑苫决策分析[J].气象,37(1):116-121.
薛建军,王维国,王秀荣,等,2010.决策气象服务回顾与展望[J].气象,36(7):69-74.
严明良,缪启龙,沈树勤.2009.基于超级集合思想的数值预报产品变权集成方法探讨[J].气象,35(6):19-25.
张芳华,曹勇,徐琚,等,2016.Logistic判别模型在强降水预报中的应用[J].气象,42(4):398-405.
张涵斌,陈静,智协飞,等,2014.基于GRAPES_Meso的集合预报扰动方案设计与比较[J].大气科学学报,37(3):276-284.
张人禾,沈学顺,2008.中国国家级新一代业务数值预报系统GRAPES的发展[J].科学通报,53(20):2393-2395.
Accadia C,Mariani S,Casaioli M,et al,2003.Sensitivity of precipitation forecast skill scores to bilinear interpolation and a simple nearest-neighbor average method on high-resolution verification grids[J].Wea Forecasting,18(5):918-932.
Arnaud P,Bouvier C,Cisneros L,et al,2002.Influence of rainfall spatial variability on flood prediction[J].J Hydrol,260(1/2/3/4):216-230.
Bougeault P,Toth Z,Bishop C,et al,2010.The THORPEX interactive grand global ensemble[J].Bull Amer Meteor Soc,91(8):1059-1072.
Cleveland W S,Grosse E,Shyu W M,1991.Local regression models[M]//Chambers J M,Hastie T J.Statistical Models in S.London:Chapman and Hall/CRC:309-376.
Ebert E E,2001.Ability of a poor man's ensemble to predict the probability and distribution of precipitation[J].Mon Wea Rev,129(10):2461-2480.
Gebhardt C,Theis S,Krahe P,et al,2008.Experimental ensemble forecasts of precipitation based on a convection-resolving model[J].Atmos Sci Lett,9(2):67-72.
Golding B W,Ballard S P,MyIne K,et al,2014.Forecasting capabilities for the London 2012 Olympics[J].Bull Amer Meteor Soc,95(6):883-896.
Kim G,Barros A P,2001.Quantitative flood forecasting using multisensor data and neural networks[J].J Hydrol,246(1-4):45-62.
Knebl M R,Yang Z L,Hutchison K,et al,2005.Regional scale flood modeling using NEXRAD rainfall,GIS,and HEC-HMS/RAS:a case study for the San Antonio River Basin Summer 2002 storm event[J].J Environ Manage,75(4):325-336.
Malardel S,Wedi N,Deconinck W,et al,2016.A new grid for the IFS[R].ECMWF Newsletter No.146.Shinfield Park,Reading:European Centre for Medium-Range Weather Forecasts:23-28.
Messner J W,Mayr G J,Zeileis A,et al,2014.Heteroscedastic extended logistic regression for postprocessing of ensemble guidance[J].Mon Wea Rev,142(1):448-456.
Novak D R,Bailey C,Brill K F,et al,2014.Precipitation and temper-ature forecast performance at the weather prediction center[J].Wea Forecasting,29(3):489-504.
Palmer T N,Molteni F,Mureau R,et al,1993.Ensemble prediction[C]//Proceedings of ECMWF Seminar on Validation of models over Europe.Reading:ECMWF.
Petersen D,Brill K F,Bailey C,et al,2014.The evolving role of the forecaster at the weather prediction center:World Weather Open Science Conference[C].
Ruth D P,1992.The Systematic Interpolative Radial Search(SIRS)-A method to compute gridpoint values from contours[R].TDL Office Note 92-14.U.S.Department of Commerce,National Oceanic and Atmospheric Administration,National Weather Service,Office of Systems Development,Techniques Development Laboratory:1-16.
Shapiro L G,Stockman G,2002.Computer Version[M].Englewood:Prentice Hall PTR:69-73.
Surcel M,Zawadzki I,Yau M K,2014.On the filtering properties of ensemble averaging for storm-scale precipitation forecasts[J].Mon Wea Rev,142(3):1093-1105.
Toth Z,Kalnay E,1993.Ensemble forecasting at NMC:the generation of perturbations[J].Bull Amer Meteor Soc,74(12):2317-2330.
Toth Z,Kalnay E,1997.Ensemble forecasting at NCEP and the breeding method[J].Mon Wea Rev,125(12):3297-3319.
Unidata,2017(2017-10-23).Network Common Data Form(netCDF)version 4.5.0[CP/OL].Boulder:UCAR/Unidata.http://DOI.org/10.5065/D6H70CW6.
Wolberg G,1990.Digital Image Warping[M].Los Alamitos:WileyIEEE Computer Society Press
Zehe E,Becker R,Bardossy A,2001.The influence of spatial variability of soil moisture and precipitation at different scales on runoff production and infiltration[C]//van Loon E E,Troch P A.Book of Abstracts.International Workshop Catchment Scale Hydrologic Modeling and Data Assimilation.Wageningen.
曹勇,刘凑华,宗志平,等,2016.国家级格点化定量降水预报系统[J]·气象,42(12):1476-1482.
陈德辉,沈学顺,2006.新一代数值预报系统GRAPES研究进展[J].应用气象学报,17(6):773-777.
陈德辉,薛纪善,杨学胜,等,2008.GRAPES新一代全球/区域多尺度统一数值预报模式总体设计研究[J].科学通报,53(20):2396-2407.
陈力强,周小珊,杨森,2005.短期集合预报中定量降水预报集合方法初探[J].南京气象学院学报,28(4):543-548.
