Contributions of Fuqing ZHANG to Predictability,Data Assimilation,and Dynamics of High Impact Weather:A Tribute

This article reviews Fuqing ZHANG’s contributions to mesoscale atmospheric science,from research to mentoring to academic service,over his 20-year career.His fundamental scientific contributions on predictability,data assimilation,and dynamics of high impact weather,especially gravity waves and tropical cyclones,are highlighted.His extremely generous efforts to efficiently transmit to the community new scientific knowledge and ideas through mentoring,interacting,workshop organizing,and reviewing are summarized.Special appreciation is given to his tremendous contributions to the development of mesoscale meteorology in China and the education of Chinese graduate students and young scientists.

Improving the Analyses and Forecasts of a Tropical Squall Line Using Upper Tropospheric Infrared Satellite Observations

The advent of modern geostationary satellite infrared radiance observations has noticeably improved numerical weather forecasts and analyses.However,compared to midlatitude weather systems and tropical cyclones,research into using infrared radiance observations for numerically predicting and analyzing tropical mesoscale convective systems remain mostly fallow.Since tropical mesoscale convective systems play a crucial role in regional and global weather,this deficit should be addressed.This study is the first of its kind to examine the potential impacts of assimilating all-sky upper tropospheric infrared radiance observations on the prediction of a tropical squall line.Even though these all-sky infrared radiance observations are not directly affected by lower-tropospheric winds,the high-frequency assimilation of these all-sky infrared radiance observations improved the analyses of the tropical squall line’s outflow position.Aside from that,the assimilation of all-sky infrared radiance observations improved the analyses and prediction of the squall line’s cloud field.Finally,reducing the frequency of assimilating these all-sky infrared radiance observations weakened these improvements to the analyzed outflow position,as well as the analyses and predictions of cloud fields.

Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.

Correction to:Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

The article“Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales”,written by Yunji ZHANG,Eugene E.CLOTHIAUX,and David J.STENSRUD was originally pub-lished electronically on the publisher’s internet portal on 30 of April 2021 without open access.With the author(s)’decision to opt for Open Choice,the copyright of the article changed on 26 of October 2021 to©The Author(s),2021 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License,which permits use,sharing,adapta-tion,distribution and reproduction in any medium or format,as long as you give appropriate credit to the original author(s)and the source,provide a link to the Creative Commons licence,and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons licence,unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use,you will need to obtain permission directly from the copyright holder.To view a copy of this licence,visit http://creativecommons.org/licenses/by/4.0.The original article has been corrected.

Assimilation of All-sky Geostationary Satellite Infrared Radiances for Convection-Permitting Initialization and Prediction of Hurricane Joaquin(2015)

Intensity forecasting is one of the most challenging aspects of tropical cyclone(TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin(2015) with an ensemble Kalman filter(EnKF)based on the Weather Research and Forecasting(WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin(2015)'s intensity, this study examines the potential in improving Joaquin's prediction when assimilating all-sky infrared radiances from GOES-13's water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin's intensity,including its rapid intensification(RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane's RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.

The ocean response to climate change guides both adaptation and mitigation efforts

在全球变化背景下,海洋的很多变化在人类社会发展的时间尺度上(百年至千年)具有不可逆转性,海洋巨大的热惯性是造成该不可逆性的主要原因.这个特征为人类和生态系统应对海洋变化提出一系列挑战.本文从海洋变化的角度总结了人类应对气候变化的要求,提出需要进行多时间尺度的规划和统筹.在近期(到2030年),实现联合国可持续发展目标至关重要.在中期(2050–2060年前后),全球需要逐步减排并实现碳中和目标.同时,适应和减缓气候变化的行动和措施必须同步施行;全球海洋观测系统需要得以维持并完善以持续监测海洋变化.在远期(在2060年之后),即使全球达到净零排放,包括深海变暖和海平面上升在内的海洋变化都将持续,因此应对全球变化的行动需持续数百年之久.在该时间尺度,应对“低概率,高影响”气候风险(即发生的可能性较低,但一旦发生影响极大的事件带来的风险,例如:大西洋经圈反转环流突然减弱,海洋生态系统跨过临界点,无可挽回的冰盖质量损失等)的准备应充分纳入长期规划.

