基于高时间分辨率快电场变化资料的北京地区地闪回击统计特征

利用2014年北京闪电网观测到的4站及以上同步高时间分辨率闪电快电场变化资料,对北京地区5次雷暴过程中304次正地闪和1467次负地闪的回击特征进行了统计分析,主要包括:回击次数、10%~90%上升时间、下降时间、半峰值宽度、回击间隔、回击峰值电场强度、回击间隔和回击序数的关系等。结果表明,正、负地闪中单回击地闪所占比例分别为91.1%和24.2%,单次负地闪的平均回击次数为3.8次,观测到的最大回击数可达20次。304次正地闪首次回击的10%~90%上升时间、下降时间和半峰值宽度的算术平均值分别为4.2μs、14.5μs和6.2μs;29次正地闪继后回击对应值分别为3.6μs、12.6μs和5.7μs;1467次负首次回击的对应值分别为2.4μs、23.9μs和5.3μs;4109次负继后回击的对应值分别为1.7μs、19.5μs和3.4μs。正、负地闪回击间隔的几何平均值分别为106 ms和59 ms。负地闪回击间隔呈对数正态分布,平均回击间隔随着回击序数的增加有逐渐减小的趋势。最后,还对70次正回击、421次负首次回击和789次负继后回击峰值电场进行了统计,将其归一化到100 km的平均值分别为11.2 V/m、7.2 V/m和5.0 V/m。平均来看,负地闪首次回击峰值电场比继后回击峰值电场大1.4倍,但是有23.5%的继后回击峰值电场大于其对应的首次回击。     

大兴安岭地区地闪回击辐射场特征

利用慢电场变化测量仪所获取的观测资料详细分析了大兴安岭地区地闪回击辐射场特征。结果表明,35次正地闪首次回击的慢前沿、10%～90%平均上升时间分别为7.8μs、4.5μs,其中11次正地闪首次回击的过零时间、负反冲深度平均值分别为34μs、23%。76次负地闪首次回击的慢前沿、10%～90%平均上升时间分别为3.5μs、1.9μs,继后回击的慢前沿为1.4μs,其中15次负地闪首次回击的过零时间、负反冲深度平均值分别为51μs、52%。另外,正地闪首次回击的半峰值宽度大于负地闪首次回击,平均值分别为13.6μs、5.6μs。与国内外已有结果的进一步对比发现,大兴安岭地区的地闪回击辐射场特征与瑞典、美国弗罗里达的地闪回击辐射场特征有较好的一致性,但与我国内陆高原的地闪辐射场特征有明显差异。     

广东一次雷暴过程负地闪先导的电学特征分析

利用 0 .0 8μs时间分辨率的大容量慢天线电场变化测量系统在广东从化地区一次雷暴过程中观测得到的 44次负地闪电场变化波形 ,对负地闪回击前 2 0 0 μs内的先导电场变化波形进行了分析。发现负地闪首次回击前的先导电场变化波形 ,按最后一个先导脉冲与相应回击间电场变化特征大致可分为三类。通常负地闪先导过程由若干脉冲式变化组成 ,首次回击前先导脉冲间的平均时间间隔为 1 5.8μs(均方差 5.3μs) ;继后回击前直窜 -梯级先导脉冲间的平均时间间隔为 9.4μs(均方差 5.5μs)。首次回击前最后一个先导脉冲与首次回击间的平均时间间隔为 1 2 .7μs(均方差 7.8μs) ,最后一个先导脉冲幅值与回击峰值之比的平均值为0 .1 (均方差 0 .0 4 ) ,且两者之间有很好的相关性 ,并用回击传输线模式对这一关系进行了解释。     

闪电电场变化波形时域特征分析及放电类型识别

对闪电电场变化波形进行时域特征分析,研究闪电放电类型识别方法,是闪电探测系统研制工作的重要组成部分.利用闪电快电场变化资料,研究分析闪电波形的时域特征,分别统计负地闪回击和双极性窄脉冲波形的上升时间、下降时间、脉冲宽度等多个特征参数,得出负地闪回击波形上升时间平均值为2.9μs、下降时间平均值为89μs、脉冲宽度平均值为15.4μs,而双极性窄脉冲波形的上升时间平均值为1.7μs、下降时间平均值为2.1μs、脉冲宽度平均值为2.4μs.通过对闪电波形参数的统计分析,给出了不同放电过程的识别判据,实现了对地闪回击、双极性窄脉冲的自动识别,并利用实测数据进行了验证.结果表明,制定的波形识别判据对负地闪回击的识别效率可达到90%,对正地闪回击与双极性窄脉冲事件也有较高的识别率.     

