海南省澄迈县雷暴气候特征及其灾害防御

通过统计分析海南省澄迈县1959~2004年逐日雷暴资料,找出雷暴发生时空分布特征,统计1995~2004年10a雷暴发生的影响天气系统,计算出各天气系统影响下雷暴发生的概率。分析结果表明:澄迈县雷暴日46a平均雷暴频次437次,年际变化呈波动减少趋势,5~8月是雷暴发生的高发期,占全年雷暴的53%,16~17时是一天中发生雷暴的最高期,西南方向发生的雷暴略多于其他方向,澄迈县受西南低压槽、南海低压槽和副热带高压等天气系统影响时发生雷暴的概率较大。     

西南低压槽影响下的海南岛地闪活动特征

采用2010—2018年的海南岛天气分型资料和闪电定位数据,统计分析海南岛在西南低压槽影响下地闪发生概率的时空分布特征,结果显示:在西南低压槽天气影响下,海南岛地闪主要出现在4—9月;地闪发生概率月分布曲线呈双峰特性,以8月为主峰、5月为次峰,00—12时(北京时,下同)的地闪发生概率月分布曲线与全天不同,呈逐月上升特...     

甘肃武威市雷暴天气时空分布特征

雷暴天气是甘肃武威市多发的灾害性天气之一。利用1961~2010年武威市5个气象站雷暴资料,以及2001~2010年4~10月逐日NCEP再分析资料,分析了武威市雷暴天气的时空分布特征及变化趋势,并依据气流的南北配置方法对雷暴天气进行了环流分型。结果表明:受海拔高度和地形地势的影响,武威市雷暴具有明显的地域特征,南部天祝山区雷暴日数远大于其他各地,占雷暴总日数的40.6%。年际、年代际雷暴日数总体呈减少趋势,其中,天祝的减少趋势尤为显著,其递减率为-5.819 d/10 a,年雷暴日数的时间序列存在着7~8 a的准周期变化。一年内,6~8月是雷暴的高发期,雷暴日数占全年总日数的70.8%~78.6%。雷暴的日变化特征明显,12~22时为其多发时段,集中发生时段为13~17时,雷暴的平均持续时间为10~40 min。武威市雷暴天气环流形势可分为西北气流型、西南气流型和西风气流型3类。其中,西北气流型,高空冷平流深厚且移速缓慢,最有利于强对流天气发生,雷暴发生比例最高;西南气流型,系统过境后无残余的冷空气滞留,不利于强对流天气发生,雷暴发生比例最低;西风气流型,高空低涡位置较偏北,冷空气较强,较利于强对流天气发生,雷暴发生比例相对较高。     

2005—2007年乌兰浩特机场夏季雷暴特征分析

对乌兰浩特机场2005—2007年夏季(6—8月)雷暴天气进行了统计和分析。统计结果表明:乌兰浩特机场夏季发生雷暴天气的概率不高,按日数统计的气候概率达23.36%;连续性不强;持续时间短,一般在1.5h以内;雷暴天气多数出现在午后至夜间,上午出现的概率极低。雷暴一般形成在机场西、西南和南部,消失在东和东南部,移动方向主要为由西向东。     

天气系统与海南降水的关系研究

以海南文昌为例,通过对影响海南省的四类十二型天气系统的活动及其对降水天气的影响进行分析研究表明,影响海南省的天气系统,以热带系统较多,冷空气类系统次之;单一系统,以变暖高压脊(G2)和西南低压槽(SWT)较活跃,华南沿海槽(ST2)和越南低压槽(YT)较少。降水则以冷空气类(除WS型)和低压槽类(除SWT型)较多,降水概率基本在50%以上,其中静止锋(WQ,EQ)系统和华南沿海槽(ST2)的降水概率甚至达到65~70%;较好地揭示了各种天气系统在海南省的活动规律及与降水的关系,为海南省指导各县市的天气预报及服务提供依据。     

2006年5—9月雷暴天气及各种物理量指数的统计分析

对2006年5-9月全国雷暴天气时空特征进行了统计分析,结果表明:雷暴天气的发生具有明显的短时局地特征,大多数发生在17-20时,上午11时发生最少.全国范围发生过雷暴天气的站点不到总数的三分之一.从空间分布来看,广东、广西及云南三省(区)是雷暴发生最为频繁的省份,内蒙古中西部、新疆北部、青海北部等地则发生较少.此外,统计分析各物理量指数后发现,各种物理量指数对于雷暴等强对流天气发生呈现出不同的概率分布特征,其中最主要的特征是当雷暴等强对流性天气发生时,存在3个高概率区域,每个区域对应物理量指数值相对集中在一个特定范围内.     

