具有复杂地形适应能力的INCA短临预报系统介绍
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摘要
INCA是由奥地利国家气象局发展的具有复杂地形适应性的短临集成分析预报系统,也是世界天气研究计划预报示范项目INCA-CE推荐的短临业务系统,已经在十几个国家和地区得到广泛应用。INCA构建高分辨系统地形、地表层指数和垂直坐标系,在分析中结合地面实况和遥感资料,一方面保证分析中实况信息得以准确保留,另外一方面利用遥感资料来提供基于实况插值的空间结构。INCA短临预报中使用了经典的相关运动矢量外推方法,并引入了地形影响方案。由于INCA系统实现了对山区地形的精细化描述,进而充分考虑了地形对要素场的影响,INCA在地形复杂的山区具有一定优势,在有着山洪地质灾害隐患的地区将能发挥较好的短临预警作用。INCA在强对流预报中发展了基于INCA分析场对流参数组合和卫星产品的决策算法来实现对流生消预报。还发展了一个雷暴大风物理参数化预报方案,主要基于雷达观测和短临预报来估算降水粒子载荷和负浮力,进而预报雷暴大风。对INCA分析和预报进行了验证检验,在短临时段对数值模式有明显提升,INCA对流算法对纯外推预报有所改进。
This paper presents the INCA(Integrated Nowcasting through Comprehensive Analysis) system, which has been developed with complex terrain adaptability at the Austrian National Weather Service. As the proposed nowcasting system by WWRP/WMO Forecast Demonstration Project INCA-CE, it has been widely used in more than ten countries and regions in the world. INCA sets up high resolution system terrain, surface-layer index and vertical coordinates. The analysis part of the system combines surface station data with remote sensing data in such a way that the observations at the station locations are reproduced, whereas the remote sensing data define the spatial structure of meteorological variables through interpolation. The nowcasting part employs classical correlation-based motion vectors derived from previous consecutive analyses, and in the case of precipitation the nowcast includes an intensity-dependent elevation effect. Because the INCA system implements the fine description of the mountainous terrain and takes full account of the influence of terrain on the element fields, INCA has certain advantages in the mountainous area with complex topography. It can do well as a technical nowcasting and warning system in areas at risk of mountain torrents and geological disasters. INCA improves nowcasting of convective cells by using a decision algorithm which is based on a subset of the convective analysis fields, combined with satellite products. A physical approach of parameterizing gusts related to thunderstorms was developed. Intense downdrafts and convective outflow are partially determined by the amount of negative buoyancy and precipitation load, which are assessed from radar reflectivity observations and nowcasts. Cross validation of the analysis and verification of the nowcast are performed. Analysis quality is high and significant added value of the system compared to the NWP forecast is found in the first few hours of the nowcast. It is shown that the pure translational forecast of convective cells can be improved by using a decision algorithm of some key convective diagnostics, and the improvement is particularly evident in mountain areas.
This paper presents the INCA(Integrated Nowcasting through Comprehensive Analysis) system, which has been developed with complex terrain adaptability at the Austrian National Weather Service. As the proposed nowcasting system by WWRP/WMO Forecast Demonstration Project INCA-CE, it has been widely used in more than ten countries and regions in the world. INCA sets up high resolution system terrain, surface-layer index and vertical coordinates. The analysis part of the system combines surface station data with remote sensing data in such a way that the observations at the station locations are reproduced, whereas the remote sensing data define the spatial structure of meteorological variables through interpolation. The nowcasting part employs classical correlation-based motion vectors derived from previous consecutive analyses, and in the case of precipitation the nowcast includes an intensity-dependent elevation effect. Because the INCA system implements the fine description of the mountainous terrain and takes full account of the influence of terrain on the element fields, INCA has certain advantages in the mountainous area with complex topography. It can do well as a technical nowcasting and warning system in areas at risk of mountain torrents and geological disasters. INCA improves nowcasting of convective cells by using a decision algorithm which is based on a subset of the convective analysis fields, combined with satellite products. A physical approach of parameterizing gusts related to thunderstorms was developed. Intense downdrafts and convective outflow are partially determined by the amount of negative buoyancy and precipitation load, which are assessed from radar reflectivity observations and nowcasts. Cross validation of the analysis and verification of the nowcast are performed. Analysis quality is high and significant added value of the system compared to the NWP forecast is found in the first few hours of the nowcast. It is shown that the pure translational forecast of convective cells can be improved by using a decision algorithm of some key convective diagnostics, and the improvement is particularly evident in mountain areas.
引文
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[4]Dixon M,Wiener G.TITAN:Thunderstorm identification,tracking,analysis,and nowcasting-A Radar-based Methodology.Journal of Atmospheric and Oceanic Technology,1993,10:785-797.
[5]郑永光,周康辉,盛杰,等.强对流天气监测预报预警技术进展.应用气象学报,2015,26(6):641-657.
