山西省主要河流流域面雨量预报业务流程

以T213、HLAFS模式、MM5中尺度模式输出的格点资料以及日本降水量格点资料为基础，将影响山西降水的天气动力模型归纳为诊断模型，从中引出多个能够全面反映降水模型特征的综合物理因子；根据各种数值模式输出的降水量预报性能和质量优劣特点，依据数值模式的形势场预报优于要素场预报的现实，构造在不同环流形势背景下，启动不同预报方程的面雨量预报业务流程，有效地遏止了在环流形势调整时预报输出不能快速响应的弱点，提高了点和面雨量预报的准确度。     

格点选择对MAPS面雨量预报效果的影响

以MAPS数值预报产品为基础，采用1998～2001年MAPS数值格点降水预报场资料，选取长江上游六大流域不同的代表格点计算该流域不同时段、不同时效的面雨量。以历年面雨量实况为标准，对上述时段面雨量预报值进行相关分析。结果表明，格点选择不同，该流域面雨量预报结果存在较大差异，对于MAPS数值降水预报而言，采用将格点北移1纬度、东移3经度的方式，其预报效果最佳。将这种格点选择方式应用于2002年长江上游六大流域面雨量预报，其效果较好。     

基于人工神经网络的暴雨预报方法探讨

探讨了基于人工神经网络模型的暴雨预报方法。该方法仿预报员的暴雨预报思路，在动力模式的降水预报产品、环流形势场和暴雨落区之间通过人工神经网络建立非线性的统计预报模型，该模型的输入是动力模式的降水预报和初始环流形势场的扩展正交分解主成份分量，输出是预报区域的暴雨落区预报。2000年的汛期试验表明该客观预报方法可明显改进数值预报模式的暴雨落区预报，因此可望在业务预报中有较好的应用前景。     

长江上游流域面雨量预报系统

以T213数值预报产品降水格点为基础，采用权重方法和逐次订正法计算，然后根据统计、经验、模式等方法订正来预报单站降水，采用泰森多边形法计算长江上游流域面雨量的“四川省气象台长江上游流域面雨量预报系统”。     

长江上游流域面雨量预报系统

以T213数值预报产品降水格点为基础,采用权重方法和逐次订正法计算,然后根据统计、经验、模式等方法订正来预报单站降水,采用泰森多边形法计算长江上游流域面雨量的"四川省气象台长江上游流域面雨量预报系统".     

三种数值模式对长江上游面雨量预报能力的评估

利用2007—2008年长江上游逐日面雨量实况和中国T213、日本JMH、德国GER三种数值模式降水预报格点资料,采用TS评分方法,检验三种数值模式对长江上游面雨量≥20mm强降水的预报能力。检验结果显示,日本JMH模式12~36h预报评分达38.5%;中国T213模式为28.2%;德国GER模式为26.9%。并且在对降水落区进行定性评估的基础上,建立了降水预报产品与流域面雨量实况的线性回归方程。     

不平衡场在甘肃平凉市强对流天气预报中的释用

通过对平凉市强对流天气发生发展的高空环流形势进行合成分析,归纳出平凉市强对流天气的500 hPa典型场模型和环境场特征;利用T213数值预报格点资料对2008年6～9月逐日资料计算不平衡场,探讨了不平衡场与平凉市强对流天气的对应关系,通过实例分析和业务应用,该释用方法取得了较好的业务效果.     

1995年T_(63)数值预报产品检验与分析

T63数值模式的预报性能和预报时效如何，这是广大预报员急需了解和普遍关注的问题。本文取1995年全年T63格点资料（2．5×2．5网格距），着重分析检验见数值模式对主要影响广西天气的环流形势与天气系统预报能力等。     

开封中、短期逐日降水分级滚动预报方法

利用欧洲中心和T213数值预报产品格点资料,经环流形势特征分析、格点读数、指标量化、计算机编程等步骤,研制了逐日降水分级滚动预报方法。     

西北区东部6—9月大雨短期预报支持系统(MOS)

本文试用 ECMF500 百帕48小时预报高度场格点资料和 BJ 北半球模式数值预报产品格点资料,选定关键区对西北区东部大雨短期预报建立人机对话的支持系统。技术路线是:气候分析选定过程——大雨日当时场有限区环流分型——逐级消空——进入分型 MOS 数学模型——判别过程有无和参考落区。本系统的运行环境为 IBM/PC 机及其兼容机,支撑软件包使用 BASIC 语言和C 语言,操作方便。实现本系统,将为区域中心日常预报业务增添一有效工具。     

