山东冰雹时空分布特征与分类预报指标研究

利用冰雹实况资料、高空探测资料、地面观测资料和EC细网格数值预报资料，统计分析了2012—2021年79次对山东造成较大灾害的冰雹过程的时空分布特征，总结了不同区域、不同大小以及关键月份降雹的关键环境参量特征及阈值。结果表明：①山东降雹具有明显的时空分布特征，降雹主要出现在鲁中地区和鲁北地区；降雹日数年际变化较大，最多年份可达14 d，最少仅为5 d；降雹主要出现在春末夏初，占全年降雹日数的65%；14:00—20:00是冰雹高发时段，占全天降雹的63.3%。②鲁中地区年平均出现大冰雹的次数最多，但半岛地区出现大冰雹的概率更大；大冰雹主要出现在5—6月，占全年大冰雹日数的68.6%。③山东降雹具有较大的对流有效位能、中等及以上强度的深层（0～6 km）垂直风切变、显著的条件不稳定层结和适宜的特征层高度/厚度。④不同区域、不同大小以及关键月份的物理参量的特征和潜势预报阈值都有一定的差别，主要体现在内陆地区、6月降雹、大冰雹较沿海地区、5月降雹、小冰雹的对流有效位能明显偏大、干暖盖指数偏小、深层垂直切变有所增大、抬升凝结高度略偏高、-20～0 ℃层的厚度偏薄。     

贵州威宁1997-2017年冰雹时空变化特征分析

利用威宁县37个人影作业点收集1997～2017年35个乡镇的地面降雹资料,应用统计学方法和ArcGis地理信息分析工具,分析了威宁县冰雹日的年际、月际、日变化特征、空间分布特征以及海拔高程与降雹频次相关性。分析结果表明:威宁县年平均冰雹日数为15.3d,冰雹日数的年际变化总体呈现先减少后增加趋势,但冰雹日数均小于20世纪末期;冰雹日数M-K检验表明从2003年开始冰雹日数呈逐渐上升趋势,在2010年后出现冰雹日数突变现象;冰雹主要发生在4～8月,占整个降雹日的98.36%,春季、夏季多,秋季、冬季少。春季冰雹日数占31.15%,夏季冰雹日数占67.21%;一天内冰雹主要发生在13～21时,占全部冰雹发生次数的85.07%,即午后到傍晚发生频率高;冰雹主要出现在县的北部、中部、西部至西北部、南部至西南部一线,各个乡镇海拔高程与降雹次数存在正相关,相关系数为0.412,降雹次数随地形高程增加呈现增加趋势,降雹次数与经纬度差异没有相关性。以上这些结论可为威宁县冰雹预报指标研究和开展人工防雹提供科学参考,为冰雹防灾减灾提供技术支撑。      

怀化近15年降雹时空分布及其环境参量特征分析

利用怀化地区11个国家气象站2004—2018年降雹日资料、地面和高空常规观测资料,对怀化地区近15年降雹时空分布、冰雹天气的主要形势以及环境参量特征进行了统计分析。结果表明:1)怀化地区中部降雹多,冰雹天气主要发生在2月和3月的午后到傍晚,冰雹直径较小。2)高架对流类是怀化地区降雹最主要的天气形势。怀化一般处于地面冷高压底部或底后部;850 hPa或925 hPa以下为东北风或北风,是一个强冷垫;850 hPa有切变线、干线和锋区;700 hPa有强暖湿气流沿锋面(强冷垫)做斜升运动。3)怀化高架对流冰雹天气发生的主要环境参量特征为700 hPa与500 hPa温度差≥11℃;850 hPa与500 hPa垂直风切变≥20 m/s;700 hPa比湿≥3.28 g/kg;0℃高度为3.2～4.0 km,-20℃高度为6.3～8.0 km,且0℃到-20℃层的厚度≥2.7 km。     

1965—2016年乌审旗冰雹时空分布特征

利用乌审旗3个站的1965—2016年逐时、逐日冰雹资料,分析乌审旗近52a来冰雹发生的空间分布、年际变化、月际变化和持续时间等特征。结果表明,乌审旗近52a平均降雹日数总体呈减少趋势,平均每10a减少0.8d;1965-1990年冰雹较多;2000—2015年相对较少;3—10月为降雹月,主要集中在6—9月,其中8月最多;一日发生降雹的时间主要集中在14—18时,以15—16、17—18时最多;降雹持续时间以5min以内居多;空间分布为北部降雹日数多于中部及南部。     

西北地区初夏冰雹及其环流背景气候特征

应用西北地区194个气象站1961~2001年初夏6月冰雹日数资料,研究了西北地区初夏冰雹发生日数的时空分布特征,讨论了典型多雹年和少雹年大尺度环流的气候特征。结果表明:西北地区初夏冰雹发生日数最高的地方在天山山脉西端、沿祁连山脉及其以南的青海大部(除柴达木盆地)和甘肃甘南高原等海拔较高的地方。在冰雹发生日数最高的地方年代际变化明显,而在冰雹发生日数偏少的地方年代际变化不明显。另外多雹年和少雹年的北半球极涡中心强度、高原高度场、印缅槽、欧洲环流C型天数等环流特征量以及北半球500 hPa环流形势和OLR场均存在着明显差异。     

