台风“黑格比”造成浙东北滞后型暴雨成因分析及多模式预报检验

基于地面常规加密观测及ERA5再分析、热带气旋最佳路径、雷达卫星等资料,利用天气诊断方法探讨了2020年4号台风“黑格比”在登陆北上减弱后南侧滞留的降水云团引发浙东北暴雨成因。受对流层中层副高西脊点偏西及台风北侧高层急流出口区右侧辐合下沉影响,台风云系不对称结构明显,主要分布在南侧。中层冷空气从台风西侧入侵触发中小尺度对流系统,小尺度云团在台风环流内逆时针移动至台风东侧并发展滞留,在浙东北引发强降水。期间冷暖气团（中层MPV1正值和低层MPV2负值）交汇区及中低层锋生大值均可指示暴雨落区,垂直螺旋度也可体现冷空气入侵后台风后倾的垂直结构演变特征;台风东侧持续的西南急流水汽输送有利于夜间浙东北对流降水的维持发展,且水汽低层辐散区对强降水落区有6 h左右的预报提前量。基于SAL定量降水检验证实：大尺度模式由于模拟对流降水演变的欠缺,无法预报出夜间滞后型暴雨增幅;中小尺度模式虽然对暴雨强度刻画相对准确,但大值雨区偏移;ECMWF 3日20:00起报场预报过程累积雨量误差小,较4日08:00起报预报结果更接近实况,但短时暴雨出现时间偏早3～6 h,不利于此类滞后型区域暴雨的预报参考。     

非常规探测资料在江西一次暖区暴雨过程分析中的应用

综合运用风廓线雷达等多种非常规探测资料,对江西省2013年6月29日暖区大暴雨进行分析,并对比6月28日锋面暴雨,归纳总结短时大暴雨发生的一些前兆信号及可用指标。结果表明:1)风廓线雷达能直观反映暴雨区附近中小尺度扰动、近地面弱冷空气入侵、急流脉动发展等特征,1.5—4 km高度层出现16 m/s以上急流对暖区暴雨发生有利,对强降水的发生有1—3 h提前指示作用。2)0.5—1.5 km高度层正的风垂直切变带对应降水发生发展,正速度带中大于4 m/s风速切变对应下游降水加强。3)PWV值在强降水发生前常出现持续上升或波浪上升。PWV值达到65 mm且维持较长时间,同时配合动力触发条件,有利于强降水的发生;PWV值低于60 mm并持续性下降,对应降水趋于减弱停止;强降水落区出现在湿舌前端的PWV等值线密集区内。4)此次强降水主要发生在TBB小于-40℃区域前端的等值线密集区和地面辐合线附近,且地面辐合线的强度、移向与新生单体的发展密切相关;强回波不断在地面辐合线附近合并加强形成"列车效应",雷达回波上逆风区、急流核、速度对等特征的出现有利于强降水的维持。     

"北冕"和"黑格比"台风暴雨对比分析

采用多种物理量综合诊断分析方法,对路径相似的强热带风暴"北冕"和强台风"黑格比"在西进途中进行水汽来源、不稳定层结的维持等方面的研究,探讨台风及其减弱后的低压环流发生大暴雨的成因.结果表明:"北冕"和"黑格比"路径相似,两次台风大暴雨落区比较一致,而它们减弱后台风低压环流仍对桂西南造成强降水,低空急流的存在是台风低压环流维持并造成强降水的主要因素.     