正地闪和负地闪预击穿脉冲序列的统计分析与对比

2009~2010年夏季,在大兴安岭林区利用闪电快、慢电场变化测量仪组成的网络对自然闪电进行了多站同步观测。本文选取2010年夏季3次过境雷暴过程中具有4站以上同步的资料,同时对表现出明显预击穿过程的37次正地闪和56次负地闪的预击穿脉冲序列进行了统计分析。统计的主要参数包括:脉冲序列的总持续时间(Total Duration),脉冲序列和首次回击之间的时间间隔(PB-RS Separation),预击穿过程到首次回击的时间间隔(Pre-RS Interval),单个脉冲持续时间(Individual Pulse Duration),相邻脉冲时间间隔(Interpulse Interval)等。对于负地闪,相应参数的算术平均值为4.1 ms、55.4 ms、56.0 ms、8.8μs和111.0μs,几何平均值为3.7 ms、35.6ms、36.5 ms、7.4μs和98.2μs;对于正地闪,相应参数的算术平均值为4.5 ms、75.6 ms、77.3 ms、11.5μs和297.3μs,几何平均值为3.0 ms、57.8 ms、60.0 ms、10.0μs和217.9μs。对比发现,正地闪预击穿脉冲序列相对负地闪预击穿脉冲序列持续时间更长,和首次回击的时间间隔更大,其单个脉冲更宽,在整个序列中排列更稀疏。计算了正、负地闪最大预击穿脉冲幅值和首次回击幅值的比值(PB/RS,PB代表最大预击穿脉冲幅值,RS代表首次回击幅值),通过和其他研究结果的对比,发现负地闪有PB/RS随纬度增大而增大的趋势,而正地闪没有。另外,检验了首次回击前地闪电场波形与BIL模型(Breakdown Intermediate Leader,BIL)的符合情况,发现只有很小比例的电场波形符合BIL模型。     

地闪回击的微秒级辐射场特征及近地面连接过程分析

利用１μｓ时间分辨率的慢天线电场变化仪在甘肃中川地区雷暴过程中测量得到的大量地闪辐射波形地地闪回击辐射场特征及回击的慢前沿过程进行分析,发现１８次正地闪和８５次负地闪产在周前沿过程上升时间为１９．２μｓ和９．４μｓ,８４次负地闪继后回击的前沿过程为４．３ μｓ。ＹＹ ＵＤＡ Ｏ ３．１μ;     

青藏高原东北部地区闪电特征初步分析

利用VHF辐射源三维定位系统及快、慢天线资料,对青海大通地区5次雷暴过程中云闪、负地闪、正地闪的起始高度、持续时间、辐射源数目及正、负地闪云内放电过程的持续时间和回击次数进行了统计分析.研究表明,该地区闪电持续时间较短,平均＜0.5 s;正、负地闪首次回击发生前均有较长时问的云内放电过程,正地闪的云内放电过程持续时间略长于负地闪;负地闪的回击次数较少,平均为2.5次,其中40％的负地闪只有1次回击,而正地闪回击次数均为1次;云闪的起始高度最高,负地闪的起始高度低于云闪,正地闪的起始高度最低;云闪产生的辐射源数目最多,负地闪少于云闪,正地闪产生的辐射源数目最少.     

