基于易损度分析的吉林省雷电灾害风险区划

分析整理2003-2012年吉林省历史雷灾记录,利用48个气象站人工观测雷暴日数序列和2011年《吉林省统计年鉴》数据,结合应用聚类分析和层次分析法建立了吉林省县(市)雷电灾害易损度计算模型。利用自然断点法对模型计算出的易损度进行分级,实现了吉林省各县(市)的雷电灾害风险区划。区划结果表明:吉林省的雷电灾害风险由强到低呈现出由中部向周边递减的结构,强风险区主要位于吉林省中部和南部的地级市本市;高风险区主要位于中部和南部经济发展水平相对较高的县(市);中风险区和低风险区则主要集中于东部山区和西部平原地区。     

层次分析法和GIS技术在河南省雷电灾害风险区划中的应用

根据自然灾害风险评估理论,利用闪电定位资料、地理信息数据、社会经济数据以及雷电灾情等数据,采用层次分析法（AHP法）,从致灾因子的危险性、承灾体的暴露度和承灾体的脆弱性方面,研究雷电灾害风险评估及区划方法,建立起评价指标与风险评估的定量关系,形成了河南省雷电灾害风险评估的方法.同时,结合GIS技术,形成了致灾因子危险性分布图、承灾体的暴露度分布图和承灾体的脆弱性分布图,最终叠加形成河南省雷电灾害综合风险区划图.区划结果表明：高风险区主要位于豫东和豫西北大部分地区,低风险区主要位于豫北和豫西南部分地区.     

雷电灾害风险区划方法研究及其在安徽省的应用

本文根据自然灾害系统理论和自然灾害风险评估理论,利用气象资料、地理信息数据、社会经济数据以及雷电灾情等数据,采用统计方法、灾情解析、专家打分等方法,从致灾因子、孕灾环境、承灾体方面,研究雷电灾害风险评估及区划方法,建立起评价指标与风险评估的定量关系,形成了较完整的雷电灾害风险评估及区划技术方法体系,具有很好的应用推广价值。对安徽省雷电灾害风险区划表明:高风险区主要位于经济水平较高的城市以及皖南山区高海拔地区,而低风险区主要位于淮北地区,与灾情验证情况吻合。     

基于投影寻踪方法的湖北省雷电灾害风险区划

利用湖北省2007—2017年闪电监测与雷暴日观测等数据资料,选取雷暴日、地闪密度、雷电流波头陡度、雷电流强度、大电流密度、小电流密度6个雷电参数作为湖北省雷电灾害风险评价指标;采用投影寻踪方法,构建基于雷电参数的雷电灾害风险评价模型,据此对湖北省雷电灾害进行综合评价与风险区划。结果表明:湖北省雷电灾害可划分为高、较高、中、较低和低5个风险等级,风险等级整体从东至西逐渐降低,东部地区风险明显高于西部地区;较高和高风险区主要位于红安、孝昌、孝南、东西湖、蔡甸、汉南至洪湖一线以东地区;较低和低风险区主要位于襄州、襄城、谷城、保康、兴山、秭归、巴东至五峰一线以西地区;上述以东地区与以西地区之间地带主要为中等风险区,共27个区、县(市)。雷电灾害风险区划结果可为本地开展雷电防灾减灾工作和有效降低灾害损失提供科学依据。     

苏浙沪地区高温灾害风险区划研究

利用1961—2009年苏浙沪地区144个气象站的观测数据和2008—2010年苏浙沪地区社会经济资料,从致灾因子危险性、孕灾环境敏感度、承灾体易损性及抗灾能力4个方面综合评估和分析了苏浙沪地区高温灾害风险的空间差异。结果表明:1961—2009年苏浙沪地区高温致灾因子呈南高北低的分布特征,浙江地区高温致灾因子危险性明显大于上海和江苏地区;孕灾环境敏感度指数呈北部和中部地区高、南部地区低的分布,高温灾害高敏感区主要分布在江苏、上海及浙北的平原和沿海地区;经济发达和规模较大的苏浙沪核心城市多为高温灾害承灾体高易损性区,苏北和浙南相对欠发达地区多为高温灾害承灾体低易损性区、次低易损性区或中等易损性区;沪宁杭地区高温灾害的抗灾能力最强,对应的抗灾能力风险较低,而苏北地区和浙南山区高温灾害的的抗灾能力风险较高。综合致灾因子危险性、孕灾环境敏感度、承灾体易损性和抗灾能力4个方面,苏浙沪地区高温灾害综合风险总体呈中南部地区风险高、北部地区风险低的分布,高温灾害高风险区和次高风险区主要集中分布在浙江大部及上海、苏南部分地区,高温灾害低风险区或次低风险区主要分布在长江以北和浙江沿海地区。     