代刊,曹勇,钱奇峰,等,2016.中短期数字化天气预报技术现状及趋势[J].气象,42(12):1445-1455.
高嵩,毕宝贵,李月安,等,2017.MICAPS4预报业务系统建设进展与未来发展[J].应用气象学报,28(5):513-531.
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[J].气象,40(5):580-588.
林建,宗志平,蒋星,2013.2010—2011年多模式集成定量降水预报产品检验报告[J].天气预报,1(5):67-74.
王凤娇,吴书君,王立静,等,2011.海盐生产的降水塑苫决策分析[J].气象,37(1):116-121.
薛建军,王维国,王秀荣,等,2010.决策气象服务回顾与展望[J].气象,36(7):69-74.
严明良,缪启龙,沈树勤.2009.基于超级集合思想的数值预报产品变权集成方法探讨[J].气象,35(6):19-25.
张芳华,曹勇,徐琚,等,2016.Logistic判别模型在强降水预报中的应用[J].气象,42(4):398-405.
张涵斌,陈静,智协飞,等,2014.基于GRAPES_Meso的集合预报扰动方案设计与比较[J].大气科学学报,37(3):276-284.
张人禾,沈学顺,2008.中国国家级新一代业务数值预报系统GRAPES的发展[J].科学通报,53(20):2393-2395.
Accadia C,Mariani S,Casaioli M,et al,2003.Sensitivity of precipitation forecast skill scores to bilinear interpolation and a simple nearest-neighbor average method on high-resolution verification grids[J].Wea Forecasting,18(5):918-932.
Arnaud P,Bouvier C,Cisneros L,et al,2002.Influence of rainfall spatial variability on flood prediction[J].J Hydrol,260(1/2/3/4):216-230.
Bougeault P,Toth Z,Bishop C,et al,2010.The THORPEX interactive grand global ensemble[J].Bull Amer Meteor Soc,91(8):1059-1072.
Cleveland W S,Grosse E,Shyu W M,1991.Local regression models[M]//Chambers J M,Hastie T J.Statistical Models in S.London:Chapman and Hall/CRC:309-376.
Ebert E E,2001.Ability of a poor man's ensemble to predict the probability and distribution of precipitation[J].Mon Wea Rev,129(10):2461-2480.
Gebhardt C,Theis S,Krahe P,et al,2008.Experimental ensemble forecasts of precipitation based on a convection-resolving model[J].Atmos Sci Lett,9(2):67-72.
Golding B W,Ballard S P,MyIne K,et al,2014.Forecasting capabilities for the London 2012 Olympics[J].Bull Amer Meteor Soc,95(6):883-896.
Kim G,Barros A P,2001.Quantitative flood forecasting using multisensor data and neural networks[J].J Hydrol,246(1-4):45-62.
Knebl M R,Yang Z L,Hutchison K,et al,2005.Regional scale flood modeling using NEXRAD rainfall,GIS,and HEC-HMS/RAS:a case study for the San Antonio River Basin Summer 2002 storm event[J].J Environ Manage,75(4):325-336.
Malardel S,Wedi N,Deconinck W,et al,2016.A new grid for the IFS[R].ECMWF Newsletter No.146.Shinfield Park,Reading:European Centre for Medium-Range Weather Forecasts:23-28.
Messner J W,Mayr G J,Zeileis A,et al,2014.Heteroscedastic extended logistic regression for postprocessing of ensemble guidance[J].Mon Wea Rev,142(1):448-456.
Novak D R,Bailey C,Brill K F,et al,2014.Precipitation and temper-ature forecast performance at the weather prediction center[J].Wea Forecasting,29(3):489-504.
Palmer T N,Molteni F,Mureau R,et al,1993.Ensemble prediction[C]//Proceedings of ECMWF Seminar on Validation of models over Europe.Reading:ECMWF.
Petersen D,Brill K F,Bailey C,et al,2014.The evolving role of the forecaster at the weather prediction center:World Weather Open Science Conference[C].
Ruth D P,1992.The Systematic Interpolative Radial Search(SIRS)-A method to compute gridpoint values from contours[R].TDL Office Note 92-14.U.S.Department of Commerce,National Oceanic and Atmospheric Administration,National Weather Service,Office of Systems Development,Techniques Development Laboratory:1-16.
Shapiro L G,Stockman G,2002.Computer Version[M].Englewood:Prentice Hall PTR:69-73.
Surcel M,Zawadzki I,Yau M K,2014.On the filtering properties of ensemble averaging for storm-scale precipitation forecasts[J].Mon Wea Rev,142(3):1093-1105.
Toth Z,Kalnay E,1993.Ensemble forecasting at NMC:the generation of perturbations[J].Bull Amer Meteor Soc,74(12):2317-2330.
Toth Z,Kalnay E,1997.Ensemble forecasting at NCEP and the breeding method[J].Mon Wea Rev,125(12):3297-3319.
Unidata,2017(2017-10-23).Network Common Data Form(netCDF)version 4.5.0[CP/OL].Boulder:UCAR/Unidata.http://DOI.org/10.5065/D6H70CW6.
Wolberg G,1990.Digital Image Warping[M].Los Alamitos:WileyIEEE Computer Society Press
Zehe E,Becker R,Bardossy A,2001.The influence of spatial variability of soil moisture and precipitation at different scales on runoff production and infiltration[C]//van Loon E E,Troch P A.Book of Abstracts.International Workshop Catchment Scale Hydrologic Modeling and Data Assimilation.Wageningen.