新一代天气雷达背景场特征资料生成方法及检验

地形对波束遮挡是影响雷达观测资料质量的重要误差源之一。国家防汛抗旱指挥系统二期工程建设了天气雷达应用系统,系统利用新一代天气雷达背景场特征资料客观分析技术计算出雷达站周围环境对雷达波束造成遮挡影响的背景场特征资料(挡角图、等射束高度图和波束遮挡能量耗损率图)。详细介绍了新一代天气雷达背景场特征资料计算原理和方法,并提出利用雷达回波概率特征方法,将计算出的背景场特征资料与不同仰角雷达回波统计的概率空间分布进行对比分析,验证了新一代天气雷达背景场特征资料的正确性,为后期雷达波束能量遮挡进行定量订正提供依据。     

突发性强灾害天气预警系统：理论与应用

“突发性强灾害天气预警系统”以WWW为平台,融贯多种天气预报新技术,为各类用户提供了崭新的预报视角和技术含量较高的预报产品;产品包括强对流指数诊断、基于卫星和雷达的外推产品,中尺度数值模式预报产品,以及基于“综合叠套技术”给出的强天气展望和强天气临近概率预报产品等。通过近几年部分省市业务化运行检验,证明该系统整体自动化程度高,运行稳定,其提供的综合预警产品能有效地为暴雨等强对流天气提供预警信息,提高了暴雨等强天气的预报预警服务质量。     

上海强对流智能预报业务新技术研究进展

强对流天气系统发展剧烈,常造成严重的暴雨、雷电、大风和冰雹等灾害。对强对流天气的准确预报一直是国际气象领域研究的难点和瓶颈问题,也是大城市防灾减灾关注的重点。强对流预报技术的发展已经从单纯依赖于雷达的图像识别,发展到雷达、卫星、高分辨率数值模式以及人工智能大数据预测融合应用的新阶段。在回顾国际强对流预报技术进展的基础上,介绍了上海气象业务部门近年来攻关研发的雷达自适应组网观测、雷达外推短临预测和数值预报误差机器学习订正等关键新技术及集成建立的上海强对流智能监测预报系统。这些技术成果的业务应用,在城市防灾减灾和精细化治理中已发挥了重要作用,可供相关研究人员参考。     

利用WRF3D-Var同化多普勒雷达反演风场试验研究

为了将C波段雷达风场资料更好地应用于数值预报模式中,利用两步变分法反演多普勒雷达风场资料,并处理成标准的常规探空资料,以WRF模式及其三维变分同化系统为平台,针对2013年6月19日发生在天水的一次强暴雨过程进行同化雷达反演风的试验研究.试验结果表明:同化雷达反演风场后,对降水预报的改进能维持12h,尤其同化雷达反演风场后3~9h效果非常显著;0~3h作用不是很明显;9~12h预报具有一定的正作用.另外,循环同化比同化一次效果好,但并不是同化次数越多越好.因此,同化C波段雷达反演风场后,对降水预报具有一定的正作用.     

基于雷达与卫星的对流触发观测研究和临近预报技术进展

对流触发(CI)一直是强对流天气预报中至关重要而又充满挑战的环节。在CI发生之前,高时空分辨率的天气雷达和静止气象卫星常能够观测识别到边界层辐合线和积云快速发展等用于评估CI发生条件的前兆信号,从而为定时定点的CI临近预报提供有力观测支撑。基于此,综述了雷达和卫星在CI观测研究和临近预报技术上的运用进展。首先回顾了近40年来CI观测研究中的里程碑工作以及最新的研究进展,结合CI发生条件梳理了CI研究方式和内容及其随雷达和卫星探测能力提升而呈现的发展趋势。进而介绍了较为成熟的3种基于雷达和卫星观测的CI业务临近预报技术在国际范围内的发展运用。最后提出雷达和卫星观测在CI研究和预报运用中需要进一步解决的问题。     

云分析预报方法研究进展

云作为地球大气系统的重要组成部分,不仅影响着气候变化和天气系统的发展演变,还与航空活动密切相关,一直以来是空军和民航部门非常关注的气象要素之一。在云探测、资料同化和反演方法发展的基础上,从实际业务保障和数值模式发展需求出发,综述国内外云分析、预报方法和云分析预报系统开发的研究成果,分析各类方法的优势和不足,明确国内外研究的主要差距,并探讨国内未来研究的方向。云分析方法中,探空对云廓线识别较好,卫星可见光和红外资料在云顶信息反演方面优势明显,多普勒雷达能够获取对流层中层和底层的云信息,而毫米波雷达能够很好地反映云三维结构信息,发展潜力巨大。云预报方法中,传统的统计和诊断方法发展较为成熟,而考虑了大气温湿和云微物理状况的大气辐射传输模式正演模拟云顶亮温的方法是未来的发展趋势。加强云探测技术,综合利用云分析预报方法,借鉴国外先进云分析预报系统的设计理念,积极开发我国自主的云分析预报系统,推动天气预报、航空气象保障和数值预报模式的发展将会是我国云研究的重要方面。     

