热气候指数评价中国南方城市夏季舒适度

利用南方14个城市1981-2013年6-9月的逐日气象资料,根据生物环境特点,制定了基于通用热气候指数的新评价方法,对中国南方城市夏季舒适度进行评价研究。结果表明:中国南方城市的高温不舒适天数近33 a来以3.4 d/10a的速度增加,并有5 a震荡周期。舒适度排名显示,体感温度最高的4个城市分别为重庆、福州、南昌和长沙,杭州与重庆的体感舒适度下降速率较快。对比高温不舒适天数和高温日数发现,两者具有很好的一致性,证明了高温不舒适度与气温关系的密切性。同时,由于热气候指标计算要素的多重考虑,结果与高温日数存在一些差异,但其更具有一定参考和应用价值。     

宁波市高温中暑气象等级评定方法研究

利用1980—2014年宁波市气象观测资料和2011—2014年6—8月宁波市中暑病例资料,基于现有中暑气象等级,通过对气象因素和中暑事件进行相关分析,采用分位数法建立了新的中暑气象等级。结果表明:本文采用第45、第70和第85分位数对宁波市日最高气温和炎热指数进行了新的等级划分,并结合中暑事件与高温持续时间对高温中暑气象等级划分进行了改进,将宁波地区中暑气象等级分为可能发生中暑、易发生中暑、较易发生中暑和极易发生中暑4个等级。对改进的高温中暑气象等级验证和对比分析表明,改进后的高温中暑气象等级划分标准更适合宁波地区,由气象条件和中暑实况确定的高温中暑等级基本可反映人体中暑的风险,对实际中暑气象等级预报更具指导作用。     

天津市脑卒中高住院风险的气象原因探析

气象条件的剧烈变化可增加脑卒中危险人群的患病几率。本研究收集天津市2016—2020年脑卒中日住院数据以及气象数据,采用脑卒中日住院人数累积概率分布进行住院风险等级划分,通过相关分析确定高影响气象因子,并利用分布滞后非线性模型与半参数广义相加模型开展高影响气象因子不同时间尺度变化、滞后以及累积效应对脑卒中住院风险的影响研究。结果表明:天津市脑卒中年住院人数约为22.5万,最高月住院人数可达2.1万,日均住院人数为623。男、女住院人数比为8:5,50岁以上人群为易患脑卒中疾病的高危人群。深秋（10—11月）、初冬（12月）和春季（3—5月）为天津市脑卒中住院高风险期。6℃以上的月变温和24 h负变温相叠加可加大脑卒中住院风险,且月变温为负变温时,脑卒中住院风险最高。30℃以上高温和?5℃以下低温均可引起脑卒中住院高风险,低温带来的脑卒中住院风险高于高温,低温效应在滞后2—3 d达到最强。24 h负变温的住院风险高于正变温,且变温幅度越大住院风险越高,7℃以上24 h负变温在滞后3—5 d的住院风险最高。天津市脑卒中高住院风险的气象原因主要是月尺度和日尺度温度剧烈变化的叠加,其次为极端温度及其24 h剧烈变化的影响。      

体感温度对夏季气象负荷率变化的影响研究——以湖北省黄石市为例

本文以黄石市2007-2013年逐日电力负荷为研究对象,利用同期气象资料计算体感温度数据及舒适度等级,并以此对电力负荷进行分解,进而讨论体感温度对夏季气象负荷率变化的影响。结果表明:(1)利用体感温度及舒适度等级可对电力负荷进行更精细的分解,且体感温度同气象负荷率具有最高关联度;(2)研究时段内黄石市逐日最大电力负荷总体呈线性增长,但2008年金融危机期间电力负荷呈下降趋势;(3)2010年之前,工作日的气象负荷率高于节假日,但自2011年起,该现象出现反转,且差值逐渐增大;(4)研究时段内,体感温度高于22.9℃(工作日)或21.5℃(节假日)时,即会产生敏感负荷,而体感温度升高1℃最多可引起6%的气象负荷率增加。     