2019年超强台风“利奇马”引发浙江特大暴雨过程分析

利用NCEP FNL 0.25°×0.25°的再分析资料和浙江省中尺度气象站降水资料,从产生强降水的条件来对“利奇马”特大暴雨过程进行诊断分析。结果表明:(1)强降水主要集中在近台风中心的西南部分及其稍远的北部,其中近台风中心为眼壁降水,北部为螺旋云带降水;(2)850~925 hPa水汽通量辐合中心与暴雨落区一致,水汽辐合强度差异是造成台风眼壁强降水落区差异的关键;(3)台风强度大时近中心上升运动强烈,正垂直螺旋度中心值的减小和中心下降对应强降水的发生,低层正螺旋度和高层负螺旋度中心的重叠区对对流性降水落区有一定的指示;(4)本次过程地形增益最明显地区在台州北部,在水汽条件处于劣势情况下出现降水副中心。     

2015年10月4日佛山强龙卷风灾害过程浅析

受1522号台风"彩虹"外围螺旋云带影响,2015年10月4日15:28—16:00佛山市出现了强龙卷风并对多个镇街造成严重灾害。通过灾害现场调查、多普勒雷达观测、群众走访、视频影像等资料,综合比对分析龙卷风的特征,结果表明:该次龙卷风过程发生在台风"彩虹"外围螺旋云带中,发生时的台风中心距离佛山350 km;龙卷风影响时间约为32 min,路径长度为31.7 km,平均时速约为60 km/h,强度达F2级,属于强龙卷,具有"移动速度快、影响范围广、风力破坏强"的特点。     

一次近海快速增强型台风引发金华东部极端强降水成因分析

利用多种观测资料和ERA5逐时再分析资料，对2020年第4号台风“黑格比”（Hagupit）登陆后引发金华东部极端强降水成因进行分析。结果表明：（1）台风主体环流内部中小尺度对流系统的活动是金华东部强降水事件发生的直接原因。棠溪站位于对流活动中心区域（TBB≤-50℃），附近回波强度一直维持在35 dBZ以上，最大回波顶高≥15 km，≥45 dBZ的强回波伸展高度在5 km左右，低于0℃层高度，符合热带海洋型强降水回波特征。（2）低空急流和地形抬升作用是本次强降水过程发生的重要原因。（3）高低空散度的良好配置增强了棠溪站上空的垂直上升运动，促使雨强猛增。（4）低空尤其是925 hPa强烈的水汽输送为强降水的产生和维持提供了充沛的水汽条件。（5）充足的不稳定能量也为强降水的发生提供了有利的环境条件。棠溪站处于假相当位温高能区（>356 K），且K指数一直维持在37℃以上，有利于对流活动的发生和强降水的出现。本次极端强降水过程是在强烈上升运动、水汽的持续输送、地形抬升和不稳定能量释放的共同作用下引起的。     

Sepat台风（0709）登陆过程中眼放大现象研究

台风登陆过程中常发生结构变化,从而引起其强度、路径以及风雨分布等一系列变化,导致登陆台风灾害十分复杂.0709号台风Sepat在穿过台湾岛时结构变化明显,出现了台风眼放大现象.基于上海台风研究所台风资料、FY-Ⅱ卫星半小时一次的遥感资料、台湾雷达逐时合成回波图像以及NCEP每日4次1°×1°格距的再分析资料,研究了Sepat登陆过程中的眼放大现象.结果表明:(1)Sepat登陆台湾后眼墙塌陷、眼消失,但随后在从台湾海峡移向大陆过程中重新出现了台风眼并伴有眼放大现象,眼直径扩展至约600 km;(2)这种眼放大现象,实际上是台风内核区对流云团分裂扩散过程中与外围螺旋云带一起重新发展出的环状结构.台风眼的扩大与眼区下垫面温度降低、低层大气不稳定度减弱、径向外流加强、下沉运动区范围扩大等因素有关;(3)在台风外围,环境干空气侵入台风环流并在其西部形成了弧状湿度锋.锋区既促进对流运动发展,也阻碍了台风眼区云团进一步向外扩散,使对流云团在锋区附近排列成半圆弧状云带,并在台风气旋性环流组织下与台风东部的螺旋云带一起形成了环状眼墙;(4)台风的减弱消亡与其眼区放大现象密切相关.台风眼放大过程中,由于眼内干空气下沉范围加大、对流凝结潜热加热减弱,不利于暖心结构维持,台风强度亦随之衰减.同时,其增强的径向外流在一定程度上阻止水汽能量向台风内核区输入,促使台风内核对流运动的减弱和消亡.     