"云娜"台风的监视和预报

2004年“云娜”台风的监视和预报工作中，在应用常规天气资料的基础上加强了对历史热带气旋资料、天气雷达资料和过去对台风与台风暴雨分析预报研究成果的运用。在台风登陆前、登陆过程中和登陆后三个不同阶段中，应用多种资料进行有针对性的分析判断，并向防台风指挥部门及时提供信息服务，在防台工作中发挥了有效作用。，     

黄淮流域天气雷达应用系统介绍与应用分析

2009-2010年,水利部水文局引进了美国海洋大气管理局(NOAA)强风暴实验室(NSSL)开发的新一代多探测器定量估算降水系统(下称Q2),利用黄淮流域的6部新一代天气雷达,开发了水利部天气雷达应用系统(下称MWKQ2)并进行了应用试验。系统集成了雷达、自动雨量站、探空等资料,实时每10分钟自动生成格距0.01°×0.01°(1km×1km)的多种降水产品以及区域面雨量产品(1、3、6、12、24、48、72h)。介绍了该系统的组成及关键技术,重点对MWRQ2雨量估算结果与常规雨量站资料进行了对比分析,结果表明这两种方法估算雨量的一致性较好,尤其是时段区域面雨量差别较小。     

全天候卫星微波观测资料变分同化研究进展

云和降水区微波观测包含大量与天气系统,特别是台风、暴雨等灾害性天气系统发生发展密切相关的大气信息,因此微波资料的全天候同化应用成为当前数值预报领域的热点研究问题。过去20年间,全球几大数值预报中心逐步开展了全天候同化技术的研究和业务应用,证实了全天候卫星微波观测资料能够改进模式中的质量、风场、湿度以及云和降水场的初始信息,从而改进数值预报模式的预报效果。通过梳理和评述全天候卫星微波观测资料同化方法,分析其中的关键技术问题和目前存在的困难和挑战,为未来在我国数值天气预报领域开展全天候同化研究提供依据。随着我国新一代数值天气预报模式的发展应用,加强我国全天候资料同化技术的研究将会在业务中发挥更大的科学效益和应用效益。     

关于地形对降水的影响研究简介

一、前言地形对降水的影响及其估算,对暴雨分析计算、雨量站网设计及流域规划均是一个十分重要的课题。同时,也是一个相当困难和研究基础十分薄弱的课题。近年来,国外日益认识到这一课题的重要性,并加强了研究。其中,日本“梅雨研究计划”提出了地形影响暴雨的许多事实和看法;美国近年来采用了多种新技术,如卫星、雷达和地面气象站网联合观测技术,资料自动处理技术,山地气流模拟技术等,对山地气流及暴雨特性进行了详尽细致的模拟,以期揭露更多的事实和取得理论上的进展;此外,英国及南斯拉夫、加拿大、巴基斯坦、瑞典等多山国     

Assimilation of Doppler weather radar observations in a mesoscale model for the prediction of rainfall associated with mesoscale convective systems

Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.     

Simulation of Heavy Precipitation Associated with an Intense Western Disturbance over Western Himalayas

Northern India is comprised of complex Himalayan mountain ranges having different altitude and orientations. This highly variable terrain is responsible for complexity of the weather systems passing over the region. During winter season, large amount of precipitation is received in this region due to eastward moving low pressure synoptic weather systems called Western Disturbances (WDs). Such heavy precipitation over the region lead to landslides and trigger avalanches in snow bound regions. This causes heavy damage to properties and human lives and therefore poses a great natural hazard threat. In this study an attempt is made to simulate a heavy precipitation event associated with an intense WD using a state of the art mesoscale model. Some important model simulated fields are compared with verifying analysis. Precipitation and circulation features associated with the intense WD are well simulated by the model. Forecast errors indicate that the high resolution mesoscale model could simulate the weather associated with the WD with reasonable accuracy.     

