登陆广东热带气旋中尺度降水分布变化特征

利用每小时地面观测资料和卫星遥感资料 ,以 1 999～ 2 0 0 1年在珠江三角洲地区登陆的热带气旋为研究对象 ,从合成分析和个例分析两方面揭示了登陆广东热带气旋降水的中尺度特征及其分布变化。结果表明 ,热带气旋登陆前后中尺度强降水分布发生明显变化 ,登陆后降水不对称性加大 ;热带气旋登陆后中尺度强降水分布随时间变化 ,登陆后第 1 0个小时之前 ,中尺度强降水基本上分布于热带气旋中心附近 ;而热带气旋登陆第 1 0个小时之后 ,中尺度强降水具有明显的“离心”或“偏心”特征。     

登陆海南的热带气旋中尺度降水分布变化特征

利用每小时地面观测资料和卫星资料,以1996-2005年在海南岛登陆的热带气旋为研究对象,按照气旋移动路径将其分为4大类,从4类不同路径的7个个例分析揭示了登陆海南热带气旋降水的中尺度特征及其分布变化.结果表明,不同路径的热带气旋登陆前10个小时之内,中尺度强降水基本上分布于热带气旋中心附近;而热带气旋登陆后,中尺度强降水开始出现明显的"离心"或"偏心"特征.不同路径的热带气旋在登陆前后,其最大降水中心的强度变化也有明显差异.登陆前后,中尺度强降水基本均出现在气旋中心西南到东南侧100～200km内,表现出明显的南北不对称.个例分析也证明,热带气旋强降水在空间和时间上都具有明显的中尺度特征.     

登陆粤西的热带气旋降水特征分析

利用1949～2000年《热带气旋年鉴》资料,对51年来登陆粤西的热带气旋在陆地维持时间、不同强度的降水之间的分布、相同量级强降水的分布等进行统计分析,揭示登陆粤西热带气旋降水分布实况和特征。结果表明,登陆粤西的热带气旋在登陆后的维持时间和其造成陆地强降水范围成正相关的关系;热带气旋造成不同强度(暴雨、大暴雨、特大暴雨)的降水在其路径左右侧分布,雨强越大,出现的几率越少;热带气旋登陆后造成的暴雨量级降水在热带气旋路径右侧比左侧产生的几率更大;而大暴雨、特大暴雨落在路径左侧的可能性比落在右侧的可能性大。     

1960—2003年我国热带气旋降水的时空分布特征

利用1960—2003年登陆影响我国的热带气旋及其造成的降水资料, 对44年间登陆我国热带气旋降水时空变化特征进行统计分析。结果表明:热带气旋降水与热带气旋登陆活动相一致, 主要发生在5—11月, 其中7—9月为盛期; 热带气旋降水量以及热带气旋暴雨日数的分布是自南向北、从沿海到内陆迅速减小, 最大出现在海南和华南、东南沿海地区; 热带气旋强度越强其最大过程降水一般也就越大, 但是两者并非严格的线性关系; 1960年以来, 我国受热带气旋影响的绝大部分地区热带气旋降水呈波动下降的趋势。     

利用TRMM资料分析2002年登陆广东的热带气旋降水分布特征

用2002年3个热带气旋登陆广东的过程中自动站的降水资料, 对TRMM准全球、准实时的3 h降水估测资料进行了检验, 表明该资料与地面3 h降水有很好的相关性, 可以反映出热带气旋3 h降水变化的特征。利用该资料分析了这3个热带气旋登陆过程中不同半径、不同方向降水的时空变化特征, 并分析了不同热带气旋之间降水差异的大尺度环流背景。研究发现, 3个热带气旋登陆过程中心附近降水沿半径方向存在收缩和扩展的变化, 除了低层水汽输送的变化和地形对降水造成影响之外, “北冕”和“黄蜂”都发现热带气旋外围降水加强会导致其中心附近降水减弱, 这与以往的观测及研究成果类似。     

登陆热带气旋影响湖南并造成强降水的气候特征

利用1951～2007年热带气旋、湖南降水资料,统计分析了登陆影响湖南的热带气旋时空分布,及造成的强降水特征.结果表明:57年中登陆影响湖南的热带气旋共161个,平均每年3个,主要出现在7～9月,影响热带气旋主要为台风或以上强度;影响湖南的热带气旋登陆地点以广东、福建最多,强度达强热带风暴或以上的热带气旋可造成极端暴雨降水,时间主要出现在8月.20世纪90年代以后暴雨强度呈加大趋势.     