金沙江中下游面雨量分布特征及预报检验

基于2019年4～10月金沙江中下游逐日面雨量实况资料、西南区域数值天气预报业务模式(SWC-WARMS)和中央气象台智能网格预报模式(NWGD)0～24小时降水预报对金沙江中下游月累计面雨量、日面雨量的月极值分布、暴雨频次分布特征进行分析并做了检验评估。结果表明:(1)金沙江中下游月累计面雨量主要集中在6～9月,强降雨天气也主要出现在6～9月。(2)2019年4～10月期间总共出现暴雨次数22次,出现暴雨次数最多的区域是A区,D区没有出现暴雨。(3)西南区域模式对于C区、D区、E区月累计面雨量的预报以及对于A区和C区小雨和中雨的预报优于中央气象台预报模式。(4)平均绝对误差(Ea)、模糊评分(Mp)和TS评分(Tsk)结果显示中央台智能网格预报模式上优于西南区域预报模式。      

滁河流域汛期多模式集成面雨量预报检验评估

对2013—2016年汛期ECMWF、JMA及中尺度WRF模式的预报结果进行检验,基于合理的时间尺度,制作了动态权重集成面雨量预报(DWI)、分步集成面雨量预报(SI)和等权重集成面雨量预报(EWI)产品,并对2017—2020年汛期降水期间多种集成面雨量预报产品和ECMWF、JMA、WRF的单个模式面雨量预报产品进行对比评估.结果表明:3种集成面雨量预报效果整体上优于单一数值预报模式,尤其是预报致灾严重的暴雨等级降水优势明显;DWI和WRF对强降水的面雨量预报正确率最高,其他2种集成面雨量预报结果次之,ECMWF及JMA较差;模式集成预报弱降水过程的优势不明显.     

金沙江下游多种面雨量集成预报方法的对比分析

集成方法有利于提高降水要素预报的准确性和可预报性。本文基于格点实况资料和智能网格预报、西南区域数值预报、ECMWF模式预报、GRAPES模式预报产品,以面雨量为研究对象,采用多元回归法、BP神经网络法、评分权重法、加权集成预报法和算术平均法,得到集成面雨量预报,再运用平均绝对误差、模糊评分、正确率、TS评分、偏差分析等方法,对2020年4—10月金沙江下游面雨量预报效果进行对比分析。结果表明：多元回归集成法和BP神经网络法的预报效果总体上优于其他几种集成方法。在考虑流域面雨量的预报量级时,下游可以采用预报量级较小的模式和集成方法。集成后偏差百分比均有降低,且多元回归法和BP神经网络法对预报量级较小的模式有矫正作用。在面雨量有无、小雨和中雨预报中,多元回归法集成效果较好,在大雨量级预报中,BP神经网络法集成效果较好。这些结论可为流域面雨量预报提供参考借鉴。     

A numerical study on forecasting the Henan extraordinarily heavy rainfall event in August 1975

This study is essentially an experiment on the control experiment in the August 1975 catastrophe which was the heaviest rainfall in mainland China with a maximum 24-h rainfall of 1060.3 mm, and it significantly demonstrates that the limited area model can still skillfully give reasonable results even only the conventional data are available. For such a heavy rainfall event, a grid length of 90 km is too large while 45 km seems acceptable. Under these two grid sizes, the cumulus parameterization scheme is evidently superior to the explicit scheme since it restricts instabili-ties such as CISK to limited extent, The high resolution scheme for the boundary treatment does not improve fore-casts significantly.The experiments also revealed some interesting phenomena such as the forecast rainfall being too small while af-fecting synoptic system so deep as compared with observations. Another example is the severe deformation of synoptic systems both in initial conditions and forecast fields in the presence of complicated topography. Besides, the fixed boundary condition utilized in the experiments along with current domain coverage set some limitations to the model performances.     

