中国夏季干湿型热浪天气时空分布及环境舒适度评价

基于中国气象局对热浪天气的定义并参考地理分区和热浪日湿度分级标准,定义连续3 d以上地面最高气温≥35 ℃的天气过程为热浪,选取 1960—2018 年 476 个地面气象站观测数据研究中国夏季干热型和湿热型热浪日数的时空分布特征及其变化趋势。结果表明,中国夏季热浪日数除新疆外呈现东南高、西北低的空间分布格局,江南地区夏季热浪发生日数最多（年均 15 d）。温湿指数和人体舒适度指数评价结果表明江淮地区热浪天气期间环境舒适度最差,热浪天气对人体的不利影响更显著。相对于内陆地区,沿海地区因海风影响午后气温显著降低,有利于缓解热浪天气的影响,因而沿海站点夏季热浪日数比邻近的内陆站点偏少。除黄淮地区外中国大多数站点热浪日数均呈现增加趋势,江苏、浙江沿海、广东、重庆、海南、新疆及广西东部热浪日数增加趋势显著（1 ～5 d·(10 a) -1,α=0.05）;中国东部和东南沿海湿热型热浪增加趋势显著,增幅达 1～5 d·(10 a) -1;浙江、江西北部、甘肃、新疆等地区干热型热浪日数显著增加（α=0.01）。1990 年以来全国夏季热浪天气发生更为频繁;其中 2000—2009 年间干热型热浪日数偏多,而 2010 年之后强湿热型热浪日所占比例增加。     

气象灾害分布与影响

<正>2016年6月,联合国环境署(UNEP)发表的关于环境与人体健康联系的报告中,用1995—2005年的数据,描述了受到5种天气灾害影响的人数(左)、灾害发生次数(中)和因天气灾害死亡人数(右)之间的联系。一些灾害,如热浪,尽管发生次数和受到影响的人数量比例不大,但在致死灾害排名中靠前。     

中国高温热浪危害特征的研究综述

全面综述了高温热浪气象灾害在危害特点、标准与类型、气候特征、形成原因、对全球气候变暖的响应、监测和预测与预警技术、减灾技术及应对策略等8个方面的研究成果.高温热浪是一种较短时间尺度的天气灾害,基本天气特征是高温低湿,除高寒地带外,每年6～8月在全国各地均有发生.大气环流异常是高温热浪形成的直接原因,气候变暖变干是导致高温热浪频繁发生的重要原因.深刻了解高温热浪的危害特征,对应对高温热浪发生发展、监测预测、安全生产、趋利弊害具有重要的指导作用.     

高温中暑气象等级评定方法

在全球气候变化的大背景下, 高温热浪天气频繁出现, 由其引发的群发性中暑事件不断发生。为了有效预防极端高温天气对人体健康的影响, 利用全国358个重点城市1996-2005年逐日地面气象观测资料, 通过对气象要素与中暑的相关分析, 选择炎热指数为气象指标对引发中暑的气象条件进行了等级划分, 同时考虑不同程度高温天气的持续时间确定了高温中暑气象等级, 分别为可能发生中暑、较易发生中暑、易发生中暑和极易发生中暑4个等级。利用武汉市1994年和1995年7 -8月中暑人数与高温中暑气象等级进行对比分析, 结果表明:两者具有较好的对应关系。     

京津唐夏季高温特征及对城市化的响应探析

正城市化不是引起高温的唯一原因,大气环流和全球气候变暖也可能是引起高温的主要原因,深入对比研究大气环流和城市化对高温的影响将是未来研究的重点。改革开放以来,中国的城市化进程加快,极端高温天气发生越来越频繁,呈现出强度大、频次高、范围广等特点,极端高温事件往往与特重干旱相伴而来,严重威胁人们的生命及能源、水资源和粮食安全等。高温热浪在夏季严重影响人体健康,甚至会造成死亡。高温还使用水量、用电量急剧上升,从而给人     

高温热浪频发对经济系统影响的研究进展

随着全球气候变化,极端天气气候事件对全球经济、社会和健康产生了较大影响[1-2]。医学期刊《柳叶刀》发布报告称2017年极端天气气候事件造成的经济损失达到3260亿美元,几乎是2016年的3倍[3]。高温热浪是一种典型的极端天气气候事件,不同区域的高温热浪受湿度等因素的影响而有所差异。世界气象组织(WMO)将高温热浪定义为日最高气温在32℃以上且维持3 d以上的天气过程[4]。中国气象局将日最高气温在35℃及以上且维持3 d以上的天气过程称为高温热浪[5]。     