1956～2012年浙闽登陆热带气旋降水精细化观测统计分析

选取我国东南沿海热带气旋登陆数目多、经济发达的浙江和福建两省,利用国家级地面气象站逐小时降水观测资料,结合热带气旋降水客观分离方法,对1956~2012年（共57年）浙、闽两省沿海登陆热带气旋降水开展客观分离,统计分析热带气旋登陆期间降水精细化时空分布特征。结果表明:热带气旋平均路径在登陆前6小时至登陆后24小时呈西北行,累积降水具有明显非对称分布特征,与主要水汽辐合区相吻合,登陆后24小时至48小时的降水分布与鄱阳湖水体以及局地地形有密切联系;伴随登陆进程,降水分布呈现显著变化,登陆前,浙、闽两省降水较强;登陆后,降水范围向内陆扩展到浙、闽两省以外地区;登陆点聚类分析指出,所有类别的较强降水时段均位于登陆前12小时至登陆后6小时,但不同类别的降水分布和演变特征具有显著差异,这种差异与局地地形和热带气旋环流所处位置关系密切;小时强降水统计分析显示,伴随着登陆进程强降水频次分布逐渐变化和向内陆地区推进,高频次强降水主要出现在登陆前、后6小时的浙、闽两省沿海地区,且以两省交界附近地区最为集中,与该地区明显的高大地形分布有着密切的关系。两省各台站由登陆热带气旋带来的小时降水极值差异较大,从10到143 mm均有分布,大部分极值在30至60 mm之间。其中,极值大于50 mm的站点主要分布在沿海地区,在浙、闽交界处较为集中,与小时强降水的频次分布一致。     

影响青田热带气旋的时空分布及降水特征分析

普查了1971--2008年影响青田的热带气旋个例,并按不同登陆地点和移动路径进行分类统计,分别对青田县热带气旋降水的时空分布特征进行统计分析。结果表明,38a中影响青田的热带气旋年均1．7个;8月分影响频数最高,平均过程雨量最大;平均过程雨量空间分布特征为东部多于西部,南部多于北部,本县东南部为热带气旋暴雨中心。通过分析,初步了解不同路径热带气旋降水的分布特征,为今后的热带气旋降水预报服务提供参考依据。     

利用区域站资料分析台州南登型热带气旋的降水时空分布

利用2004--2010年时间段的区域自动站雨量资料序列,选择同期登陆台州以南到闽中以北沿海的热带气旋共18例,统计分析其降水的时空分布特征,初步解释了降水分布差异性成因。结果表明：登陆闽北至浙南沿海的热带气旋平均面雨量是登陆闽中沿海的2．1倍。登陆闽北至浙南沿海的热带气旋,登陆前后平均雨量分别占总雨量平均的67％和33％;而登陆闽中沿海的热带气旋,登陆前后平均雨量刚好相反,其比例分别为33％和67％。台州地区热带气旋降水强度与主导风向关系密切,而主导风向则更多取决于登陆区段。     

登陆广东热带气旋的降水分布和移速变化

利用1980～2001年登陆广东的72个热带气旋的路径和降水资料,计算了热带气旋登陆前后的移动速度和加速度,比较分析了热带气旋主要降水落区与热带气旋移速变化的关系.计算结果统计表明登陆广东的热带气旋中,有66.1%的个例在登陆时移速加快.当主要降水落区位于热带气旋前进方向右侧时,热带气旋的12小时平均加速度为正的占了大部分(81.8%);当主要降水落区位于热带气旋前进方向左侧时,近八成(78.6%)的热带气旋平均加速度为负.这些统计结果进一步从诊断事实上说明了地形以及非绝热加热等因子对台风移动的可能影响.     

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.     

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.     

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.     

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     

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.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.