广州高建筑物雷电回击光脉冲特征分析

为了深入认识负地闪放电过程中光辐射信号的特性, 对广州高建筑物雷电观测站所获得的回击光脉冲波形进行了分析。对观测到的88例负地闪事件中的184次回击(包括60次下行闪电首次回击、58次下行闪电继后回击、66次上行闪电继后回击)的光脉冲特征进行了统计分析, 结果表明: 下行闪电首次回击光脉冲10%~90%上升时间T₁的算术平均值/中值为32.5/31.4μs, 20%~80%上升时间T₂的算术平均值/中值为22.6/22.4μs, 半峰宽度T₃的算术平均值/中值为131.1/117.0μs。下行闪电继后回击光脉冲T₁的算术平均值/中值为30.4/27.7μs, T₂的算术平均值/中值为19.5/17.6μs, T₃的算术平均值/中值为153.6/142.6μs。在21例下行多回击负地闪事件中, 光脉冲回击间隔时间在12.6~368.6 ms范围之间, 算术平均值为78.7 ms, 有14%闪电事件存在继后回击光脉冲峰值大于首次回击的情况。上行闪电继后回击光脉冲T₁的算术平均值/中值为27.5/24.3μs, T₂的算术平均值/中值为17.0/15.7μs, T₃的算术平均值/中值为132.2/124.5μs。总体上, 下行闪电首次回击的光脉冲上升时间最长、下行闪电继后回击次之、上行闪电继后回击最小; 下行闪电继后回击脉冲半峰宽度比下行闪电首次回击及上行闪电继后回击的更大。      

正地闪和负地闪预击穿脉冲序列的统计分析与对比

2009～2010年夏季,在大兴安岭林区利用闪电快、慢电场变化测量仪组成的网络对自然闪电进行了多站同步观测。本文选取2010年夏季3次过境雷暴过程中具有4站以上同步的资料,同时对表现出明显预击穿过程的37次正地闪和56次负地闪的预击穿脉冲序列进行了统计分析。统计的主要参数包括：脉冲序列的总持续时间（Total Duration）,脉冲序列和首次回击之间的时间间隔（PB-RS Separation）,预击穿过程到首次回击的时间间隔（Pre-RS Interval）,单个脉冲持续时间（Individual Pulse Duration）,相邻脉冲时间间隔（Interpulse Interval）等。对于负地闪,相应参数的算术平均值为4.1 ms、55.4 ms、56.0 ms、8.8 μs和111.0 μs,几何平均值为3.7 ms、35.6 ms、36.5 ms、7.4 μs和98.2 μs;对于正地闪,相应参数的算术平均值为4.5 ms、75.6 ms、77.3 ms、11.5 μs和297.3 μs,几何平均值为3.0 ms、57.8 ms、60.0 ms、10.0 μs和217.9 μs。对比发现,正地闪预击穿脉冲序列相对负地闪预击穿脉冲序列持续时间更长,和首次回击的时间间隔更大,其单个脉冲更宽,在整个序列中排列更稀疏。计算了正、负地闪最大预击穿脉冲幅值和首次回击幅值的比值（PB/RS,PB代表最大预击穿脉冲幅值,RS代表首次回击幅值）,通过和其他研究结果的对比,发现负地闪有PB/RS随纬度增大而增大的趋势,而正地闪没有。另外,检验了首次回击前地闪电场波形与BIL模型（Breakdown Intermediate Leader, BIL）的符合情况,发现只有很小比例的电场波形符合BIL模型。     

甘肃平凉地区正地闪特征分析

利用雷电定位和雷达观测资料对甘肃平凉地区正地闪特性进行了分析。结果表明：正、负地闪回击的上升时间分布范围基本一致，大约在3—20μs之间，其平均值负地闪为8．33μs，正地闪为10．7μs。负地闪回击后的过军时间分布范围较广，在10-130μs之间，其平均值为51μs；正地闪回击后的过军时间分布范围比负地闪要小得多，在10一50μs之间，其平均值为19．67μs。负地闪的反冲深度dp为32％，正地闪为55％。在正负地闪的日变化中，负地闪有两个峰值分别出现在01：00和13：00(北京时，下同)，而正地闪在下午18：00出现一个极大值，正负地闪数的分布呈反相关。降雹时间的峰值与正地闪峰值时间有比较好的一致性，正地闪的发生与云中固态水成物粒子的沉降有关。     

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.     

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.     

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     

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.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;