Variational Quality Control of Non-Gaussian Innovations in the GRAPES m3DVAR System: Mass Field Evaluation of Assimilation Experiments

The existence of outliers can seriously influence the analysis of variational data assimilation.Quality control allows us to effectively eliminate or absorb these outliers to produce better analysis fields.In particular,variational quality control(VarQC) can process gray zone outliers and is thus broadly used in variational data assimilation systems.In this study,governing equations are derived for two VarQC algorithms that utilize different contaminated Gaussian distributions(CGDs): Gaussian plus flat distribution and Huber norm distribution.As such,these VarQC algorithms can handle outliers that have non-Gaussian innovations.Then,these VarQC algorithms are implemented in the Global/Regional Assimilation and PrEdiction System(GRAPES) model-level three-dimensional variational data assimilation(m3 DVAR) system.Tests using artificial observations indicate that the VarQC method using the Huber distribution has stronger robustness for including outliers to improve posterior analysis than the VarQC method using the Gaussian plus flat distribution.Furthermore,real observation experiments show that the distribution of observation analysis weights conform well with theory,indicating that the application of VarQC is effective in the GRAPES m3 DVAR system.Subsequent case study and longperiod data assimilation experiments show that the spatial distribution and amplitude of the observation analysis weights are related to the analysis increments of the mass field(geopotential height and temperature).Compared to the control experiment,VarQC experiments have noticeably better posterior mass fields.Finally,the VarQC method using the Huber distribution is superior to the VarQC method using the Gaussian plus flat distribution,especially at the middle and lower levels.

Skill Assessment of North American Multi-Models Ensemble (NMME) for June-September (JJAS) Seasonal Rainfall over Ethiopia

In recent years, there has been increasing demand for high-resolution seasonal climate forecasts at sufficient lead times to allow response planning from users in agriculture, hydrology, disaster risk management, and health, among others. This paper examines the forecasting skill of the North American Multi-model Ensemble (NMME) over Ethiopia during the June to September (JJAS) season. The NMME, one of the multi-model seasonal forecasting systems, regularly generates monthly seasonal rainfall forecasts over the globe with 0.5 - 11.5 months lead time. The skill and predictability of seasonal rainfall are assessed using 28 years of hindcast data from the NMME models. The forecast skill is quantified using canonical correlation analysis (CCA) and root mean square error. The results show that the NMME models capture the JJAS seasonal rainfall over central, northern, and northeastern parts of Ethiopia while exhibiting weak or limited skill across western and southwestern Ethiopia. The performance of each model in predicting the JJAS seasonal rainfall is variable, showing greater skill in predicting dry conditions. Overall, the performance of the multi-model ensemble was not consistently better than any single ensemble member. The correlation of observed and predicted seasonal rainfall for the better performing models—GFDL-CM2p5-FLOR-A06, CMC2-CanCM4, GFDL-CM2p5-FLOR-B01 and NASA-GMAO-062012—is 0.68, 0.58, 0.52, and 0.5, respectively. The COLA-RSMAS-CCSM4, CMC1- CanCM3 and NCEP-CFSv2 models exhibit less skill, with correlations less than 0.4. In general, the NMME offers promising skill to predict seasonal rainfall over Ethiopia during the June-September (JJAS) season, motivating further work to assess its performance at longer lead times.

Review of Chinese atmospheric science research over the past 70 years: Synoptic meteorology

