1961—2021年四川省区域性暴雨过程时空变化特征

利用四川省156个国家气象观测站1961—2021年逐日降水资料,运用暴雨过程综合识别方法及评价指标,探讨四川省区域性暴雨过程时空变化特征。研究表明：1961—2021年四川省共出现875次区域性暴雨过程,过程次数逐年变化整体呈弱增长趋势,综合强度在20世纪90年代到21世纪初持续偏弱,21世纪以后呈现较明显增强趋势。四川区域性暴雨过程主要发生在6月下旬到9月上旬,大多持续1～2 d,区域性暴雨日数大值中心主要分布在盆地西部和东北部,阿坝州中部和东部、甘孜州东南部及攀西地区东北部,6—8月区域性暴雨日数大值中心从盆地东部逐渐向西部变化,9月则在盆地北部;盆地各月平均过程雨量以西部和东北部最强,攀西地区6、9月区域性暴雨日数偏少,但中部和东北部过程雨量强度未明显减弱。     

四川省近10年极端小时降水时空分布特征

利用2012~2020年四川省156个国家气象观测站小时降水资料,以四川盆地、川西高原和攀西地区为考察重点,统计分析了全省极端小时降水的时空分布特征。结果表明:（1）四川省各站极端小时降水阈值、发生频次、平均强度及贡献率差异明显,高值区主要集中在盆地和攀西南部;盆地多站极端小时降水阈值在50 mm/h以上,小时降水极大值超过80 mm/h。（2）四川省极端小时降水事件主要集中在7月和8月,其中50 mm以上的小时强降水事件占比超过1/3;盆地、川西高原和攀西地区极端小时降水发生频次分别在7月、6月和8月达到最高,而小时强降水事件分别在8月、7月和6月出现最多。（3）四川省极端小时降水频次日变化峰值出现在02时,具有单峰和夜发特征,其中盆地、川西高原和攀西地区主峰值分别出现在05时、21时和02时;四川省50 mm以上小时强降水事件夜发占比达63.5%,各区域出现高峰时段差异大。      

近50年我国持续性暴雨的统计分析及其大尺度环流背景

根据1951～2005年中国大陆730个台站的逐日降水资料和持续性暴雨发生的特点, 提出了采用局地持续性暴雨和区域持续性暴雨事件的两种客观定义来描述和统计近50年我国持续性暴雨时空特征及其变化。单站逐日降水量连续三天或三天以上均大于等于50 mm为一次局地持续性暴雨；区域持续性暴雨指在一定区域范围内连续三天降水量总和大于等于100 mm且每天降水量大于等于25 mm的面积超过某一阈值 (详细定义见正文）。根据局地持续性暴雨定义, 指出: 近50年中国局地持续性暴雨事件主要发生在江南和华南地区, 发生季节以6月为最多；根据区域持续性暴雨定义, 统计分析了四类典型的区域持续性暴雨类型, 分别是: 渤海辽西型、北方经向型、南方锋面型和华南低压型。其中南方锋面型又可根据持续性暴雨易发生的地理位置分为江淮型、江南型和华南型三种。对这六类区域持续性暴雨的历史个例进行同比分析, 研究了不同类型持续性暴雨发生的季节性和年际变化,以及它们在大尺度环流背景方面的共性特征。     

基于GIS的四川省区域性暴雨降水分布的空间插值方法与面积估测

暴雨是四川省主要的灾害性天气之一,每年由暴雨引发的次生灾害在全省造成严重的人员伤亡和经济损失。本研究利用四川省5006个气象站逐日降水量资料,采用距离权重反比法(IDW)和普通克里金插值法(Ordinary Kriging)法对2018年8次区域性暴雨过程降水分布进行计算,统计出不同降水等级的面积及面积比例,并对两种插值方法的的计算精度进行了评估。结果表明:(1)在8次区域性降水过程中的距离权重反比法(IDW)和普通克里金插值法(Ordinary Kriging)法的平均相对误差均低于7%,有较高的计算精度;(2)2018年区域性暴雨降水主要分布于盆地西北部、盆地南部和盆地东南部地区,川西高原与攀西地区降水量相对较小;(3)8次区域性暴雨过程中,过程累计降水量>50mm的面积在20247~158144km2,面积比率在4.17%~32.54%。分析发现,暴雨面积能更较好的反映出一场暴雨天气过程的影响范围,同时也可以作为区域暴雨的判别指标。      