台风“利奇马”(1909)快速增强事件的降水演变

利用台风路径资料及GPM多星集合降水反演产品(IMERG),分析了“利奇马”台风快速增强(RI)事件的平均降水率、降水(>0 mm·h^-1)和短时强降水(>20 mm·h^-1)的覆盖率随时间的演变。进一步,将RI事件分为RI启动前0~24 h、RI启动期、RI持续期、RI结束前0~24 h,和RI结束后0~24 h等阶段,分析平均降水率、降水和短时强降水发生频率的空间分布。研究结果表明:(1)在整个RI事件中,平均降水率和短时强降水发生频率较高的区域主要集中在台风中心西北方位,但其面积和位置随阶段转换而变化;(2)在RI启动前0~24 h,降水覆盖率的高值区由台风内核逐渐扩大至台风外围,而平均降水率和短时强降水覆盖率在RI启动后才明显增强;(3)在RI启动前0~12 h到RI结束前0~24 h的4个阶段,平均降水率和短时强降水发生频率的高值区都出现在台风移动方向的正前方。     

基于CloudSat卫星分析西太平洋台风云系的垂直结构及其微物理特征

基于2012—2014年CloudSat卫星数据,按照热带气旋强度分类的6个等级以及沿台风中心的径向距离,分析西太平洋台风云系的垂直结构及其微物理特征。研究表明:(1)不同强度的台风云系中均是单层云占主导,多层云中双层云出现比例最高;随着台风强度的增强,距离台风中心250km之内,单层云分布位置更加集中且垂直厚度较厚,而450km之外的单层云一直集中在7~15km,厚度较薄;随着台风强度的增强,距离台风中心250km之内的双层云中的底层云和顶层云均增厚且分布位置更加趋于集中,云间距变窄,而450km之外顶层云和底层云较薄,云间距一直较大。(2)台风云系中,深对流云、高层云、卷云与其他云类型相比,分布的垂直范围较广,出现频率较高,分布的位置会随着台风强度变化和沿台风中心径向距离的增加有明显的变化。(3)随着台风强度的增强,近台风中心5km以上的回波有明显增强,除此高值区外,发展较为成熟的台风,距台风中心450km之外也会出现多个明显的柱状回波高值区。(4)近台风中心液水含量的值和冰水含量的值随强度变化均有明显增加,但外围云系中也有分散的冰水含量高值中心但分布高度相对较低,在10km附近;液水粒子数浓度的高值区域与液水含量的高值区非常对应,而冰水含量的高值区位于冰粒子数浓度的高值区下方,表明小的冰粒子被较强的对流活动带到了高处,而大的冰粒子集中在云系较低处。     

进入杭州湾的两个台风降水特征及成因分析

本文利用FY-4A红外云图和ERA5再分析等资料对"云雀"和"温比亚"两个台风的强降水进行诊断分析。结果表明:"云雀"影响华东期间,西太平洋副热带高压(WPSH)不断加强西伸,台风路径右侧辐散环流维持,台风中心附近垂直风切变指向偏西方向,导致强降水始终集中在台风路径左侧。"温比亚"登陆前,台风中心附近垂直风切变指向西北方向,台风左侧垂直速度强于右侧,有利于强降水发生在台风路径左侧。"温比亚"登陆后,垂直风切变转为指向东北方向,台风右侧垂直速度强于左侧,有利于强降水发生在台风路径右侧。进一步分析指出,"云雀"登陆时期的垂直风切变和WPSH南侧偏东风气流有关;而"温比亚"登陆后WPSH减弱东退和中高纬高空脊东移,垂直风切变指向变化和高空脊后部的西南气流有关。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on