Synoptic meteorology is a branch of meteorology that uses synoptic weather observations and charts for the diagnosis,study,and forecasting of weather.Weather refers to the specific state of the atmosphere near the Earth’s surface during a short period of time.The spatial distribution of meteorological elements in the atmosphere can be represented by a variety of transient weather phenomena,which are caused by weather systems of different spatial and temporal scales.Weather is closely related to people’s life,and its development and evolution have always been the focus of atmospheric scientific research and operation.The development of synoptic meteorology is closely related to the development of observation systems,dynamical theories and numerical models.In China,observation networks have been built since the early 1950 s.Up to now,a comprehensive meteorological observation systembased on ground,air and space has been established.In particular,the development of a new generation of dense radar networks,the development of the Fengyun satellite series and the implementation of a series of large field experiments have brought our understanding of weather from large-scale environment to thermal dynamics,cloud microphysical structure and evolution characteristics of meso and micro-scale weather systems.The development of observation has also promoted the development of theory,numerical model and simulation.In the early days,China mainly used foreign numerical models.Lately,China has developed numerical model systems with independent intellectual property rights.Based on the results of high-resolution numerical simulations,in-depth understanding of the initiation and evolution mechanism and predictability of weather at different scales has been obtained.Synoptic meteorology has gradually changed from an initially independent development to a multidisciplinary approach,and the interaction between weather and the change of climate and environment has become a hot and frontier topic in atmospheric science.This paper reviews the important scientific and technological achievements made in China over the past 70 years in the fields of synoptic meteorology based on the literatures in China and abroad,from six aspects respectively including atmospheric dynamics,synoptic-scale weather,typhoon and tropical weather,severe convective weather,numerical weather prediction and data assimilation,weather and climate,atmospheric physics and atmospheric environment.

ADVANCES IN UNDERSTANDING DIFFICULT CASES OF TROPICAL CYCLONE TRACK FORECASTS

Although tropical cyclone track forecast errors have substantially decreased in recent decades,there are still cases each season with large uncertainties in the forecasts and/or very large track errors.As such cases are challenging for forecasters,it is important to understand the mechanisms behind the low predictability.For this purpose the research community has developed a number of tools.These tools include ensemble and adjoint sensitivity models,ensemble perturbation experiments and nudging experiments.In this report we discuss definitions of difficult cases for tropical cyclone track forecasts,diagnostic techniques to understand sources of errors,lessons learnt in recent years and recommendations for future work.

Modeling Arctic Boundary Layer Cloud Streets at Grey-zone Resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds,we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiaġvik(formerly Barrow),Alaska,on 2 May 2013 and were observed by MODIS(the Moderate Resolution Imaging Spectroradiometer).The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain.We investigated the model-simulated mesoscale environment,horizontal and vertical cloud structures,boundary layer stability,and cloud properties,all of which were subsequently used to interpret the observed roll-cloud case.Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer.The clouds were stratiform-like in the mesoscale domain,but as the model resolution increased,roll-like structures,aligned along the wind field,appeared with ever smaller wavelengths.A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing.With fixed model grid spacing at 0.333 km,changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment,a stronger vertical water vapor gradient below the cloud layers,and the wavelengths of the rolls decreased slightly.In this study,only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Daily extreme precipitation and trends over China

Based on daily precipitation data of more than 2000 Chinese stations and more than 50 yr, we constructed time series of extreme precipitation based on six different indices for each station: annual and summer maximum(top-1) precipitation,accumulated amount of 10 precipitation maxima(annual, summer; top-10), and total annual and summer precipitation.Furthermore, we constructed the time series of the total number of stations based on the total number of stations with top-1 and top-10 annual extreme precipitation for the whole data period, the whole country, and six subregions, respectively. Analysis of these time series indicate three regions with distinct trends of extreme precipitation:(1) a positive trend region in Southeast China,(2) a positive trend region in Northwest China, and(3) a negative trend region in North China. Increasing(decreasing)ratios of 10–30% or even >30% were observed in these three regions. The national total number of stations with top-1 and top-10 precipitation extremes increased respectively by 2.4 and 15 stations per decade on average but with great inter-annual variations.There have been three periods with highly frequent precipitation extremes since 1960:(1) early 1960 s,(2) middle and late 1990 s,and(3) early 21 st century. There are significant regional differences in trends of regional total number of stations with top-1 and top-10 precipitation. The most significant increase was observed over Northwest China. During the same period, there are significant changes in the atmospheric variables that favor the decrease of extreme precipitation over North China: an increase in the geopotential height over North China and its upstream regions, a decrease in the low-level meridional wind from South China coast to North China, and the corresponding low moisture content in North China. The extreme precipitation values with a50-year empirical return period are 400–600 mm at the South China coastal regions and gradually decrease to less than 50 mm in Northwest China. The mean increase rate in comparison with 20-year empirical return levels is 6.8%. The historical maximum precipitation is more than twice the 50-year return levels.