Forecasting for flood warning

Advances in flood forecasting have been constrained by the difficulty of estimating rainfall continuously over space, for catchment-, national- and continental-scale areas. This has had a concomitant impact on the choice of appropriate model formulations for given flood-forecasting applications. Whilst weather radar used in combination with raingauges – and extended to utilise satellite remote-sensing and numerical weather prediction models – have offered the prospect of progress, there have been significant problems to be overcome. These problems have curtailed the development and adoption of more complete distributed model formulations that aim to increase forecast accuracy. Advanced systems for weather radar display and processing, and for flood forecast construction, are now available to ease the task of implementation. Applications requiring complex networks of models to make forecasts at many locations can be undertaken without new code development and be readily revised to take account of changing requirements. These systems make use of forecast-updating procedures that assimilate data from telemetry networks to improve flood forecast performance, at the same time coping with the possibility of data loss. Flood forecasting systems that integrate rainfall monitoring and forecasting with flood forecasting and warning are now operational in many areas. Present practice in flood modelling and forecast updating is outlined from a UK perspective. Challenges for improvement are identified, particularly against a background of greater access to spatial datasets on terrain, soils, geology, land-cover, and weather variables. Representing the effective runoff production and translation processes operating at a given grid or catchment scale may prove key to improved flood simulation, and robust application to ungauged basins through physics-based linkages with these spatial datasets. The need to embrace uncertainty in flood-warning decision-making is seen as a major challenge for the future. To cite this article: R.J. Moore et al., C. R. Geoscience 337 (2005).     

“我国重大天气灾害形成机理与预测理论研究”取得的主要研究成果

国家重点基础研究发展计划项目“我国重大天气灾害形成机理与预测理论研究”经过项目全体科学家的５年研究，取得了一系列重要的研究成果：①提出了基于多种实时观测资料的梅雨锋暴雨的多尺度物理模型；②建立了梅雨锋暴雨的天气学模型；③梅雨锋是由多个不同尺度系统构成的梅雨锋系，它具有介于温带锋系结构与热带辐合带结构之间的副热带锋系结构，在长江中下游可以有时表现为双峰结构。锋前的湿物理过程与锋上强对流系统发展形成的正反馈过程以及梅雨锋系的不同尺度系统的相互作用是梅雨锋维持与发展的重要机制；④提出了多种中尺度暴雨的定量卫星遥感反演理论和方法，并形成一系列新的反演产品；⑤成功地研究了双多普勒雷达同步探测和反演中尺度暴雨三维结构的理论和方法；⑥发展了配有三维变分同化系统的中尺度暴雨数值预报模式系统，在2003年淮河抗洪救灾中发挥了积极作用；⑦成功组织了2001/2002年长江中下游梅雨锋暴雨野外科学试验，在野外试验中还开展了中日国际合作，在此基础上项目建立了规范、完善、使用便捷的暴雨野外试验数据库，实现了数据共享。     

数字流域与雨量站网论证技术的集成应用研究

针对传统站网论证方法难以与降雨分布的影响因素相关的局限性,将数字流域引入站网论证方法中,阐述了数字流域建设和信息提取的相关技术,并将数字流域与站网密度、相关分析、雨量等值线、历史洪水预报分析4种站网论证技术进行集成和应用研究。研究结果表明,数字流域与雨量站网论证技术的集成考虑了地形等因素影响,论证结果更合理,其基本思想可为类似的站网论证分析提供借鉴。     

基于TRMM卫星雷达降雨的流域陆面水文过程

利用热带降雨观测计划(TRMM)卫星雷达降雨数据驱动分布式陆面水文模型,研究流域尺度陆面水文过程,评估该数据在水文模拟与预报等研究领域的性能。通过与实测雨量资料比较,验证TRMM卫星雷达降雨数据的质量。分别将TRMM卫星雷达降雨与观测降雨作为耦合模型的气象输入,模拟和研究淮河流域1998~2003年的陆面水文过程时空变化。结果表明,TRMM卫星雷达降雨数据能够很好地描述降雨的时空分布,利用TRMM降雨模拟的结果与利用观测降雨模拟的结果精度相当;模拟流量与实测资料基本吻合。卫星雷达降雨数据在陆面水文过程研究中具有广泛的应用前景。     