四川省降雨灾情时空分布及其与雨量相关特征分析

利用四川省2002—2020年降雨灾情数据和156个国家气象观测站及5727个区域气象观测站逐日、逐小时降雨资料，分析四川省降雨灾情时空分布及其与雨量特征的联系。结果表明：四川省近年来降雨灾情数量增长明显，盆地西部、南部灾情数量最多，密度最大，凉山州和盆地东北部死亡人数最多。灾害主要发生在6—9月，灾情分布有从盆地东北部、南部向西部发展，最后到东北部的趋势。盆地在有大暴雨出现时灾害发生可能性最大，致灾频率50%以上，暴雨致灾频率20%～40%;攀西地区暴雨出现时致灾频率20%～30%;川西高原暴雨天气过程较少，大雨出现时致灾频率最大，为10%～30%。最大小时雨量盆地区在10 mm以下的灾害主要发生在盆南和盆东北，盆西在各个雨量等级范围内占比都较大，攀西地区灾害主要集中在10～40 mm，川西高原为20 mm以下。最大日降雨量小于50 mm的灾害主要分布在盆南，超过300 mm的主要发生在盆西北，50～100 mm以盆南和盆西南为主，攀西地区50～100 mm占比最大，川西高原为25～50 mm。     

青藏高原周边地区持续性暴雨特征分析

长江上游的暴雨是造成该区域和长江中下游洪涝的主要因子,研究长江上游的青藏高原周边地区持续性暴雨特征对防灾减灾有着重要意义。应用历史天气图资料、NCEP 1°×1°再分析资料和国家气象信息中心提供的气候整编降水资料,采用统计和天气学方法,分析了1961 2011年青藏高原周边地区持续性暴雨特征。研究表明,青藏高原周边地区局地持续性暴雨通常持续3~4天,持续时间最长的暴雨发生在湖北武汉,为10天。整体上,高原地区较周边地区暴雨发生率相对低,局地持续性暴雨有4个降水高频中心,西藏东南部降水高频中心的波密发生频次最高,为15次;四川西部至中东部暴雨高频区持续性暴雨发生范围最广;另2个高频区为云南南端及湖北中东部地区。青藏高原东侧的西南地区区域持续性暴雨以持续3天为主,7月发生频率最高,21世纪以来,暴雨中心有向东移动的趋势。通常持续性暴雨过程伴随高原低值系统活动,其中西南低涡是最主要的影响系统。     

湖南夏季降水日变化特征

利用湖南96个测站13年的逐时自记降水资料, 分析了夏季（6~8月）降水日变化特征。结果表明, 湖南夏季降水日变化呈现显著的区域差异。湘东南降水量、 降水频次峰值主要出现在午后到傍晚, 而其它地区的降水峰值一般出现在清晨。进一步分析显示, 降水频次峰值出现时次分布更集中, 区域特征更鲜明。湘西北、 湘东南区域平均的累积降水量、 降水频次及降水强度的日变化在清晨和午后均呈双峰型特征。湘西北主（次）峰值出现的时间大致与湘东南次（主）峰值出现的时间对应。同时, 降水日变化与降水持续时间密切相关。持续5~10 h降水事件是持续1~4 h事件与持续10 h以上事件降水量峰值出现时间发生显著变化的过渡降水事件。持续1~4 h（10 h以上）的降水事件的极值降水始发时间为午后至傍晚（夜间）。在不同持续时间的降水事件中, 持续2 h降水的累积量最大。     

1980—2012年5—9月川渝盆地小时强降水特征研究

利用四川和重庆123个气象观测站1980—2012年小时降水资料,分析川渝地区主汛期5—9月小时强降水频次、强度和持续性等时间演变和空间分布特征。结果表明,≥20、≥30和≥50 mm·h-1三种强度阈值强降水时间演变上,1980—2012年年际和日变化具有较好的一致性,三种强降水年平均频次分别为504、184和28次。≥20 mm·h-1 强降水空间分布上,在山地地形动力辐合抬升,以及盆地西部较大的地形梯度作用下,≥20 mm·h-1强降水高频次区主要分布于盆地西北部的龙山山脉、西南部雅安及乐山周围与盆地过渡区。≥20 mm·h-1强降水频次的日峰值空间分布上,盆地南部主要出现在20:00—01:00（北京时,下同）,而盆地中部、北部和东部主要在02:00—07:00。持续不同小时时间尺度的强降水事件日变化上,具有双峰型结构,午后为第一个降水峰值,20:00至第二天07:00为第二个峰值,白天多为短时间（2~6 h）强降水事件,而傍晚开始至第二天清晨,持续2~18 h强降水事件均有发生。不同开始时间强降水事件的强度与频次和降水量具有一致性的日变化特征,呈现单峰型结构,峰值主要发生在18:00—06:00,且不同开始时间事件频次和降水量空间分布上,白天（09:00—20:00）相对于夜间（21:00—08:00）偏小,即夜间强降水事件特征表现明显。     