基于CiteSpace的热浪研究知识图谱分析

近年来,全球热浪事件频发,对环境、生态系统以及人体健康造成了重大影响。对热浪研究发展历程和研究热点与前沿进行梳理有助于为研究学者提供一些有益的启示。文中以热浪为主题词,从Web of Science核心数据库中检索出1975—2019年文献2237篇,运用CiteSpace知识图谱分析工具,对热浪的研究进展及演变趋势进行了图谱解读和分析。结果表明:(1)国外对于热浪的研究起步较早,在该领域拥有较多的高影响力学者以及科研机构,如美国国家大气研究中心;中国在热浪领域起步较晚,但是发展速度很快,代表机构为中国科学院。(2)热浪研究涉及的学科广泛,如气象与大气科学、环境科学、环境科学与生态学等,其中与环境相关的学科占主要。(3)热浪研究热点可概括为4个方向,包括热浪对健康的影响、热浪热点事件、热浪的影响因素以及热浪研究方法。(4)热浪的研究发展过程可分为3个阶段:起始阶段,研究重点在极端气候现象导致的热浪和热浪的时间变化特征领域;发展阶段,研究内容为1995年芝加哥热浪事件与2003年欧洲热浪事件,并关注了热浪与城市热岛的关系及热浪对健康的影响;当前研究阶段,减少城市热浪风险和海洋热浪是热浪研究领域的前沿。     

广西天气气候对人体健康的影响

采用广西多年季、月、旬平均气温、季平均相对湿度和历年的月最高气温、极端最高气温、主要天气气候事件等气象资料以及广西疾病预防控制中心的疾病监测数据和相关医学文献,对广西气候因素对人体健康的影响开展研究。结果显示,冬季和秋季的寒潮、夏季高温热浪,春、秋、冬季的"回南天"、低温阴雨是对人体健康影响较大的天气气候事件;气象因素引发的主要疾病包括心脑血管疾病、呼吸道疾病、胃肠道疾病等,其中受气象因素影响而致死的疾病中以心脑血管疾病死亡率最高,呼吸道疾病死亡率居第二位。     

2012—2016年宁波市中暑流行特征及热浪对其影响分析

城市高温热浪事件严重影响人体健康和生命安全已成共识。利用宁波市2012—2016年中暑病例数据和同期气候数据对宁波市夏半年中暑流行特征及热浪对其的影响作了相关分析。结果表明:2012—2016年,2012年和2013年中暑人数最多,并集中在6—8月,其中7月人数最多占比55. 3%;男性中暑概率明显高于女性,中暑程度主要集中在轻度中暑,31—60岁年龄段中暑人数占比最高,市区中暑人数占比要高于郊区(县);用温湿两要素结合的炎热指数和热浪公式定义宁波热浪过程,发现热浪天数和中暑人数的相关系数高达0. 898,选出7次热浪过程计算热浪中暑的相对危险度,发现除2013年以外其他年份热浪中暑的相对危险度均在10以下,2013年的3次热浪中暑的相对危险度分别为18. 1、21. 6和25. 8,这与2013年热浪出现相对频繁集中有关;同时通过这7次热浪过程的前、后段热浪中暑的相对危险度的比较,并未见明显的热浪滞后效应存在。     

2016年全球重大天气气候事件及其成因

2016年全球主要温室气体浓度持续上升,地表温度相比工业化时代之前水平偏高1.1℃,成为有气象记录以来的最热年。受全球变暖影响,北极海冰全年处于较低水平,格陵兰冰盖和南极海冰的消融程度明显增强;海洋温度升高致使全球海平面上升和海洋环境变化。在超强厄尔尼诺事件背景下,受大气环流异常影响,全球降水空间分布不均,年初多地旱情持续发展,造成粮食和水资源危机;年内暴雨洪涝、高温热浪、寒流暴雪和热带气旋等各类极端天气气候事件频繁发生,在世界各地造成了严重人口伤亡和社会经济损失。本文总结了2016年全球重大天气气候事件及其影响,并重点分析了中国长江流域降水异常偏多及美国高温热浪天气两个典型事件的形成原因。分析表明,夏季西太平洋副热带高压偏西偏强,致使西南低空急流作为水汽通道将低纬暖湿气流向长江流域输送,配合同期亚洲东北部的高空槽引导高纬冷空气南下,冷暖气团的共同作用导致了中国长江流域强降水事件频发、汛情严重;北美副热带高压在美国境内一段时期内的稳定停滞以及低纬水汽输送条件偏差,是7月美国中东部地区高温热浪天气事件发生的主要原因。     

