基于GIS技术的乐山市暴雨洪涝灾害风险区划研究

利用乐山历史气象资料,综合乐山自然、社会经济与防灾资料,利用GIS技术和自然灾害风险指数,构建乐山暴雨洪涝灾害风险评价模型,对乐山暴雨洪涝风险的致灾因子危险性、孕灾环境敏感性、承灾体易损性、防灾能力多个因子定量分析,计算出全市范围暴雨洪涝灾害综合风险指数,并绘制了风险区划图。结果表明:乐山市中区、五通桥区、沙湾区、峨眉山市和夹江县的部分地区其暴雨洪涝灾害风险最大;金口河区、峨边县、马边县暴雨洪涝灾害风险最小。      

河北省棉花连阴雨灾害定量化评估指标与风险分析

利用河北省棉区1981—2015年40个气象站逐日气象资料、农业气象观测站棉花农情、连阴雨灾情、棉花产量资料,分析连阴雨过程特征及其对棉花生长的影响,修订和完善连阴雨灾害指标;采用数理统计方法获取历史连阴雨产量灾损率、筛选关键致灾因子,采用权重系数法构建连阴雨强度指数,并建立基于强度指数的灾损评估模型;利用有序样本聚类分析法划分连阴雨强度等级;依据风险分析原理,构建连阴雨风险指数并进行风险区划。结果表明：建立的强度指数能够客观反映连阴雨灾害强度,灾损评估模型评估效果较好。棉花播种出苗期连阴雨发生概率低（0.076）、造成的损失小（平均产量灾损率0.09%）;现蕾至吐絮期连阴雨影响较大,发生概率和造成的灾损率由大到小依次为花铃期（0.447,17.1%） > 现蕾期（0.394,11.7%） > 吐絮期（0.237,7.2%）。近年来,现蕾期连阴雨发生站次减少,对棉花影响减弱,花铃期和吐絮期发生站次增加,尤其是吐絮期增加明显,成为连阴雨灾害影响棉花生长的主要时期。现蕾期和花铃期连阴雨高风险区主要分布在非主棉区,其中现蕾期高风险区分布在保定北部及以北棉区,花铃期高风险区分布在保定北部及以北棉区和石家庄、邢台、邯郸三市西部棉区;吐絮期高风险区分布在保定西南部、衡水西部、石家庄及其以南棉区,部分地区为主棉区。     

应用主成分构建的暴雨致灾能力评估指数及其应用

为了构建合理的四川暴雨致灾能力评估指数(简称:评估指数),本文对2008~2018年四川地区126次致灾性暴雨过程,选取刻画暴雨特征的8个降水量因子,利用总体主成分和阈值法确立因子的权重及阈值,由此建立了评估指数模型。经历史个例反演及预报个例的评估应用表明:(1)暴雨区域的平均雨量值,≥25mm/h的面积及大暴雨面积是影响四川暴雨致灾能力强弱的关键因子,利用主成分构建的评估指数较好的反映了历次暴雨过程的致灾能力,当指数达0.8以上时,一般对应着大型及以上暴雨灾害。(2)结合经济损失及气象灾害评估分级处置标准,将评估指数划为4个等级。基于此,利用每日08时和20时四川省气象台订正的0.05°×0.05°预报降水数据,输入评估指数模型计算未来3d的指数及对应的致灾能力落区等级空间分布。实际应用表明,评估指数模型对评估暴雨过程的整体致灾能力及具体的暴雨致灾能力落区等级分布有显著的实用性。      

广西甘蔗主产区产量灾损风险评估

根据风险分析原理,利用1978-2009年广西甘蔗产量资料,采用减产率、变异系数、灾损减产风险指数等指标,对广西甘蔗主产区产量灾损风险水平进行评估。结果表明,广西甘蔗主产区气象产量历年平均减产率0-25%,以轻度减产年型（减产率5%-10%）居多,且呈现一定的连片性;减产率变异系数0.75-4.00,崇左市和南宁市部分县区在1.00以下,说明这些地区甘蔗受气象灾害影响造成的大减产年份少;灾损减产风险指数0-0.48,按主产区各地市灾损减产风险指数从小到大排列,防城港市〈崇左市〈南宁市〈钦州市〈来宾市〈贵港市。综合考虑干旱、低温霜冻等气象灾害影响,气象灾害引起甘蔗产量波动风险程度以贵港市的最大,防城港市的最小。研究结果可为广西甘蔗稳产高产制定防灾减灾措施、农业保险制度推行等提供基础理论依据。     

广东省县域单元热带气旋灾害损失评估方法研究

利用2004—2014年广东省的热带气旋(Tropical Cyclone, TC)降水和大风资料以及TC造成的直接经济损失数据,通过TC经济灾损率的定义,研究了TC直接经济损失与TC降水和大风的关系,并建立评估模型。广东省沿海地区是TC降水和大风影响频繁地区,TC经济灾损率和受灾频次在广东西南部和东部沿海地区较大。TC经济灾损率与TC降水和大风之间存在较好的指数关系。由此得到不同等级经济灾损率对应的气象因素致灾阈值。利用此气象因素致灾阈值可以对县域单元的TC直接经济损失进行评估。对2004—2014年广东省TC造成的直接经济损失的模拟结果表明,该方法能较好地评估广东的县域单元TC经济损失。      