基于GIS的洛阳市高温灾害风险区划

利用洛阳市1961-2010年历史气候资料和地理信息数据,通过分析高温灾害致灾因子、孕灾环境因子、承灾体易损性因子和防灾减灾因子4个因子的指标,利用层次分析法确定各个因子指标的权重建立高温气象灾害风险评价体系。其中选取洛阳市9个观测站高温日数,并运用皮尔逊Ⅲ型概率密度模型分别从不同频率推测高温影响程度并分析高温危险性因子;利用洛阳市基础地理信息数据,选取海拔高度和河网密度作为评价孕灾环境因子指标;利用洛阳市土地利用分类分析不同土地类型承载体潜在易损性,同时考虑高温易受伤害人群的人口比例怍为承载体易损性因子指标;防灾减灾因子利用各乡镇财政一般收入水平和人均可支配收入作为量化指标。从区划图中可以看出：总体高温风险等级北部高于南部;东北部、中部风险等级最高,其中偃师中部、伊川西部和南部地区、嵩县北部地区风险等级最高;次高风险等级主要分布在新安、宜阳、伊川中东部、孟津东部和西部、嵩县中部等地区;栾川、嵩县南部、洛宁西部风险等级最低。     

1991—2019年呼和浩特市人体舒适度变化特征分析

基于"黄金分割率"的体感温度计算及相应舒适度划分法,利用呼和浩特市1991—2019年7个气象观测站逐日数据,分析了人体舒适度等级和日数不同尺度的时空变化特征,并分析了各气象因子与体感温度间的相关关系.结果表明:呼和浩特市不同舒适度等级日数所占比例由大到小依次为严寒域日数、广义舒适域日数和酷热域日数.其中广义舒适域日数...     

杭州地区人体舒适度对自然死亡人数的影响

选取涵盖温度、湿度和降水等要素的体感温度及人体舒适度等级划分方法,以杭州地区为研究对象,探讨1998年8月至2007年7月杭州地区人体舒适度对自然死亡人数及不同性别、年龄、典型疾病死亡人数的具体影响。结果表明:1998年8月至2007年7月杭州地区体感温度与自然死亡人数之间大致呈二次多项式分布,当体感温度约为25.5℃时日平均死亡人数达最低值,体感温度对死亡人数滞后影响以3—5 d滞后相关最显著。以36.51人为阈值,杭州地区死亡高峰日多出现冬季,偶尔出现在夏季,5月和10月人体舒适度等级最高。男女死亡人数与体感温度均呈显著的负相关关系,男性日平均死亡人数略高于女性,冷不舒适的影响高于热不舒适的影响。老年和中年死亡人数与体感温度均呈显著的负相关关系,且老年人对温度的敏感性最大,婴幼儿和少年、青年死亡人数受体感温度的影响较小,日平均死亡人数由高至低依次为老年、中年、青年、婴幼儿、少年。循环系统和呼吸系统疾病死亡人数与体感温度均呈显著的负相关关系,而体感温度与肿瘤死亡人数呈显著的正相关关系,日平均死亡人数由高至低依次为肿瘤、循环系统和呼吸系统疾病,但呼吸系统疾病对体感温度的变化较敏感。     

西安呼吸系统疾病气象风险指数等级预报研究与应用

利用2010年1月1日—2014年12月31日西安市呼吸系统疾病死亡数据与相应的气象观测数据,选取与呼吸系统疾病有显著相关性的气象因子,采用多元逐步回归方法,建立呼吸系统疾病死亡人数预测模型和呼吸系统疾病气象风险指数等级预报方法,并对预测模型和等级预报进行了检验。结果表明：呼吸系统疾病日死亡人数预测模型准确率在795%以上,呼吸系统疾病气象风险指数等级预报准确率达到98%,预测预报效果较好。将呼吸系统疾病气象风险指数等级预报融入西安公共气象指数预报服务系统,制作呼吸系统疾病气象风险指数等级预报、预警产品,并通过全方位融媒体发布手段开展健康气象预报预警服务。     

人体舒适度的分析与预报

大气温度、湿度、风、太阳辐射等是影响人体舒适度的气象因子,也是影响体感温度的气象因子.因此人体舒适度与体感温度关系密切.根据体感温度计算结果和旬平均气温,可确定人体舒适度等级.     

