Science and Prediction of Heavy Rainfall over China: Research Progress since the Reform and Opening-Up of New China

This paper reviews the major progress on development of the science and prediction of heavy rainfall over China since the beginning of the reform and opening-up of new China(roughly between 1980 and 2019). The progress of research on the physical mechanisms of heavy rainfall over China is summarized from three perspectives: 1) the relevant synoptic weather systems, 2) heavy rainfall in major sub-regions of China, and 3) heavy rainfall induced by typhoons. The development and application of forecasting techniques for heavy rainfall are summarized in terms of numerical weather prediction techniques and objective forecasting methods. Greatly aided by the rapid progress in meteorological observing technology and substantial improvement in electronic computing, studies of heavy rainfall in China have advanced to investigating the evolution of heavy-rain-producing storms and observational analysis of the cloud microphysical features. A deeper and more systematic understanding of the synoptic systems of importance to the production of heavy rainfall has also been developed. Operational forecast of heavy rainfall in China has changed from subjective weather event forecasts to a combination of both subjective and objective quantitative precipitation forecasts, and is now advancing toward probabilistic quantitative precipitation forecasts with the provision of forecast uncertainty information.     

A case study of excessive rainfall forecasting

Summary Flash floods have been recognized as one of the most significant natural disaster problems in the world. Within the United States, the annual average flood death toll exceeds one hundred and property damage is on the order of a billion dollars. There has been an increased effort of the meteorological community to improve short term quantitative precipitation forecasting, principally by improving mesoscale numerical weather prediction for heavy rain events. Nevertheless, to date, numerical weather prediction has had rather limited impact on the prediction of the most damaging convective rainstorms.This study examines numerical experiments, including both coarse-mesh and fine-mesh model simulations, of the Enid, Oklahoma flood of 10–11 October 1973. Besides the great concentration of rainfall, the Enid flood was rather unique in comparison with other flash flood cases in that it was part of a much larger area of heavy rainfall which soaked the central Plains over the 24h period ending at 1200 UTC 11 October. The objective is to assess the overall usefulness and limitation of numerical weather prediction models in quantitative precipitation forecasting for this flash flood event.The model experiments reveal that the broad-scale precipitation patterns associated with the front and cyclone are well predicted, but the maximum rainfall amounts around Enid are underpredicted. The fine-mesh model is superior to the coarse-mesh model because of the former's ability to generate many significant mesoscale features in the vicinity of the front. In the fine-mesh model, many convection-related parameters (e.g., moisture flux convergence) are correlated very well temporally and spatially with the observed heavy precipitation scenario.     

天气预报的业务技术进展

该文总结回顾了中央气象台近年来的天气预报业务技术进展。天气预报质量的历史演变显示了预报业务水平的提高, 这种业务能力的提高既反映了预报技术的发展, 也带来了天气预报业务的变化。对业务天气预报中各种预报技术应用进展的分析表明:数值预报在天气预报业务能力提高中发挥着重要的基础性作用; 同时, 基于对不同尺度天气影响系统发展演变过程深入认识的基础上, 天气学的预报方法依然是预报业务中的重要技术方法; 动力诊断预报已成为灾害性天气预报中的重要手段之一, 数值预报产品的解释应用是实现气象要素精细定量预报的技术途径。     

Impact of 4DVAR assimilation of rainfall data on the simulation of mesoscale precipitation systems in a mei-yu heavy rainfall event

The multi-scale weather systems associated with a mei-yu front and the corresponding heavy precipitation during a particular heavy rainfall event that occurred on 4 5 July 2003 in east China were successfully simulated through rainfall assimilation using the PSU/NCAR non-hydrostatic, mesoscale, numerical model （MM5） and its four-dimensional, variational, data assimilation （4DVAR） system. For this case, the improvement of the process via the 4DVAR rainfall assimilation into the simulation of mesoscale precipitation systems is investigated. With the rainfall assimilation, the convection is triggered at the right location and time, and the evolution and spatial distribution of the mesoscale convective systems （MCSs） are also more correctly simulated. Through the interactions between MCSs and the weather systems at different scales, including the low-level jet and mei-yu front, the simulation of the entire mei-yu weather system is significantly improved, both during the data assimilation window and the subsequent 12-h period. The results suggest that the rainfall assimilation first provides positive impact at the convective scale and the influences are then propagated upscale to the meso- and sub-synoptic scales.
Through a set of sensitive experiments designed to evaluate the impact of different initial variables on the simulation of mei-yu heavy rainfall, it was found that the moisture field and meridional wind had the strongest effect during the convection initialization stage, however, after the convection was fully triggered, all of the variables at the initial condition seemed to have comparable importance.     