Summer heat waves over western Europe 1880–2003, their relationship to large-scale forcings and predictability

We investigate the large-scale forcing and teleconnections between atmospheric circulation (sea level pressure, SLP), sea surface temperatures (SSTs), precipitation and heat wave events over western Europe using a new dataset of 54 daily maximum temperature time series. Forty four of these time series have been homogenised at the daily timescale to ensure that the presence of inhomogeneities has been minimised. The daily data have been used to create a seasonal index of the number of heat waves. Using canonical correlation analysis (CCA), heat waves over western Europe are shown to be related to anomalous high pressure over Scandinavia and central western Europe. Other forcing factors such as Atlantic SSTs and European precipitation, the later as a proxy for soil moisture, a known factor in strengthening land–atmosphere feedback processes, are also important. The strength of the relationship between summer SLP anomalies and heat waves is improved (from 35%) to account for around 46% of its variability when summer Atlantic and Mediterranean SSTs and summer European precipitation anomalies are included as predictors. This indicates that these predictors are not completely collinear rather that they each have some contribution to accounting for summer heat wave variability. However, the simplicity and scale of the statistical analysis masks this complex interaction between variables. There is some useful predictive skill of summer heat waves using multiple lagged predictors. A CCA using preceding winter North Atlantic SSTs and preceding January to May Mediterranean total precipitation results in significant hindcast (1972–2003) Spearman rank correlation skill scores up to 0.55 with an average skill score over the domain equal to 0.28 ± 0.28. In agreement with previous studies focused on mean summer temperature, there appears to be some predictability of heat wave events on the decadal scale from the Atlantic Multidecadal Oscillation (AMO), although the long-term global mean temperature is also well related to western European heat waves. Combining these results with the observed positive trends in summer continental European SLP, North Atlantic SSTs and indications of a decline in European summer precipitation then possibly these long-term changes are also related to increased heat wave occurrence and it is important that the physical processes controlling these changes be more fully understood.     

近54年京津冀地区热浪时空变化特征及影响因素

基于1960—2013年京津冀及周边地区34个气象站逐日最高气温和相对湿度资料,利用高温热浪模型,辅以趋势分析、突变检验及相关分析等方法,研究近54年京津冀地区热浪时空变化特征,探讨城市化对热浪变化的影响,并尝试寻找对热浪异常具有稳定指示意义的环流因子。结果表明:1960—2013年京津冀地区热浪变化具有明显的阶段性,以20世纪70年代中期为转折,热浪呈先减少后增加趋势;京津冀地区热浪空间格局变化整体呈南减北增,东南平原区热浪呈下降趋势,北部生态涵养区呈现增加趋势;在区域尺度上,城市化或迁站影响并未改变北京极端热浪变化趋势,主要影响以轻度和中度热浪变化为主;西太平洋副热带高压和青藏高原反气旋环流与京津冀地区热浪异常关系最为显著,对热浪异常是一种稳定且强烈的指示信号。当青藏高原高空反气旋环流异常偏强,西太平洋副热带高压明显偏北,京津冀地区发生超级热浪可能性较大。     