Energetics of Indian winter monsoon

The Indian subcontinent is characterized by complex topography and heterogeneous land use-land cover. The Himalayas and the Tibetan Plateau are spread across the northern part of the continent. Due to its highly variable topography, understanding of the prevailing synoptic weather systems is complex over the region. The present study analyzes the energetics of Indian winter monsoon (IWM) over the Indian subcontinent using outputs of mesoscale model (MM5) forced with National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), US, initial and boundary conditions. MM5 modeling framework, designed to simulate or predict mesoscale atmospheric circulations, is having a limited-area, non-hydrostatic and terrain following 12 sigma levels. The IWM energetics is studied using MM5 model outputs. Prior to this model’s validity and deviation from the corresponding observations (NCEP/NCAR) is assessed. The model’s overestimation/underestimation of wind, temperature and specific humidity at upper troposphere proves that the model has difficulty in picking up corresponding fields at all the model grid points because of terrain complexity over the Himalayas and Tibetan Plateau. Hence, the model fields deviate from the corresponding observations. However, model results match well with the winter global energy budget calculated using reanalysis dataset by Peixoto and Oort (1992). It suggests MM5 model’s fitness in simulating large scale synoptic weather systems. And, thus the model outputs are used for calculation of energetics associated with IWM. It is observed that beyond \(15^{{\circ }}\hbox {N}\) lower as well as upper level convergence of diabatic heating, which represents continental cooling and sinking of heat from atmosphere to land mass (i.e., surface is cooler than surrounding atmosphere) dominates. The diabatic heating divergence (cooling of continents) is found over ocean/sea and whole of the China region, Tibetan and central Himalayas (because of excess condensation than evaporation). The adiabatic generation of kinetic energy depends on the cross isobaric flow (north to south in winter, i.e., the present study shows strong circulation during IWM). It is found that wind divergence of model concludes lower level convergence over study region (i.e., strong winter circulation in the model fields).     

Role of land state in a high resolution mesoscale model for simulating the Uttarakhand heavy rainfall event over India

In 2013, Indian summer monsoon witnessed a very heavy rainfall event (>30 cm/day) over Uttarakhand in north India, claiming more than 5000 lives and property damage worth approximately 40 billion USD. This event was associated with the interaction of two synoptic systems, i.e., intensified subtropical westerly trough over north India and north-westward moving monsoon depression formed over the Bay of Bengal. The event had occurred over highly variable terrain and land surface characteristics. Although global models predicted the large scale event, they failed to predict realistic location, timing, amount, intensity and distribution of rainfall over the region. The goal of this study is to assess the impact of land state conditions in simulating this severe event using a high resolution mesoscale model. The land conditions such as multi-layer soil moisture and soil temperature fields were generated from High Resolution Land Data Assimilation (HRLDAS) modelling system. Two experiments were conducted namely, (1) CNTL (Control, without land data assimilation) and (2) LDAS, with land data assimilation (i.e., with HRLDAS-based soil moisture and temperature fields) using Weather Research and Forecasting (WRF) modelling system. Initial soil moisture correlation and root mean square error for LDAS is 0.73 and 0.05, whereas for CNTL it is 0.63 and 0.053 respectively, with a stronger heat low in LDAS. The differences in wind and moisture transport in LDAS favoured increased moisture transport from Arabian Sea through a convectively unstable region embedded within two low pressure centers over Arabian Sea and Bay of Bengal. The improvement in rainfall is significantly correlated to the persistent generation of potential vorticity (PV) in LDAS. Further, PV tendency analysis confirmed that the increased generation of PV is due to the enhanced horizontal PV advection component rather than the diabatic heating terms due to modified flow fields. These results suggest that, two different synoptic systems merged by the strong interaction of moving PV columns resulted in the strengthening and further amplification of the system over the region in LDAS. This study highlights the importance of better representation of the land surface fields for improved prediction of localized anomalous weather event over India.     

Spatio-temporal estimation of shallow landslide hazard triggered by rainfall using a three-dimensional model

A shallow landslide triggered by rainfall can be forecast in real-time by modeling the relationship between rainfall infiltration and decrease of slope stability. This paper describes a promising approach that combines an improved three-dimensional slope stability model with an approximate method based on the Green and Ampt model, to estimate the time–space distribution of shallow landslide hazards. Once a forecast of rainfall intensity and slope stability-related data, e.g., terrain and geology data, are acquired, this approach is shown to have the ability to estimate the variation of slope stability of a wide natural area during rainfall and to identify the location of potential failure surfaces. The effectiveness of the estimation procedures described has been tested by comparison with a one-dimensional method and by application to a landslide-prone area in Japan.     

Impact of vegetation on the simulation of seasonal monsoon rainfall over the Indian subcontinent using a regional model

The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation, surface radiation, etc., that in turn induces changes in the model simulated outputs. The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model. The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization) versus that of USGS (United States Geological Survey) vegetation dataset on the simulation of the Indian summer monsoon. The present study has been conducted for five monsoon seasons (1998–2002), giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal) and 2002 (deficient). The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon. Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast. The MM5-USGS has greater tendency of overestimation of rainfall. It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation. Among the five years of study, it is seen that the RMSE of July and JJAS (June–July–August–September) for All India Rainfall is mostly lower for MM5-ISRO. Also, the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO. The wind fields at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation. The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the verification analysis by ISRO vegetation. The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India, showing greater spatial variability over the region. However, the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation. Sensible heat flux over north-west India is also better simulated by MM5-USGS.