广州市雷电灾害易损性分析评估和易损度区划

基于广州市2013—2015年闪电监测资料和2010—2015年雷电灾害资料,分析了雷击大地密度的空间分布和雷电灾害频度特征;并结合广州市人口密度、GDP等特征,选取雷击大地密度NG、雷电灾害频度P、生命易损模数L和经济易损模数D这4个参数作为雷电灾害风险评估指标,利用层次分析法确定评估指标权重,建立了雷电灾害风险评估方程式,对广州市雷电灾害易损性进行分析,从而形成雷电灾害易损度区划。结果表明:天河为极高风险区,海珠、萝岗、番禺和花都为高风险区,越秀、荔湾、黄埔和白云为中风险区,从化、增城和南沙为低风险区。研究结果可为广州市雷电灾害易损度区划提供技术支撑。     

基于GIS技术的江西省雷电灾害风险区划

利用2010—2019年江西省闪电定位监测数据、地理信息数据和社会经济数据,基于GIS技术、自然灾害风险评估方法和层次分析法等方法,从致灾因子、孕灾环境、承灾体3个方面,开展雷电灾害风险区划的研究,并形成江西省雷电灾害风险区划。结果表明：江西省雷电灾害的极高风险区和高风险区主要分布在南昌市、宜春市、新余市、上饶市、吉安市大部分地区和赣州小部分地区,中风险区和低风险区主要分布在九江市、萍乡市和抚州市大部分地区,该区划结果与江西省近10 a雷灾造成的人员伤亡情况大致吻合。     

黎川县烤烟种植强降水灾害风险评估与区划

强降水严重影响烤烟生长和品质形成,对烤烟种植区进行强降水灾害风险区划将有利于烤烟种植的防灾减灾。利用2006—2018年5—6月降水量、2010—2018年烤烟产量和地形资料,采用层次分析法和灾害风险指数法,对江西省黎川县烤烟种植强降水灾害风险进行评估和区划。以单日降水强度、5日累计降水强度和高程、坡度、河网密度为危险性因子,以烤烟产量为暴露性因子,以烤烟减产率为脆弱性因子,构建烤烟种植强降水灾害风险评价指标和模型。利用模型对县域各乡镇进行风险评估,并按轻风险、低风险、中风险、高风险四个等级进行风险区划。结果表明,宏村镇烤烟种植强降水灾害风险等级最高,龙安镇、社苹乡以及县域东北部的厚村乡、洵口镇、湖坊乡、熊村镇为中等风险区,县域其他地区为低风险区或轻风险区。     

基于改进层次分析法的湖北省雷电灾害风险区划

准确判定评价指标的相对重要性是雷电灾害风险区划的关键技术之一。为解决层次分析法(AHP)由人为经验方式判定指标相对重要性存在的问题,提出一种改进的AHP法(IAHP);同时,利用湖北省2007—2020年闪电监测、数字地形高程、土壤电导率及经济社会等资料,选取雷击大地密度、地闪强度、海拔高度、地形起伏度、土壤电导率、人口密度、GDP密度7个参数作为湖北省雷电灾害风险的评价指标,构建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:湖北省雷电灾害风险可分为高、较高、中、较低、低5个等级,较高、高风险区主要位于鄂东大别山以南、幕阜山以北的平原和低山丘陵地区,以及江汉平原大部和鄂西山区向江汉平原的过渡带;较低、低风险区主要位于鄂西的恩施、神农架、十堰、宜昌西部和襄阳西南部;湖北其它地区,大部为雷电灾害中风险等级。对比检验显示,各区县雷电灾害风险指数与历年实际雷灾频次呈正相关,且相关性较好,基本反映了湖北省雷电灾害的潜在风险。     

基于层次分析模型的黑龙江省雷电灾害风险区划

根据黑龙江省1959—2008年雷暴日及1999—2008年雷电灾害资料,结合黑龙江省人口密度、城市发展等社会经济特征,选取雷暴日数、雷电灾害频度、生命易损模数及经济易损模数作为雷电灾害风险评估指标,采用层次分析法确定评估指标权重分布,建立雷电灾害风险评估模型,形成黑龙江省雷电灾害风险区划图,并对该省雷电灾害风险进行了综合评估。结果表明:位于黑龙江省中部松花江、呼兰河流域的哈尔滨、绥化和位于西部嫩江流域的齐齐哈尔为雷电灾害极高风险区;位于北部大兴安岭和小兴安岭山区的大兴安岭、黑河、伊春为高风险区;位于东部三江平原的鹤岗、鸡西、七台河为中风险区;位于东部三江平原腹地的佳木斯、双鸭山和位于东南部河谷盆地的牡丹江为低风险区。     

改进的AHP在县域尺度暴雨洪涝风险评价的应用

以淮河流域为例,选取降水、土地利用、经济、人口等指标作为淮河流域暴雨洪涝灾害风险指标,利用信息熵改进的层次分析法确定淮河流域暴雨洪涝的风险评估指标权重,并应用于县域尺度淮河流域暴雨洪涝灾害风险评价。结果表明:(1)淮河流域暴雨洪涝灾害风险空间分布整体呈现南部高、北部低,东西高、中部次之的形态。(2)改进的层次分析法得到的高风险区比传统方法的面积减少,市县个数下降,而次高风险区、中风险区、次低以及低风险区面积比之传统方法均有增加。同时风险平均值升高,导致受灾程度可能加大。(3)改进方法得到的岳西县风险等级由高风险区降为次高风险区,低于金寨县风险等级。宿州市风险等级由次高风险区降为中风险区,较灵璧、泗县风险低,与实际情况更为相符,提高了淮河流域暴雨洪涝灾害风险评价精度。     

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。     

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。     

广西甘蔗秋旱灾害风险评估技术初步研究

为增强对广西甘蔗秋旱灾害的风险评估和应急管理能力,利用气象、植被、基础地理信息和社会经济数据,根据风险三角形理念,从广西甘蔗秋旱灾害的危险度、受灾可能性和承灾体脆弱度3个方面,选择因子构建甘蔗秋旱灾害风险评估的指标体系,采用层次分析法构造判断矩阵以确定各指标和因子的权重,构建评估模型,并计算广西甘蔗秋旱灾害风险指数,再基于GIS绘制广西甘蔗秋旱灾害风险区划,结果显示:高风险区和较高风险区主要分布在来宾和崇左等市的局部地区,低风险区主要分布在桂东南地区。利用灾情数据进行验证表明:广西甘蔗秋旱灾害风险分布与甘蔗灾情损失空间分布情况基本一致。     

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.     

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;