廊坊市暴雨洪涝灾害风险评估与区划

2008年廊坊市气象灾情普查资料显示,暴雨洪涝灾害是气象灾害中造成损失最为严重的气象灾害,1949～2007年廊坊市由暴雨洪涝灾害造成的直接经济损失总计达1986.73亿元,占所有气象灾害造成直接经济损失的82.2%,严重影响着国家和地方经济的可持续发展。依据自然灾害系统理论和灾害风险评估原理,计算出廊坊市地理地貌状况指数(H)、暴雨洪涝发生强度指数(C)、暴雨洪涝灾害频率指数(R)、承灾体经济承灾能力指数(E)、经济损失指数(E')、生命易损指数(L)、生命损伤指数(L'),抗灾能力指数(K)等8个风险指数,并对其进行评估与分析的基础上,综合评价了廊坊市暴雨洪涝灾害风险程度的地域差异,得出各县市区的综合风险指数,并按极高、高、中、低等4级分区法对廊坊市暴雨洪涝灾害的综合风险指数进行区划。研究所形成的暴雨洪涝灾害风险度区划对本地防御暴雨洪涝和降低灾害损失,以及对暴雨洪涝灾害采取有效管理提供了比较客观的科学依据。     

1981—2019年北疆暴雨洪涝灾害的时空变化特征分析

基于1981—2019年新疆北疆38个县(市)出现的1394次暴雨洪涝灾害事件,以暴雨洪涝灾害出现次数、死亡人数、倒塌房屋数、倒塌棚圈数、死亡牲畜数、农作物受灾面积作为评价因子,采用多种统计学方法,构建暴雨洪涝灾损指数,分析近39 a北疆暴雨洪涝灾害的时空变化特征.结果表明:北疆暴雨洪涝灾害高发区位于博州、伊犁河谷和阿勒泰地区,危害性严重等级以上的暴雨洪涝灾害分布在伊犁河谷和阿勒泰地区,特重等级的暴雨洪涝灾害则集中发生在伊犁河谷的霍城、伊宁、巩留、尼勒克和新源等县;暴雨洪涝灾害出现次数及其造成的死亡人数、农作物受灾面积的月变化呈单峰型,而倒塌房屋数、倒塌棚圈数、死亡牲畜数则呈双峰型;年暴雨洪涝灾害出现次数呈显著的线性增加趋势,年度灾损指数呈弱的增加趋势,但在年代际时间尺度上灾害强度不断加强.大雨以上日数和暴雨以上日数是影响北疆暴雨洪涝灾害年际变化的主要气候因素.     

水稻高温热害风险评估方法研究

以衡阳地区的水稻生长为研究对象,对ORYZA2000水稻模型的相应参数进行了本地化,模拟了该地区常年气候条件、设定高温条件及各年高温条件下的一季稻产量,并计算了各年实况及设定条件下的产量灾损率,在此基础上建立了两种水稻产量灾损率评估模型。研究发现：46 a来衡阳地区水稻开花灌浆期平均日最高气温为34.98℃,高于水稻生产的最适温度5℃以上;相对常年产量,由高温热害导致的产量灾损率最高为67.2%,历年灾损中2003年的灾损率接近最高值,达67.0%;高温造成的产量灾损率受高温程度及持续时间的共同影响,二者缺一不可;根据多元回归建立的灾损率评估模型,F计算值〉〉F查表值,方程有意义。其趋势预测完全一致,灾损率精确度〉72%;根据高温指标建立的灾损率评估模型通过了46 a的大样本检验,在高温热害风险评估方面具有一定的实际应用价值。     

水稻高温热害风险评估方法研究

以衡阳地区的水稻生长为研究对象,对ORYZA2000水稻模型的相应参数进行了本地化,模拟了该地区常年气候条件、设定高温条件及各年高温条件下的一季稻产量,并计算了各年实况及设定条件下的产量灾损率,在此基础上建立了两种水稻产量灾损率评估模型.研究发现: 46 a来衡阳地区水稻开花灌浆期平均日最高气温为34.98 ℃,高于水稻生产的最适温度5 ℃以上;相对常年产量,由高温热害导致的产量灾损率最高为67.2%,历年灾损中2003年的灾损率接近最高值,达67.0%;高温造成的产量灾损率受高温程度及持续时间的共同影响,二者缺一不可;根据多元回归建立的灾损率评估模型,F计算值＞＞F查表值,方程有意义.其趋势预测完全一致,灾损率精确度＞72%;根据高温指标建立的灾损率评估模型通过了46 a的大样本检验,在高温热害风险评估方面具有一定的实际应用价值.     

盘锦水稻产量灾损风险及气象影响因子分析

应用滑动平均模拟方法,计算了盘锦地区1977-2006年30年水稻趋势单产,并据此求算出气象产量.以减产率＞5.0%界定灾年,分别从不同气象灾害损失等级出现的概率、变异系数等角度综合分析了盘锦地区水稻生产的灾损风险.并通过计算水稻产量与各气象因子的相关关系,寻找影响水稻产量的主要气象因子和气象灾害.结果显示:盘锦地区水稻产量波动随着农业生产水平的提高而减小,盘山县的灾损风险大于全市水平;热量条件的丰欠是造成盘锦地区产量波动的主要原因,其中5-10月≥10℃的积温,5、6月份的平均气温及9月份平均最高气温对产量影响显著;而在5月、6月和9月该地区的主要农业气象灾害是低温冷害,这与实际相当吻合.     

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.     

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.     

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.     

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.     

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