局地地形、地表特征对上海暴雨过程影响的研究

作者在对2001年8月5~6日上海地区一场特大暴雨的诊断分析与数值模拟研究中确知,停滞在上海的热带低压及在其内发生、发展起来的中尺度对流云团是造成此次暴雨的直接天气系统。暴雨过程中,非常规观测资料及高分辨率暴雨数值模拟结果的分析对于揭示热带低压内暴雨中尺度系统的结构及发展演变的时空连续性具有重要作用。但同时也意识到,对于造成暴雨的各尺度系统的发生、发展,特别是造成局地突发性强降水的暴雨中尺度系统,某些物理过程的影响是不可忽视的。这些物理过程或独立影响着暴雨中尺度系统的发展,或相互作用、相互制约,共同影响着暴雨中尺度系统的发展。为此,作者在此次暴雨过程较成功的数值模拟研究基础上,对上海附近山脉地形及上海地区地表状况等可能影响暴雨中尺度系统发展的物理过程进行了模拟试验研究,结果表明,上海及其周边地区局地山脉地形和上海地区的地表分布特征虽不是造成此次局地突发性强暴雨的直接原因,但明显影响着暴雨系统的移动、停滞、发展和加强。上海以西的莫干山、天目山在热带低压东移过程中对于气流具有一定阻挡作用,有利于暖湿气流的聚集及热带低压移速的减慢。但若山脉过高且热带低压移至非平原地带,则来自西南的暖湿气流会受阻而汇集在莫干山至杭州湾一带,这样在相对强的偏西气流作用下,热带低压的移向就会出现变化。另外,上海局地地表城市化特征的加强使得城市近地层空气的暖干特性效应和城区上风方风速辐合,并由此引起暴雨系统内中尺度动力、热力特征出现变化,这值得在局地暴雨强度预报中加以关注。局地城市地表特征是城市暴雨灾害不容忽视的影响因素。     

Evaluating the impact of lightning data assimilation on mesoscale model simulations of a flash flood inducing storm

Flash floods are associated with highly localized convective storms producing heavy rainfall. Quantitative precipitation forecasting of such storms will potentially benefit from explicit representations of deep moist convection in numerical weather prediction models. However, explicit representation of moist convection is still not viable in operational mesoscale models, which rely on convective parameterizations for issuing short to medium-range forecasts. In this study we evaluate a technique that uses regional Cloud-to-Ground (CG) lightning observations to define areas of deep moist convection in thunderstorms and adjust the model-generated precipitation fields in those regions. The study focuses on a major flash flood inducing storm in central Europe (23 August 2005) that was simulated with the aid of an operational weather forecasting system (POSEIDON system based on Eta/NCEP model). The performance of the technique is assessed using as reference distributed rainfall estimates from a network of radar observations. The results indicate that CG lightning data can offer sufficient information to increase the mesoscale model skill in reproducing local convective precipitation that leads to flash floods. The model error correction is shown to be proportional to the density of lightning occurrence, making the technique potentially suitable for operational forecasting of flash flood inducing thunderstorms.     

Experiments in forecasting mesoscale convective weather over Changjiang delta

The real time operational severe convective weather forecast experiment carried out during May to July in 1990 over the Changjiang Delta is briefly described. The heavy rainfall and severe convective weather forecast worksheets for the Changjiang Delta have been proposed and used in the daily forecasting. Results show that the ability of 0-12h convective weather prediction has been improved significantly after the development of the forecast methods and the establishment of a mesoscale forecast base at Shanghai Meteorological Center during 1986 to 1990.Three cases of convective weather systems (meso-alpha, meso-beta, meso-gamma) during the experiment period are described and discussed.     