保定地区冰雹的气候及物理量参数特征

利用保定地区1974~2010年4~10月19个县市气象站冰雹资料,对保定地区近37 a的冰雹气候特征进行了详细统计与研究,在此基础上筛选出典型个例,并基于北京和邢台探空站2000~2010年探空资料,细致分析了典型冰雹日常用物理量参数的阈值。结果表明:保定地区年均冰雹日数的地区差异较大,年均最大降雹日数中心位于西北部山区的涞源,铁路线以西年均降雹日总体多于铁路线以东各市县;冰雹日数与海拔高度呈显著正相关,相关系数达0.924;冰雹日数夏季最多、春季次之、秋季最少,其中6月冰雹出现几率最大;近37 a来,保定地区年冰雹日数均呈不同程度的减少趋势,其中西部山区减少趋势及波动最明显,说明降雹频繁的地区降雹年际波动也大;各物理量参数的阈值可作为预报本市冰雹的参考。     

1968—2017年湖南省冰雹时空分布特征

基于湖南省92个站点1968—2017年冰雹观测资料,采用回归分析、小波分析、主成分分析等方法,研究了湖南冰雹时空分布特征。结果表明,湖南近50年冰雹天气年际下降趋势显著,近20年来有记录的冰雹天气发生频次明显降低。湖南初次降雹的时间都集中在1—3月。冰雹月季变化显著,一年中以3月冰雹最多,2月的次之,从5月份起雹日骤然减少。春季是降雹最多的季节,占雹灾总数的56.06%,冬季的次之,夏季和秋季冰雹发生频率分别仅为全年的2.53%和0.69%。年冰雹日数主要存在4~5 a和19 a左右的振荡周期,20世纪90年代前还存在明显的9~10 a的振荡周期。各季节冰雹日数振荡周期不一。湖南冰雹空间分布呈自湘西北向湘东南递减的规律,年冰雹日数的空间分布特征与春季、冬季冰雹分布特征相似。湘北和湘中地区冰雹天气年际变化以下降趋势为主,湘南地区其气候趋势变化不明显。对湖南近50年冰雹日数进行主成分分析的前3个主要模态,在空间向量场上分别呈现出全省一致型、地势主导型和南北呼应型。     

甘肃省天水市近40a冰雹分布特征

根据甘肃省天水市7个气象站1971～2010年冰雹观测资料,分析了近40 a来该地冰雹变化规律。结果表明:天水市的冰雹分布特征呈现明显的日变化和年际变化。日分布以午后型(13～18时)为主,占全年降雹日数的49.1%;月际变化成单峰型,降雹时段集中在5～8月,占总日数的74.8%;年均累计降雹平均日数为6.4 d,降雹总日数呈逐年下降趋势。拔海高的地区冰雹发生较多,山区多于平川地区。影响天水市的冰雹路径大多呈西北—东南方向,降雹天气以西北气流型为主。     

浙江省２月份连续降雹过程诊断

利用NCEP再分析资料、MICAPS常规资料、雷达产品等资料对浙江省2009年2月23—26日连续降雹天气过程进行了诊断分析。结果表明:此次连续降雹过程降雹区均出现在高低空急流轴交叉点南侧约1个纬度,底层辐合区;850 hPa较强的水汽辐合和湿舌为此次降对流过程提供了充沛的水汽条件,上干下湿结构使对流性不稳定增强,逆温层存在使大量不稳定能量储积起来,底层冷空气渗透触发强对流发生;Ic500-700指数对此次降雹过程有较好指示意义;2月份冰雹雷达回波特征有别于春、夏季冰雹回波特征,冬末春初冷空气势力仍较强,对流强度偏弱,回波顶高偏低,其三体散射特征不明显,VIL值较小。     

基于灾情信息的1981—2017年北京地区降雹特征

该文对1981—2017年北京地区1010个高精度冰雹灾情信息进行统计分析。从年代际变化看,1981—1990年平均降雹日数为10 d,1991—2000年和2001—2010年年平均降雹日数均有所减少（5.67 d和4.33 d）,而从2011年起,年平均降雹日数急剧增加到21 d。1981—1995年年平均最大冰雹直径总体呈增加趋势,2002年开始总体较小。从年变化看,冰雹日数的年变化呈明显的单峰型即初夏峰型,4月起降雹日数逐渐增加并在6月达到峰值,其后缓慢下降。从空间分布看,北京地区的降雹分布十分广泛,但高频次降雹区域主要集中在北京西北部延庆区,平均每年至少发生两次降雹,此外降雹高值区还出现在城区的海淀区。2010年后,降雹范围明显增大,同时降雹分布也由相对集中变为相对均匀。     

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.