Dynamics of local extreme rainfall of super Typhoon Soudelor (2015) in East China

The characteristics and dynamics associated with the distribution, intensity, and triggering factors of local severe precipitation in Zhejiang Province induced by Super Typhoon Soudelor(2015) were investigated using mesoscale surface observations, radar reflectivity, satellite nephograms, and the final(FNL) analyses of the Global Forecasting System(GFS) of the National Center for Environmental Prediction(NCEP). The rainfall processes during Soudelor's landfall and translation over East China could be separated into four stages based on rainfall characteristics such as distribution, intensity, and corresponding dynamics. The relatively less precipitation in the first stage resulted from interaction between the easterly wind to the north flank of this tropical cyclone(TC) and the coastal topography along the southeast of Zhejiang Province, China. With landfall of the TC in East China during the second stage, precipitation maxima occurred because of interaction between the TC's principal rainbands and the local topography from northeastern Fujian Province to southwestern Zhejiang Province. The distribution of precipitation presented significant asymmetric features in the third stage with maximal rainfall bands in the northeast quadrant of the TC when Soudelor's track turned from westward to northward as the TC decayed rapidly. Finally, during the northward to northeastward translation of the TC in the fourth stage, the interaction between a mid-latitude weather system and the northern part of the TC resulted in transfer of the maximum rainfall from the north of Zhejiang Province to the north of Jiangsu Province,which represented the end of rainfall in Zhejiang Province. Further quantitative calculations of the rainfall rate induced by the interaction between local topography and TC circulation(defined as "orographic effects") in the context of a one-dimensional simplified model showed that orographic effects were the primary factor determining the intensity of precipitation in this case,and accounted for over 50% of the total precipitation. The asymmetric distribution of the TC's rainbands was closely related to the asymmetric distribution of moisture resulted from changes of the TC's structure, and led to asymmetric distribution of local intense precipitation induced by Soudelor. Based on analysis of this TC, it could be concluded that local severe rainfall in the coastal regions of East China is closely related to changes of TC structure and intensity, as well as the outer rainbands. In addition, precipitation intensity and duration will increase correspondingly because of the complex interactions between the TC and local topography, and the particular TC track along large-scale steering flow. The results of this study may be useful for the understanding, prediction, and warning of disasters induced by local extreme rainfall caused by TCs, especially for facilitating forecasting and warning of flooding and mudslides associated with torrential rain caused by interactions between landfalling TCs and coastal topography.

Uncertainties and error growth in forecasting the record-breaking rainfall in Zhengzhou,Henan on 19–20 July 2021

This study explores the controlling factors of the uncertainties and error growth at different spatial and temporal scales in forecasting the high-impact extremely heavy rainfall event that occurred in Zhengzhou,Henan Province China on 19−20 July 2021 with a record-breaking hourly rainfall exceeding 200 mm and a 24-h rainfall exceeding 600 mm.Results show that the strengths of the mid-level low-pressure system,the upper-level divergence,and the low-level jet determine both the amount of the extreme 24-h accumulated and hourly rainfall at 0800 UTC.The forecast uncertainties of the accumulated rainfall are insensitive to the magnitude and the spatial structure of the tiny,unobservable errors in the initial conditions of the ensemble forecasts generated with Global Ensemble Forecast System(GEFS)or sub-grid-scale perturbations,suggesting that the predictability of this event is intrinsically limited.The dominance of upscale rather than upamplitude error growth is demonstrated under the regime of k^(−5/3) power spectra by revealing the inability of large-scale errors to grow until the amplitude of small-scale errors has increased to an adequate amplitude,and an apparent transfer of the fastest growing scale from smaller to larger scales with a slower growth rate at larger scales.Moist convective activities play a critical role in enhancing the overall error growth rate with a larger error growth rate at smaller scales.In addition,initial perturbations with different structures have different error growth features at larger scales in different variables in a regime transitioning from the k^(−5/3) to k^(−3) power law.Error growth with conditional nonlinear optimal perturbation(CNOP)tends to be more upamplitude relative to the GEFS or sub-grid-scale perturbations possibly owing to the inherited error growth feature of CNOP,the inability of convective parameterization scheme to rebuild the k^(−5/3) power spectra at the mesoscales,and different error growth characteristics in the k^(−5/3) and k^(−3) regimes.