南疆暴雨研究进展

南疆地区位于欧亚腹地,属于典型的温带大陆性干旱气候,受复杂地形地貌、天气系统路径以及特殊的大气环流与水汽条件等影响,暴雨突发性强且地域性特征显著。目前,全球数值预报模式及中尺度数值模式对南疆暴雨的预报能力十分有限,近年来,许多研究团队在塔里木盆地进行了大型外场观测试验,对揭示南疆暴雨的机制机理有了更多启示,对造成南疆暴雨的对流触发机制、高低空系统配置及演变特征、降雨云物理过程等都有了更为深入的认识。本文对南疆暴雨的气候特征、大尺度环流背景、中尺度系统发生发展、水汽输送、降水动力机制等方面进行了总结回顾,并提出了需要进一步研究的科学问题,以期为进一步开展南疆暴雨研究、提高暴雨预报准确率及防灾减灾能力提供参考。     

中尺度天气图分析技术在2011年我国南方4次强降水过程中的应用

对12 h 50 mm以上的强降水带的预报,模式输出的降水资料是预报的重要依据,但是有时偏差可达100～200 km.本文尝试依据国家气象中心2010年下发的《中尺度天气图分析技术规范(暂行稿)》,利用探空资料,对2011年6月我国南方梅雨期间强降水过程中4次12 h最强降水时段的环境场进行中尺度天气图分析,得到了有利于梅雨锋附近的强降水的预报着眼点,给出了判断强降水落区的一些参考依据.700 hPa以下西南(偏南)急流汇合区,在这些地区,具备了较强的动力、水汽辐合和一定的风垂直切变.地面气压槽中低于日变化的3h变压低值区(中心)易形成变压风辐合流场,也是强降水易发区(中心).多数情况下锋面可以作为强降水南界,但当925 hPa暖切变位于地面锋面南侧(附近),强降水发生在锋前暖区,10 m·s-1以上西南急流所能到达的纬度可作为南界.500 hPa槽前≥18 m·s-1中层西南急流轴一般可作为50 mm以上的强降水区域的北界,但当925 hPa切变位置与中层西南急流位置重叠或位于其北侧时,则以700 hPa切变为北边界.将这些判据应用于多次强降水天气时段中,并与日本模式输出降水比较,在强雨带南北界以及降水中心方面有订正作用.中尺度天气图分析技术及预报思路是订正模式对强降水落区预报的有效手段之一.     

贵州西部极端对流性暴雨预报失败案例剖析

2020年6月1—2日,贵州西部发生了1次局地性的对流性暴雨过程,预报员和各数值模式对此次过程的预报量级显著偏小,对暴雨范围的低估,造成了特大暴雨、大暴雨的漏报。该文利用常规地面、高空资料,加密自动站观测资料,多普勒天气雷达资料,卫星资料及业务中常用的数值预报产品等对此次暴雨漏报案例进行剖析,结果表明：在弱天气尺度强迫背景下,高温高湿的环境中,未能准确判断对流的触发条件,未分析出露点锋、偏西风和偏南风的辐合、冷池和地面辐合线等的存在及其对强降水的影响,加之难以在短时间内对风场的发展演变进行精细分析,导致此次暴雨过程漏报;对于发生在暖湿气团中的对流性降水的预报,需考虑高温高湿环境下露点锋、辐合区、冷池、地面辐合线的相互作用触发对流并使其组织化发展,从而导致局地性、对流性强降水的产生;基于地面加密自动站资料和雷达资料等的短时临近预报可以帮助捕捉中小尺度系统,从而提高对此类暴雨的预报准确率。     

天津地区080625强对流天气过程的分析

强对流降水是天津地区重要的灾害性天气,为了研究该类天气发生发展的动力学、热力学机制,利用NCEP/NCAR再分析资料和FY-2C卫星逐时TBB资料对2008年6月25日天津的强对流降水过程进行研究,然后利用WRF（weather research and forecasting）中尺度数值模式对该次强对流降水过程进行数值模拟和诊断分析。结果表明：中尺度露点锋是该次强对流降水的重要机制,其对应的低层气流辐合所形成的强烈上升运动及相对应的强烈发展的对流云团,是此次天津强对流降水的直接影响系统;对流有效位能等参数的变化非常好地反映出此次强降水天气的发生和发展特征;较大的相对螺旋度与此次强对流天气的发生对应也较好。由此认为,中尺度露点锋锋生的动力学、热力学过程是此次强对流降水天气发生发展的重要机制。     