西南地区东部区域性暴雨事件的客观识别及其变化特征

利用区域性极端事件客观识别方法(OITREE)和1961-2018年西南地区东部118站逐日降水资料对该区域近58年的区域性暴雨事件进行了识别,确定了相应的OITREE方法的参数组,共识别得出246次区域性暴雨事件,其中25次达到极端强度,2004年9月3-6日发生的区域性暴雨事件是西南地区东部近58年来综合强度最强的一次区域性暴雨事件。进一步分析表明:西南地区东部区域性暴雨事件的持续时间主要为2天,最长为5天;事件的累积强度集中在500～1000 mm之间,累积面积集中在10×10~4～20×10~4km~2。西南地区东部区域性暴雨事件多发于5-9月,其中7月最多,占总发生频次的31.7%。四川东部和重庆西部的平原区是暴雨事件的频发和强度中心地区。近58年西南地区东部持续性区域暴雨事件增多[0.57次·(10a)~(-1)],持续时间延长[1.2 d·(10a)~(-1)],最大影响范围扩大[5.7×104km2·(10a)~(-1)],极端强度也增强[73.4 mm·(10a)~(-1)]。     

四川地区短时强降水事件时空演变特征研究

利用四川地区自动气象站逐小时降水观测资料,分析了2010~2019年5~9月短时强降水事件24h累计降水量、频次和强度的时空分布特征,探讨了短时强降水事件发生的频次、极值分布及其与地形、海拔高度等的关系。结果表明:四川地区平均24h累计降雨量基本在50mm以上,盆地东北部、西南部、南部及阿坝州东部甚至超过100mm,最大值出现在广安,达175mm。四川地区短时强降水事件开始时间的日变化特征表现为“V”型结构的夜间峰值位相,事件持续时段多为傍晚至凌晨,时长可达10h以上,最长甚至可持续22h。在强降水事件极值的日变化上,极大值频次和降水量呈单峰结构,在03时达到最大,其后逐渐减小至15时达到谷值,而后再次增大;降水强度呈弱双峰结构,分别在04时和16时达到谷值,13时和18时达到峰值,其日变化呈“增-减-增-减”的特征。四川短时强降水事件与复杂地形有密切的关系,5~6月事件活跃区在四川盆地中部,7月在盆地西部的龙门山脉一带,8月在雅安、乐山附近,9月在盆地北部且频次明显减少;短时强降水事件的最大小时雨强可达80mm以上,出现在7~8月的盆地西部龙门山一带和南部地区。短时强降水事件随着海拔高度的增加,发生频次和日数逐渐减少,海拔2000m以上地区基本无强降水发生日出现( 峨眉山气象站例外)。      

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.     

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.     

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.     

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     

Information for Authors

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.     

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.     

INFORMATION FOR AUTHORS

正Aims Scope Advances in Atmospheric Sciences(AAS)is an international journal on the dynamics,physics,and chemistry of the atmosphere and ocean with papers across the full range of the atmospheric sciences,co-published bimonthly by Science Press and Springer.The journal includes Articles,Note and Correspondence,and Letters.Contributions from all over the world are welcome.     

Editorial

As we will soon celebrate the 90th anniversary of the founding of the Chinese Meteorological Society （CMS）,Acta Meteorologica Sinica （AMS）,which was originally named as Bulletin of the Chinese Meteorological Society,has gone through 89 years of development and excitement since her first issue in July 1925.According to archived documents （CMS Editorial Committee,1925）,AMS was founded to report the research findings of Chinese meteorologists,record their recommendations for improving meteorological services,and share their common meteorological interests in order to promote the growth of AMS such that more members could be inspired to conduct atmospheric research and meteorological knowledge would be better disseminated to and benefit the general public.By upholding and carrying forward this purpose,AMS has published many highly valuable scientific papers.Some could be treated as classical articles,which have produced important influences on both domestic and international meteorological communities and the related fields.