密云水库流域性暴雨的短期预报方法研究

为了探索密云水库流域性暴雨的预报，着眼于影响暴雨的天气系统，从数值预报的解释应用入手，试验制作了密云水库流域性暴雨预报方法。通过整理1970-1993年24年间水库流域内20个水文站雨量资料，分析45个暴雨天气样本与历史天气形势和数值预报产品的关系，筛选出预报指标和预报因子，使用数值预报产品的解释应用方法，根据天气环流形势的分型，分别组建了6、7、8月每个月份的未来24小时暴雨天气预报方程。预报检验表明该预报方法是可信的，同时也表明客观划分环流型、筛选预报因子、恰当确定暴雨标准等是预报方法的关键。     

Analysis of a Heavy Rainfall Event over Beijing During 21-22 July2012 Based on High Resolution Model Analyses and Forecasts

The heaviest rainfall over 61 yr hit Beijing during 21-22 July 2012.Characterized by great rainfall amount and intensity,wide range,and high impact,this record-breaking heavy rainfall caused dozens of deaths and extensive damage.Despite favorable synoptic conditions,operational forecasts underestimated the precipitation amount and were late at predicting the rainfall start time.To gain a better understanding of the performance of mesoscale models,verification of high-resolution forecasts and analyses from the WRFbased BJ-RUCv2.0 model with a horizontal grid spacing of 3 km is carried out.The results show that water vapor is very rich and a quasi-linear precipitation system produces a rather concentrated rain area.Moreover,model forecasts are first verified statistically using equitable threat score and BIAS score.The BJ-RUCv2.0forecasts under-predict the rainfall with southwestward displacement error and time delay of the extreme precipitation.Further quantitative analysis based on the contiguous rain area method indicates that major errors for total precipitation( 5 mm h~(-1)) are due to inaccurate precipitation location and pattern,while forecast errors for heavy rainfall( 20 mm h~(-1)) mainly come from precipitation intensity.Finally,the possible causes for the poor model performance are discussed through diagnosing large-scale circulation and physical parameters(water vapor flux and instability conditions) of the BJ-RUCv2.0 model output.     

Analysis of a Heavy Rainfall Event over Beijing During 21-22 July 2012 Based on High Resolution Model Analyses and Forecasts

The heaviest rainfall over 61 yr hit Beijing during 21-22 July 2012.Characterized by great rainfall amount and intensity,wide range,and high impact,this record-breaking heavy rainfall caused dozens of deaths and extensive damage.Despite favorable synoptic conditions,operational forecasts underestimated the precipitation amount and were late at predicting the rainfall start time.To gain a better understanding of the performance of mesoscale models,verification of high-resolution forecasts and analyses from the WRFbased BJ-RUCv2.0 model with a horizontal grid spacing of 3 km is carried out.The results show that water vapor is very rich and a quasi-linear precipitation system produces a rather concentrated rain area.Moreover,model forecasts are first verified statistically using equitable threat score and BIAS score.The BJ-RUCv2.0forecasts under-predict the rainfall with southwestward displacement error and time delay of the extreme precipitation.Further quantitative analysis based on the contiguous rain area method indicates that major errors for total precipitation（〉 5 mm h~（-1）） are due to inaccurate precipitation location and pattern,while forecast errors for heavy rainfall（〉 20 mm h~（-1）） mainly come from precipitation intensity.Finally,the possible causes for the poor model performance are discussed through diagnosing large-scale circulation and physical parameters（water vapor flux and instability conditions） of the BJ-RUCv2.0 model output.     

Combination of Meteosat- and synoptic data to determine rainfall: A case study

Summary A pilot study was carried out to determine the capability of satellite data for mapping rainfall and to prove possibilities for combination with synoptic parameters. The investigations were based on digital infrared Meteosat data of the central and southern European region during two periods in 1979. The effective infrared emission temperatures were combined with parameters derived from synoptic maps. The rainfall distribution was extracted from synoptic surface data. The vorticity and its advection with the thermal wind were derived from the 850 hPa and 500 hPa topographies. For the investigated periods appreciable agreement was observed between the rainfall areas and the areas with positive advection of vorticity. Another requirement for the occurrence of precipitation is a relative minimum of cloud top temperature and vorticity. As supplement to synoptic charts satellite data are able to provide information on rainfall areas with high areal and temporal resolution.With 6 Figures     

天气学检验在东北区域数值模式秋冬季降水预报中的应用

根据影响天气系统不同,利用2007年9月－2008年2月东北区域中尺度数值模式12h累积降水预报和东北地区常规站降水实况资料,采用天气学检验方法,从降水中心强度、中心位置、降水主体强度、落区、范围和移速6个方面对东北区域中尺度模式降水预报产品的预报性能进行检验。结果表明：模式对东北地区秋、冬季降水有很好的预报能力,但因天气系统和预报时效不同其预报能力也有较大差异,其中对高空槽预报效果最好;一般情况下,在预报出现偏差时中心和主体强度易偏强,雨带范围易偏大,移速易偏慢。