[6]Haiden T,Kann A,Wittmann C,et al.The Integrated Nowcasting through Comprehensive Analysis(INCA)system and its validation over the eastern Alpine Region.Weather and Forecasting,2011,26:166-183.
[7]Steinheimer M,Haiden T.Improved nowcasting of precipitation based on convective analysis fields.Advances in Geosciences,2007,10:125-131.
[8]Ducrocq V,Tzanos D,Senesi S.Diagnostic tools using a mesoscale NWP model for the early warning of convection.Meteorological Applications,1998,5:329-349.
[9]Waldstreicher J S.Guide to utilizing moisture flux convergence as a predictor of convection.National Weather Digest,1989,14:20-35.
[10]俞小鼎,周小刚,王秀明.雷暴与强对流临近天气预报技术进展.气象学报,2012,70(3):311-337.
[11]Sun J,Crook N A.Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint.PartⅠ:Model development and simulated data experiments.Journal of the Atmospheric Sciences,1997,54:1642-1661.
[12]Sun J,Crook N A.Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint.PartⅡ:Retrieval experiments of an observed Florida convective storm.Journal of the Atmospheric Sciences,1998,55:835-852.
[13]Wolfson M M,Dupree W J,Rasmussen R,et al.Consolidated Storm Prediction for Aviation(Co SPA),AMS 13th Conference on Aviation,Range,and Aerospace Meteorology,New Orleans,LA,2008.
[14]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(6):754-766.
[15]韩雷,王洪庆,谭晓光,等.基于雷达数据的风暴体识别、追踪及预警的研究进展.气象,2007,33(1):3-10.
[16]曾小团,梁巧倩,农孟松,等.交叉相关算法在强对流天气临近预报中的应用.气象,2010,36(1):31-40.
[17]郑永光,张小玲,周庆亮,等.强对流天气短时临近预报业务技术进展与挑战.气象,2010,36(7):33-42.
[18]Li P W,Wong W K,Cheung P,et al.An overview of nowcasting development,applications,and ser vices in the Hong Kong Observatory.Journal of Meteorological Research,2014,28(5):859-876.
[2]Wilson J W,Crook N A,Mueller,et al.Nowcasting thunderstorms:a status report.Bulletin of the American Meteorological Society,1998,79:2079-2099.
[3]Cai H,Wilson J,Pinto J,et al.Developing NIWOT:a regional 1-6hr short-term thunderstorm forecast system.The Fifth International Conference on Mesoscale Meteorology and Typhoon,Boulder,USA,Oct 31st-Nov 3rd,2006.
[4]Dixon M,Wiener G.TITAN:Thunderstorm identification,tracking,analysis,and nowcasting-A Radar-based Methodology.Journal of Atmospheric and Oceanic Technology,1993,10:785-797.
[5]郑永光,周康辉,盛杰,等.强对流天气监测预报预警技术进展.应用气象学报,2015,26(6):641-657.
[6]Haiden T,Kann A,Wittmann C,et al.The Integrated Nowcasting through Comprehensive Analysis(INCA)system and its validation over the eastern Alpine Region.Weather and Forecasting,2011,26:166-183.
[7]Steinheimer M,Haiden T.Improved nowcasting of precipitation based on convective analysis fields.Advances in Geosciences,2007,10:125-131.
[8]Ducrocq V,Tzanos D,Senesi S.Diagnostic tools using a mesoscale NWP model for the early warning of convection.Meteorological Applications,1998,5:329-349.
[9]Waldstreicher J S.Guide to utilizing moisture flux convergence as a predictor of convection.National Weather Digest,1989,14:20-35.
[10]俞小鼎,周小刚,王秀明.雷暴与强对流临近天气预报技术进展.气象学报,2012,70(3):311-337.
[11]Sun J,Crook N A.Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint.PartⅠ:Model development and simulated data experiments.Journal of the Atmospheric Sciences,1997,54:1642-1661.
[12]Sun J,Crook N A.Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint.PartⅡ:Retrieval experiments of an observed Florida convective storm.Journal of the Atmospheric Sciences,1998,55:835-852.
[13]Wolfson M M,Dupree W J,Rasmussen R,et al.Consolidated Storm Prediction for Aviation(Co SPA),AMS 13th Conference on Aviation,Range,and Aerospace Meteorology,New Orleans,LA,2008.
[14]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(6):754-766.
[15]韩雷,王洪庆,谭晓光,等.基于雷达数据的风暴体识别、追踪及预警的研究进展.气象,2007,33(1):3-10.
[16]曾小团,梁巧倩,农孟松,等.交叉相关算法在强对流天气临近预报中的应用.气象,2010,36(1):31-40.
[17]郑永光,张小玲,周庆亮,等.强对流天气短时临近预报业务技术进展与挑战.气象,2010,36(7):33-42.
[18]Li P W,Wong W K,Cheung P,et al.An overview of nowcasting development,applications,and ser vices in the Hong Kong Observatory.Journal of Meteorological Research,2014,28(5):859-876.