新中国成立70年来的中国大气科学研究:天气篇

天气指某一个地区距离地表较近的大气层在短时间内的具体状态.大气中气象要素的空间分布可表现为各种瞬息万变的天气现象,这些天气的分布和变化是由不同时空尺度的天气系统引起的.天气与民生息息相关,其发展演变一直是大气科学研究和应用的重点领域.天气学的发展与观测系统、动力学理论和数值模式的发展密切相连.中国从20世纪50年代初开始建设观测网,到目前已建成门类齐全、布局合理的地基、空基和天基综合气象观测系统.特别是新一代稠密雷达网以及风云卫星系列的发展以及多次大型野外观测试验的实施使我们对天气的认识从宏观的天气形势深入到中小尺度天气系统精细热动力、云微物理结构和演变特征.观测系统的发展同时也促进了理论、数值模式和模拟的发展,中国已由初期主要以引进国外模式为主发展为目前主要发展具有中国自主知识产权的数值模式系统,基于高分辨数值模拟结果对不同尺度天气的发生发展机理和可预报性有了深入理解.此外,天气学已由初期的独立发展逐渐向多学科交叉方向转变,气候和环境的变化与天气演变之间的相互作用已成为大气科学的热点和前沿问题.文章重点回顾过去70年来中国在对天气演变起重要作用的天气现象及其短期变化过程的物理本质、演变规律和预报方法领域所取得的重大科学和技术成果,主要根据正式发表的文献从大气动力学、天气尺度天气特征、台风及热带天气、强对流天气特征、数值天气预报及资料同化,以及天气与气候、大气物理及大气环境等交叉领域六个方面分别加以综述.

河南“21·7”极端暴雨预报的不确定性和误差增长机制

2021年7月19~20日中国河南省郑州市出现了一次极端暴雨过程,小时雨量超过200mm,24h累积雨量超过600mm,造成了巨大的人员伤亡和财产损失.本文重点研究此次降雨预报的不确定性和不同时空尺度误差增长的影响因子.研究结果表明,24h累积雨量和极端小时雨量(7月20日08时,世界时,下同)取决于中层低压、高空辐散及低空急流的强度.基于美国NCEP全球集合预报系统(GEFS)扰动和次网格尺度扰动的集合预报显示,累积雨量的预报不确定性对微小误差的大小和空间结构并不敏感,这表明本次极端暴雨事件具有有限的本性可预报性.研究发现,k^(−5/3)能谱范围升尺度而非升幅值误差增长占主导,小尺度误差增长最快,小尺度误差增大到与大尺度误差相当时,大尺度的误差才开始增长.增长最快的尺度从小尺度向大尺度转移,而且大尺度的误差增长率远小于小尺度.湿对流活动可以增大各尺度特别是小尺度的误差增长率.此外,具有不同结构的初始扰动的不同变量在从k^(−5/3)到k^(−3)能谱过渡的大尺度区域具有不同的误差增长特征.与GEFS扰动和次网格尺度扰动相比,条件非线性最优扰动(CNOP)更倾向于升幅度增长,这可能是CNOP本身最大增长扰动的定义、大尺度模拟使用对流参数化方案无法在中尺度重建k^(−5/3)能谱、以及k^(−5/3)和k^(−3)能谱不同的误差增长特征决定的.

