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。     

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。     

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。     

2010—2016年二连浩特市机场夏季雷暴特征分析

文章利用二连浩特市机场2010—2016年夏季(6—8月)常规气象观测资料,对雷暴进行统计和分析,结果表明:二连浩特市机场夏季发生雷暴的概率不高,雷暴日数分布不均匀;雷暴连续性不强;雷暴持续时间短,一般在0~2h以内;雷暴多数出现在午后至傍晚,上午出现的概率较低;雷暴形成在机场西南、北和西北方向,消失在东和东南方向,移动方向是由西向东。准确了解雷暴的分布特征,为航空飞行活动的安全、正常和效率服务。     

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,呈逐月上升特征;地闪发生概率和地闪次数时段分布曲线呈单峰特性,峰值均出现在15—18时,除12—21时外其他时段的地闪发生概率和地闪次数都很低,控制过程的后期比前期的闪发生概率和地闪次数略高;00—12时各时段海南岛地闪发生概率中心分布在东南沿海,概率中心值在5%以下,12—21时各时段地闪发生概率中心分布在北部内陆,概率中心由白沙中部向澄迈东部移动,移向呈西南—东北向,15—18时概率中心在澄迈南部达到最大值40%,21时以后概率中心分布在屯昌境内,中心值在5%以下;7—9月各时段的地闪发生概率均比4—6月高,但地闪次数峰值比4—6月少,两者各时段的地闪发生概率的空间分布完全一致。     

近30年西藏地区雷暴日数的气候分布特征

利用西藏地区1980~2009年逐月雷暴日数观测数据,分析了近30a来西藏地区雷暴的时空分布特征以及影响雷暴天气的气象因子。结果表明:(1)雷暴天气主要发生在西藏那曲地区,并由该区域向西南、东南部逐渐递减,且雷暴天气发生的中心位置随着季节有所差别。夏季雷暴日数最多,其次是秋季和春季,冬季雷暴日数最少。(2)近30年来年或各季节的雷暴日数基本呈现减少的趋势,尤其以2000年之后最为显著。雷暴日数以2003年为突变点,开始急剧减少。(3)雷暴日数和平均气温呈负相关,与风速、相对湿度、降水量呈正相关,气温升高可能是导致雷暴日数减少的主要气候影响因子。      

中国中小尺度强对流天气气候学特征

中小尺度强对流天气具有极强的破坏力,了解其气候学特征对于预测、预报和影响评价都具有实际意义。利用1961~2015年的2332个高密度逐月国家级气象站观测资料,分析了中国大陆3种常见中小尺度强对流天气（雷暴、闪电、冰雹）在年、季、月尺度上发生日数的时间变化规律和空间分布特征。结果表明:全国年平均雷暴、闪电和冰雹发生频率分别为39.23 d/a、20.56 d/a和1.07 d/a;雷暴和闪电主要发生在夏季3个月,雷暴日数7月最多,闪电日数8月最多;冰雹主要发生每年5~9月,6月发生频率最高;雷暴和闪电的高发区分布基本一致,主要集中在华南和西南,青藏高原也是雷暴的高发区域之一;冰雹的高发区主要集中在青藏高原、内蒙古高原东部以及中西部山地,而东南沿海地区发生频率则较低。进一步分析发现,我国雷暴和冰雹出现频率随海拔高度增加而明显增加,冰雹和海拔高度有更好的对应关系,二者增加速率分别为2.87 d/500 m和1.80 d/500 m,表明地势高度对这两种强对流天气形成和发展具有重要影响。     

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.     

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     

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.     

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。     

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正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography.     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.     

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.     

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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.     

Our Warmest Thanks to AAS Reviewers 2014

正The editorial office of Advances in Atmospheric Sciences(AAS),on behalf of all AAS editors,would like to publicly acknowledge the people listed below who served as reviewers for the journal daring 1 September 2013 to 24 August 2014.We recognize that the time and work of the reviewers is the most important resource in academic publishing.The quality of our journal depends in a crucial way upon the reviewing process and therefore all reviewers'time and efforts taken to sustain the quality of the journal are greatly appreciated.