多普勒雷达资料同化的稀疏化方式对暴雨过程的影响研究

利用中尺度非静力WRF(Weather Research and Forecasting)模式及其三维变分同化系统,对2007年7月淮河流域的一次强降雨过程进行多普勒雷达径向速度资料的三维变分同化试验,重点考察雷达资料的不同稀疏化方式对同化结果以及对暴雨数值模拟的影响。结果表明:同化多普勒雷达径向速度资料使得模式初始风场包含了更丰富的中尺度特征信息,有效调整了初始场的环流结构,能够改善模式对暴雨过程的模拟效果;以不同的稀疏化处理方式同化多普勒雷达径向速度资料对分析场会产生不同的影响,进而影响模式的降水预报效果,本次试验中当极坐标网格径向分辨率取10 km的时候降水过程的预报效果最好。     

梅雨期暴雨系统的流依赖中尺度可预报性

中尺度天气系统的初值敏感性,导致了中尺度系统预报极限的存在.中尺度系统的初始误差的快速增长及其中尺度可预报性依赖于系统流的特征.梅雨暴雨形成是多尺度天气系统共同作用的结果,决定了梅雨期暴雨的形成机制的多样性,也决定了其初值敏感性的差异性.本文重点对比分析了五种不同类型的梅雨暴雨的误差增长特征及其机制.冷空气抬升、低层涡...     

一次西南低涡特大暴雨的中尺度对流云团特征

针对2007年7月8~10日四川盆地南部的特大暴雨天气过程,利用逐小时红外云顶黑体亮度温度结合地面加密雨量资料对其进行了对比分析。分析指出此次特大暴雨是由西南低涡内几个中尺度对流云团连续生消造成的,在其开始阶段有一中尺度对流复合体沿基本气流方向强烈发展,此阶段云团虽发展旺盛,但由于雨团随系统移动较快,并未造成洪灾。此云团减弱后,低涡环流仍维持并少动,又依次触发了3个中尺度对流的生成,这3个中尺度对流云团逆基本气流向SSW方向缓慢移动,造成的降水落区集中,中心雨强大,持续时间长,由此导致了暴雨洪涝的产生。强降水位置对于前向传播系统,一是在其发展的前端,二是在冷云中心的略偏后的位置,最大雨强出现在云团成熟之前发展最剧烈时,而后向传播的低涡云团强降水主要在冷云中心附近,最大雨强出现在云团发展最旺盛(冷云中心TBB最低)时。     

中国暴雨中尺度系统发生与发展的诊断分析和数值模拟(Ⅱ)数值模拟

通过改进的MM4中尺度数值模式，对我国三次典型大暴雨过程的模拟，来探讨暴雨中尺度系统发生与发展的问题。主要结果指出:气旋性涡柱在不稳定暖湿气柱内生成和发展，以及与整个涡柱共存的上升运动的持续加强，对暴雨中尺度系统的发展具有重要的作用；地面热通量，凝结潜热释放对暴雨中尺度系统的发展有决定性的作用；各种不同的物理过程和参数化、青藏高原的构形造成的外强迫影响，以及模式空间分辨率等，对暴雨中尺度系统结构与演变以及降雨量的模拟结果均有重要的作用。     

临沂中尺度数值预报系统及应用

介绍了临沂中尺度数值预报系统及预报产品的释用和模式系统应用雷达资料情况,并对2005年6~10月的业务运行结果进行了检验,对小雨和中雨预报效果较好,TS评分较高,对夜间温度预报平均值绝对误差在1.52~2.52℃之间,平均均方根误差在2.01~2.93℃之间。该系统降水预报质量较高,气温预报误差小,准确率高,对定时、定点、定量的精细化预报具有较高的参考价值。应用自主开发的SDAF软件包,对系统的预报产品进行释用,研制了暴雨、空气质量、极端气温、干热风等预报方法。将多普勒雷达回波强度加入模式,改变模式水汽场,明显改进了预报。对径向速度反演降水系统内部风场进入中尺度模式进行了初步试验,得出了一些有益结论。     