中国日极端降水和趋势

利用中国2000多站50年以上的日降水资料,提取各站6个极端降水指数,即历年最大值(top-1)、历年10个最大值(top-10)累积量、历年总降水量、历年夏季top-1、历年夏季top-10累积量、历年夏季总降水量,分别形成各站各极端降水指数时间序列.统计了历年全国及6个子区域整个研究资料时段内出现top-1和top-10值的总站次,分别形成历年全国及6个子区域极端降水总站次时间序列.各极端降水指数时间序列的趋势分析表明,中国各站top-1和top-10累积量时间序列趋势分布存在较为一致的3个明显趋势区域,即中国东南正趋势区、西北正趋势区和华北负趋势区,但各时间序列的趋势分布区域特征和趋势幅度增减程度不尽相同;正负趋势明显地区的大多数站点趋势增(减)幅度比(趋势幅度与平均值的比值)达10~30%,部分站点达30%以上.top-1和top-10降水全国年总站次时间序列表明了一致的线性增加趋势,平均每十年分别增加2.4站和15站,但年际差别较大;极端降水年总站次表现为三段极端降水多发期,分别出现在20世纪60年代初、90年代中后期和21世纪初,6个区域极端降水年总站次趋势特征与全国年总站次不尽相同,极端降水全国年总站次出现较多的年份在区域上表现不一样.与降水有关的环流形势要素的时间序列趋势分析表明,华北及上游蒙古高原地区呈现明显的位势高度增加趋势,而低层从中国南部沿海地区到华北地区呈现一条南风风速减弱的趋势带和华北地区水汽含量减少的趋势区,这些趋势特征有利于华北地区极端降水的减少.经验回归水平分析表明,50年一遇重现水平从南部沿海的400~600mm减少到西北地区的50mm以下,相比20年一遇重现水平提升率平均达6.8%,但比降水最大值可小一倍以上.

超强台风Soudelor(2015)登陆前后局地强降水的动力过程分析

基于中尺度站点观测、雷达图像、卫星红外云图和NCEP全球业务分析数据资料,详细分析了2015年13号台风Soudelor在华东地区尤其在浙江省沿海产生局地灾害性强降水的分布、强度、触发因子及相应的动力过程.这次台风降水过程可分为4个阶段:第一阶段由台风北侧外围环流偏东风分量与浙江沿海地形相互作用而产生;第二阶段的降水强度最强,累积降水最大,是台风内区主体环流与局地地形相互作用的结果;第三阶段是由于台风内区减弱,主要降水云带在台风东北侧发展而形成;第四阶段由于台风环流与中纬度系统相互作用,使得降水云带"北跳"至江苏省中东部,引起浙江省内的降水迅速减弱.定量计算表明,"地形效应"对局地台风降水增幅起确定性作用,其在台风总体降水中占比达50%左右.台风登陆后结构变化引起水汽输送发生变化,进而引起台风局地降水云带发展的非对称分布,是造成台风强降水空间非对称分布的主要因子.对此个例分析表明,影响中国沿海灾害性强降水不仅与台风强度、结构及外围云带紧密相关,其降水强度会因为台风与沿海地形的复杂相互作用而增加,而其影响时间会因为由大尺度环流引导的弧线路径而延长.此次台风强降水过程的物理及动力分析可以用于指导对未来台风降水灾害的理解、预报及预防,尤其有益于由登陆台风与沿海地形相互作用引起的闪雨、山洪、泥石流及洪涝灾害的预报预警.

Rising future tropical cyclone-induced extreme winds in the Mekong River Basin

热带气旋引起的极端风速对社会的影响使得它成为湄公河流域的最大隐患之一.西北太平洋是影响湄公河流域热带气旋的重要源地之一.从20世纪70年代开始,在越南沿岸登陆的热带气旋强度没有呈现明显的变化趋势.然而,气候模式模拟预测显示西北太平洋的热带气旋强度将会在21世纪内增强,届时将很可能影响到湄公河流域.目前为止,未来湄公河流域的热带气旋活动引起的极端风速将会如何变化尚不明确.因此,本文采用了1个基于海洋大气耦合模型的降尺度技术和5个全球气候模式的输出结果对未来湄公河流域的热带气旋活动进行了模拟.结果显示,相比于1981~2000年,在RCP8.5的情境下,2081~2100年湄公河流域热带气旋的最大风速的重现期将显著缩短.这意味着该区域的热带气旋强度将明显增强.此结果预示着未来热带气旋活动将增加相关灾害的发生,并且这可能会在地区乃至全球范围威胁可持续发展、影响粮食供应和加剧冲突.