Summer heat waves over western Turkey between 1965 and 2006

Global warming is one of the greatest environmental, economic, and social threats in the world. There are many assessments to estimate climate variability over many regions. A change in the Earth’s surface temperature leads to increase in extreme temperature events, which are harmful to the ecosystem, and moreover, they create danger on human health. In this study, we have selected the western part of Turkey as the study area, since climate change projections for Turkey point out that the highest temperature change can be expected on this region during summer, and the Turkish population is very dense here to be affected by extreme events. We have used apparent temperatures to define the heat waves which we have determined their frequencies for the summer months (June–August) of 1965–2006. Since the regional comparisons of station results are intended, we selected the 90th percentile value for each station as a threshold value to be used in the delineation of heat waves. Then, the number of heat waves is determined by imposing the constraint that apparent temperatures stay above the threshold value at least for three consecutive days. Then, the changes in the number of hot days and heat waves and also their durations are analyzed by using the linear least square method. We have found that the number of hot days, heat waves, and heat wave durations is increased between 1965 and 2006 on the western part of Turkey. Additionally, their rate of change is larger within the last decade and extremes are frequently observed after 1998. Regional distributions show that the tendency of the number of heat wave events increases towards the southern latitudes of the domain. Moreover, we investigated the relationship between the number of hot days and the sea surface temperatures of the Mediterranean Sea and Black Sea. Correlation analyses are carried out by the number of hot days and averaged sea surface temperatures on the regions of the western, central, and eastern Mediterranean Sea and the Black Sea. It is found that the number of hot days of west Turkey is better correlated with the sea surface temperatures averaged over eastern Mediterranean and Black Seas. The number of heat waves is found significantly correlated with the fire occurrences for most of the stations.     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

欧洲地区夏季热浪的特征及其与阻塞环流的联系

选取了一个热浪指数,利用地面2 m气温场和500 h Pa位势高度场的美国环境预报中心和国家大气研究中心(NCEP/NCAR)再分析资料,通过聚类分析发现欧洲大陆容易产生6类热浪:西欧型(WE)、俄罗斯型(RU)、东欧型(EE)、斯堪的纳维亚半岛型(SC)、北海型(NS)、伊比利亚半岛型(IB);这些热浪事件都与欧洲大陆阻塞的位置有关。同时我们发现这6类热浪发生的频率出现明显的年代际变化,特别在20世纪80年代以后欧洲大陆热浪发生频率明显的增多趋势可能与欧洲大陆增暖背景有关,而欧洲大陆热浪发生频率的年代际变化可能是夏季北大西洋涛动(NAO)的年代际变化的结果。夏季NAO偶极子通过欧洲地区的阻塞异常对欧洲大陆气温有重要的调制作用。当夏季NAO指数处于正位相阶段时,欧洲大陆容易产生高纬度热浪,反之则容易产生低纬度热浪,并且欧洲大陆增暖趋势并不影响NAO对欧洲气温的调制作用。同时还发现:大西洋夏季NAO事件可以是欧洲热浪发生的前期条件,欧洲大陆阻塞异常落后于NAO事件1~5 d,其中IB型和WE型与NAO同期相关,其余4类型热浪对应阻塞落后于NAO 4~5 d。另外,也发现大西洋—欧洲大陆定常波列正距平的位置通过对欧洲阻塞的影响,而影响欧洲热浪发生的频率和位置。     

The impact of heat waves on surface urban heat island and local economy in Cluj-Napoca city,Romania

The association between heat waves and the urban heat island effect can increase the impact on environment and society inducing biophysical hazards. Heat stress and their associated public health problems are among the most frequent. This paper explores the heat waves impact on surface urban heat island and on the local economy loss during three heat periods in Cluj-Napoca city in the summer of 2015. The heat wave events were identified based on daily maximum temperature, and they were divided into three classes considering the intensity threshold: moderate heat waves (daily maximum temperature exceeding the 90th percentile), severe heat waves (daily maximum temperature over the 95th percentile), and extremely severe heat waves (daily maximum temperature exceeding the 98th percentile). The minimum length of an event was of minimum three consecutive days. The surface urban heat island was detected based on land surface temperature derived from Landsat 8 thermal infrared data, while the economic impact was estimated based on data on work force structure and work productivity in Cluj-Napoca derived from the data released by Eurostat, National Bank of Romania, and National Institute of Statistics. The results indicate that the intensity and spatial extension of surface urban heat island could be governed by the magnitude of the heat wave event, but due to the low number of satellite images available, we should consider this information only as preliminary results. Thermal infrared remote sensing has proven to be a very efficient method to study surface urban heat island, due to the fact that the synoptic conditions associated with heat wave events usually favor cloud free image. The resolution of the OLI_TIRS sensor provided good results for a mid-extension city, but the low revisiting time is still a drawback. The potential economic loss was calculated for the working days during heat waves and the estimated loss reached more than 2.5 mil. EUR for each heat wave day at city scale, cumulating more than 38 mil. EUR for the three cases considered.     

Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models

Simulation and projection of the characteristics of heat waves over China were investigated using 12 CMIP5 global climate models and the CN05.1 observational gridded dataset. Four heat wave indices (heat wave frequency, longest heat wave duration, heat wave days, and high temperature days) were adopted in the analysis. Evaluations of the 12 CMIP5 models and their ensemble indicated that the multi-model ensemble could capture the spatiotemporal characteristics of heat wave variation over China. The inter-decadal variations of heat waves during 1961–2005 can be well simulated by multi-model ensemble. Based on model projections, the features of heat waves over China for eight different global warming targets (1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0 °C) were explored. The results showed that the frequency and intensity of heat waves would increase more dramatically as the global mean temperature rise attained higher warming targets. Under the RCP8.5 scenario, the four China-averaged heat wave indices would increase from about 1.0 times/year, 2.5, 5.4, and 13.8 days/year to about 3.2 times/year, 14.0, 32.0, and 31.9 days/year for 1.5 and 5.0 °C warming targets, respectively. Those regions that suffer severe heat waves in the base climate would experience the heat waves with greater frequency and severity following global temperature rise. It is also noteworthy that the areas in which a greater number of severe heat waves occur displayed considerable expansion. Moreover, the model uncertainties exhibit a gradual enhancement with projected time extending from 2006 to 2099.     

Spatiotemporal changes in the size and shape of heat waves over North America

Heat waves are occurring more frequently across the globe and are likely to increase in intensity and duration under climate change. Much work has already been completed on attributing causes of observed heat waves and on modeling their future occurrence, but such efforts are often lacking in exploration of spatial relationships. Based on principles of landscape ecology, we utilized fragmentation metrics to examine the spatiotemporal changes in heat wave shape and occurrence across North America. This methodological approach enables us to examine area, shape, perimeter, and other key metrics. The application of these shape metrics to high-resolution historical (1950–2013) climate data reveals that the total number and spatial extent of heat waves are increasing over the continent, but at an individual heat wave patch level, they are becoming significantly smaller in extent and more complex in shape, indicating that heat waves have become a more widespread and fragmented phenomena.     

Heat waves in the United States: definitions, patterns and trends

High temperatures and heat waves are related but not synonymous concepts. Heat waves, generally understood to be acute periods of extreme warmth, are relevant to a wide range of stakeholders because of the impacts that these events have on human health and activities and on natural environments. Perhaps because of the diversity of communities engaged in heat wave monitoring and research, there is no single, standard definition of a heat wave. Experts differ in which threshold values (absolute versus relative), duration and ancillary variables to incorporate into heat wave definitions. While there is value in this diversity of perspectives, the lack of a unified index can cause confusion when discussing patterns, trends, and impacts. Here, we use data from the North American Land Data Assimilation System to examine patterns and trends in 15 previously published heat wave indices for the period 1979–2011 across the Continental United States. Over this period the Southeast region saw the highest number of heat wave days for the majority of indices considered. Positive trends (increases in number of heat wave days per year) were greatest in the Southeast and Great Plains regions, where more than 12 % of the land area experienced significant increases in the number of heat wave days per year for the majority of heat wave indices. Significant negative trends were relatively rare, but were found in portions of the Southwest, Northwest, and Great Plains.     

广东高温热浪致人体健康风险区划

本文采用国际上通用的自然灾害风险概念和分析方法,从高温热浪致人体健康风险的构成出发,分别构建了广东省高温热浪危险性指数、暴露度指数和承灾体脆弱性指数（含敏感性指数和适应性指数）,在定量化的风险指数基础上尝试进行风险区划研究。结果表明：高危险性区域位于广东东北部、西北部以及中部偏西地区,低危险性区域主要分布在沿海地区;人体健康高敏感性区域主要位于粤北和粤西,珠三角及粤东南沿海地区敏感性相对较低;适应性较高区域主要分布在珠三角地区,其他地区适应性较低,粤东和西南部分地区适应性最低;风险较高区域主要集中在粤东、粤西北和中部偏西及雷州半岛南部地区,风险较低区域主要在珠江三角洲及其以西沿海地区。该风险指数能较好地反映广东省高温热浪致人体健康风险的分布状况。