海南岛雷暴大风天气形势和环境参数特征分析

利用海南岛区域加密自动站资料和海口站探空资料,结合ERA-Interim再分析资料对2014-2018年海南岛雷暴大风的强度、时空分布、环流形势和物理量参数特征进行分析研究。结果表明:(1)海南岛雷暴大风主要出现在5-8月的午后到傍晚时段,最大阵风风速大部分在8级及以上。(2)雷暴大风的环流形势可以分为三类,即西南热低压型、季风槽型和冷锋型,其中季风槽型根据槽线位置可以分为华南沿海槽型和南海低压槽型。(3)西南热低压型雷暴大风的大气不稳定能量最大,上干下湿,垂直风切变较小;冷锋型的大气不稳定能量最小,上干下湿,垂直风切变最大;季风槽型的大气不稳定能量较大,整层较湿,垂直风切变最小。(4)季风槽天气形势下发生雷暴大风时,较容易伴随短时强降水天气,西南热低压型的雷暴大风风力比其他类型更大。     

博州雷暴的时间变化和周期

利用1961--2000年博州4个气象站雷暴天气的观测资料,分析了雷暴的气候特征.分析表明,博州多年年雷暴日数20-52d,年雷暴日数平原地区较少,高山地区较多,雷暴天气集中出现在夏半年5-8月.温泉雷暴天气的高发时段15-21时,精河高发时段17-23时,阿拉山口高发时段16-24时.温泉、精河和阿拉山口雷暴持续时间以30min为主.博乐和阿拉山口40a内年雷暴日数线性减少,两站年雷暴日数在1979年发生突变.博州雷暴日数年际变化具有6～9a的震荡周期.     

河北廊坊雷暴大风的气候特征

利用1970~2012年廊坊地区9个气象站地面雷暴大风观测资料,采用趋势分析、滑动t检验、小波分析和最大熵谱分析等统计方法,系统分析了该地区雷暴大风天气的时空特征及变化趋势和变化周期。结果表明:廊坊地区的雷暴大风局地性强,43 a间只出现了一次全区性的雷暴大风天气过程,雷暴大风多以单站出现为主。雷暴大风的地域性特征明显,中部的廊坊市及南部的文安、大城站较易出现,而北部发生概率较低。雷暴大风的日、月及年变化特征明显。雷暴与大风主要发生在午后至前半夜,大风发生时间一般落后于雷暴,1 h内的雷暴与10 min以内的大风发生概率最高;雷暴大风3~10月都可出现,主要集中在夏季,发生概率为73.3%;近43 a来,年均雷暴大风日数整体呈现减少趋势,且中部的站点减少趋势最显著,1994年为雷暴大风的显著突变年,其显著变化周期为3.23a。雷暴大风多为"湿"型。     

一次强飑线的成因及维持和加强机制分析

利用常规观测资料、多普勒天气雷达、自动气象站等资料对2004年7月12日影响上海的一次较长生命史的强飑线过程进行了综合分析，对这次强对流天气发生、发展、强度以及移动和传播的分析结果表明:副热带高压从华南沿海稳定地加强西伸，西风槽缓慢东移，导致华东地区850~500 hPa形成深厚西南急流，急流的加强促使低层锋生，配合K指数高能锋区的不稳定层结，大大增强了强对流天气发生的可能性；地面锋生作用和低层辐合、高层辐散造成的强抬升作用是主要的触发机制；较强的环境风垂直切变和雷暴内部上升气流与下沉气流的正反馈作用是飑线系统维持较长时间的原因，中尺度对流系统(MCS)多个雷暴单体间的相互作用使得南侧的雷暴单体加强、移动方向发生偏转。     

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.     

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.     

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.     

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.     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

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;     

Information for Contributors

正Journal of Meteorological Research is an international academic journal in atmospheric sciences edited and published by Acta Meteorologica Sinica Press,sponsored by the Chinese Meteorological Society.It has been acting as a bridge of academic exchange between Chinese and foreign meteorologists and aiming at introduction of the current advancements in atmospheric sciences in China.The journal columns include Articles.Note and Correspondence,and research letters.Contributions from all over the world are welcome.