基于GIS的贵州省道路结冰灾害风险区划分析

本文利用贵州省84个气象站1971～2008年的观测资料和2013年贵州省社会经济资料,结合地理信息数据,从致灾因子、孕灾环境、承灾体易损性、承灾体抗灾能力等四个方面采用归一化后的加权平均方法综合分析了贵州省道路结冰灾害的风险。结果表明:贵州省道路结冰灾害风险的低风险区占全省面积的24.26%,一般风险区范围最大,占全省面积的36.41%,中等风险区占全省面积的24.02%,高风险区占全省面积的11.5%,极高风险区占比最小,为3.83%。全省中等风险及以上的风险区主要集中在贵州省中部以西地区,东部地区仅分布在在铜仁市中部的梵净山区、黔东南州西部的苗岭主锋之一雷公山一带。      

浙江省雷电灾害风险分析及区划

在灾害风险评估中,基于行政区域统计单元的人口和经济数据往往与栅格水平上的致灾因子存在空间上的不匹配。利用遥感夜间灯光数据、植被指数和DEM数据构建人居指数,进行栅格尺度上的雷灾承灾体易损性分析,利用2005—2011年浙江省电网雷电信息系统的地闪数据和2008—2011年雷电灾害统计资料进行雷电致灾危险性评估,基于上述三个评估指标,采用层次分析法确定权重系数,建立浙江省雷电灾害风险评估模型,获得1 km分辨率的浙江省雷电灾害风险区划图。结果表明,杭州、宁波、台州等经济发达地区和长兴、安吉、天台和临海等平地向山区地形过渡地带是浙江省雷电高风险区,甬台温沿海、海岛、衢州西部和丽水南部地区是低风险区域,其他地区为中风险区。     

基于ArcGIS的新疆雷电灾害风险区划研究

为了明确不同区县雷电灾害风险的高低程度、防御措施和减轻雷灾损失,利用地闪资料、雷电灾情数据、社会经济资料和地理信息数据,采取归一化法、层次分析法和加权综合评价法,考虑致灾因子的危险性、孕灾环境的敏感性和承灾体的易损性3个评价指标,选择地闪密度、地闪强度、海拔高度、地形起伏、地表覆盖类型、人口密度、地均GDP、生命损失指数、经济损失指数和耕地比重等10个影响因子建立雷电灾害区划模型,绘制出新疆雷电灾害风险区划图。结果表明:雷电灾害风险极高区主要集中在阿勒泰地区北部、塔城地区大部、博州、伊犁州、喀什市和天山北坡经济带南部部分地区,而古尔班通古特沙漠和塔克拉玛干沙漠地区属于一般风险区。通过与新疆历史雷电灾情数据比较发现,雷电灾情次数空间分布与风险区划分布趋势大致吻合。     

基于灾损定量识别的河南省冬小麦晚霜冻风险区划

利用河南省30个农业气象观测站1981-2008年的冬小麦观测资料和气象资料,基于晚霜冻指数和灾度计算了河南省冬小麦晚霜冻发生概率和灾害程度。通过在WOFOST作物模型中增加霜冻影响过程,实现了晚霜冻灾损定量提取,建立了以晚霜冻危险性、暴露性和脆弱性为评价因子的风险评估模型,按照高风险区、次高风险区、中等风险区、次低风险区和低风险区5个等级标准进行了河南省冬小麦晚霜冻风险区划。区划结果表明:冬小麦晚霜冻风险程度较高的地区主要分布在河南省沈丘、卢氏和林州等地,其风险指数都在0.6以上;低风险区主要分布在伊川、巩义、信阳、南阳、太康、濮阳和杞县等地,风险指数都在0.2以下。     

南郑县暴雨灾害风险区划研究

利用南郑县国家一般气象站1971—2016年、28个区域自动气象站2012—2016年降雨资料,DEM高程数据,辖区内社会经济资料,确定暴雨灾害的致灾因子、孕灾环境、承灾体易损性等区划因子,并使用ArcGIS对各项因子进行模拟计算,得到南郑县暴雨灾害风险区划图。区划结果表明:低风险区和次低风险区基本分布在南郑县北部,中等风险区基本分布在南郑县中部,次高风险区和高风险区基本分布在南郑县南部、东南部。     

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.