“7·20”河南极端暴雨精细观测及热动力成因

利用分钟降水资料、FY-4A气象卫星高分辨率资料、多普勒天气雷达资料和ERA5再分析资料对2021年“7·20”河南极端暴雨过程中尺度系统精细结构及热动力发展机制进行观测分析和诊断研究, 结果表明: 该过程发生在“两高对峙”的鞍型场弱背景下, 其主导系统为500 hPa弱低压系统和低层偏东风切变线; 极端暴雨主要由水平尺度约300 km呈近乎圆形结构中尺度对流复合体产生, 其长时间维持与内部多个中尺度对流系统的合并及外围东南侧暖湿区新生单体的持续并入有关; 郑州站小时强降水(201.9 mm· h-1)由几乎静止的低质心β中尺度弓状回波产生, 其分钟降水量持续在3~4.7 mm; 边界层风场的动力辐合触发强烈对流, 使得强降水区上空θ_se锋区长时间处于中性层结, 其高层辐散气流在西北太平洋副热带高压附近构成次级环流下沉支; 中层500 hPa低压区气旋式曲率附近正涡度平流和925 hPa偏东气流持续暖平流输送、低层变形场锋生作用, 以及来自华东近海边界层急流异常强盛的水汽输送是此次极端过程发展维持的热动力学成因。     

强对流天气监测预报预警技术进展

强对流天气预报业务包括监测、分析、预报、预警和检验等方面。对流初生识别、对流系统强度识别和对流天气类型识别等监测技术取得新进展,综合多源资料的监测技术已应用于中国气象局中央气象台业务。对流系统的触发、发展和维持机制等获得了新认识,我国不同类型强对流天气及其环境条件统计气候特征、分析规范及相应业务产品等为业务预报提供了必要基础和技术支撑。光流法、多尺度追踪技术以及应用模糊逻辑方法的临近预报技术等有明显进展,融合短时预报技术得到广泛应用,对流可分辨高分辨率数值 (集合) 预报及其后处理产品预报试验取得了显著成效,基于数值 (集合) 预报应用模糊逻辑方法的分类强对流天气短期预报技术为业务预报提供了技术支撑。强对流天气综合监测和多尺度自适应临近预报技术、多尺度分析技术以及融合短时预报技术、发展并应用模糊逻辑等方法的、基于高分辨率数值 (集合) 模式的区分不同强度等级和极端性的分类强对流天气精细化 (概率) 预报技术等是未来发展的主要方向。     

雷达反射率三维拼图观测资料在北方区域数值模式预报系统中的同化应用研究

以业务应用为目标,开展雷达反射率三维拼图观测资料在北方区域数值预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测资料,重点关注其对降水、湿度、温度及风的预报能力影响。首先,基于2017年8月雷达拼图观测资料批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报等方面有明显的改善作用。其次,选择在业务中预报难度较大的强降水个例开展分析研究,分析表明:（1）同化雷达拼图观测资料有效提高了模式降水预报性能,临近降水发生的循环起报时次预报效果更好;（2）对于短时间多次强降水过程发生的预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水凝物或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水凝物分布、热力场等进行调整,可提高模式降水预报性能。      

AN ANALYSIS OF DISTRIBUTION AND MESOSCALE STRUCTURE OF PRECIPITATION ABOUT LANDFALL TROPICAL CYCLONE KOPPU (0915)

Observation from automatic weather stations, radars and TRMM satellites are employed to investigate the precipitation distribution of tropical cyclone (TC) Koppu (0915) that made landfall on Guangdong province in 2009. The results show that the precipitation of landfall TC Koppu is featured by significant asymmetry and mesoscale structure, and occurs mainly to the left of its moving path. By examining the sea surface temperature (SST), water vapor flux, Q vector, vertical wind shear of environment etc., it is found out that the distribution of SST, water vapor convergence, low-level convective ascending and vertical wind shear facilitates the TC precipitation to take place to the left of the TC moving path. The mesoscale structure separated by Barnes band-pass filter presents that the precipitation of landfall KOPPU has some organized mesoscale spiral structures, which is around the TC center and composed of the form of belts or blocks. The heavy local rainfall of landfall TC Koppu is primarily associated with the rainfall due to mesoscale spiral structure.