基于信息扩散理论的贵州省高温分布特征及风险分析

该文将贵州省高温易发区分为北部、东北部、东南部、南部4个区域,选取其中主要的38个国家级气象观测站1961—2019年逐日最高气温,描述高温分布特征,并基于信息扩散理论对灾害危险性风险进行分析。结果表明:(1)研究区域的高温主要出现在4—9月;平均日最高气温总体呈上升趋势,年际变化先降后升;平均年高温日数为10.7 d,主要集中在7、8月,年际变化呈现波动式,但整体呈上升趋势;极端高温大部分地区在38.0～42.0℃之间,大部分地区极端高温呈维持—升高态势。(2)赤水、沿河、榕江、罗甸4个代表站的高温度数风险概率曲线均为单弧线型,区域风险面积随等级的增加逐渐减小;4个代表站的最长连续高温日数风险概率曲线为多峰型,大部分地区连续高温日数出现5 d以下的概率较大,16 d以上高风险值的几率很小。(3) 4个高温易发区中,北区除赤水外,高温风险整体最低,且连续高温日数短;东北区高温风险在4个区域中风险最高,连续高温风险随连续日数的增大而增大;东南区高温风险呈南高北低态势;南区除罗甸高温风险较高外,其他站点整体为中低风险。     

Spatiotemporal change in China’s climatic growing season: 1955–2000

The timing, length, and thermal intensity of the climatic growing season in China show statistically significant changes over the period of 1955 to 2000. Nationally, the average start of the growing season has shifted 4.6–5.5 days earlier while the average end has moved 1.8–3.7 days later, increasing the length of the growing season by 6.9–8.7 days depending on the base temperature chosen. The thermal intensity of the growing season has increased by 74.9–196.8 growing degree-days, depending on the base temperature selected. The spatial characteristics of the change in the timing and length of the growing season differ from the geographical pattern of change in temperatures over this period; but the spatial characteristics of change in growing degree-days does resemble the pattern for temperatures, with higher rates in northern regions. Nationally, two distinct regimes are evident over time: an initial period where growing season indicators fluctuate near a base period average, and a second period of rapidly increasing growing season length and thermal intensity. Growing degree-days are highly correlated with March-to-November mean air temperatures in all climatic regions of China; the length of the growing season is likewise highly correlated with March-to-November mean air temperatures except in east, southeast and southwest China at base temperature of 0°C and southeast China at base temperature of 5°C. The growing season start date appears to have the greater influence on the length of the growing season. In China, warmer growing seasons are also likely to be longer growing seasons.     

Urban heat island and differences in outdoor comfort levels in Glasgow, UK

From extensive outdoor comfort campaigns, preliminary outdoor comfort ranges have been defined for the local population of Glasgow, UK, in terms of two thermal indices: ‘Temperature Humidity Sun Wind’ (THSW) and ‘Physiological Equivalent Temperature’ (PET). A series of measurements and surveys was carried out from winter through summer 2011 during 19 monitoring campaigns. For data collection, a Davis Vantage Pro2 weather station was used, which was equipped with temperature and humidity sensors, cup anemometer with wind vane, silicon pyranometer and globe thermometer. From concurrent measurements using two weather stations, one located close to the city core and another located at a rural setting, approximately at a 15-km distance from the urban area of Glasgow, comparisons were made with regard to thermal comfort levels and to urban–rural temperature differences for different periods of the year. It was found that the two selected thermal indices (THSW and PET) closely correlate to the actual thermal sensation of respondents. Moreover, results show that the urban site will have fewer days of cold discomfort, more days of ‘neutral’ thermal sensation and slightly higher warm discomfort. The most frequent urban heat island intensity was found to be around 3° C, whereas the fraction of cooling to heating degree-hours for a T _base of 65 °F was approximately 1/12th.     

基于灾害风险理论的湖北水稻高温热害风险分析及区划

高温热害是长江流域最主要的气象灾害之一,科学评估热害风险是防灾减灾的基础。本文利用近60年气象观测资料,对湖北高温热害的时空分布特征进行了分析;基于自然灾害风险基本理论,建立了包括影响水稻结实率关键期的热害强度、灾害发生时承灾体实际暴露度、灾害脆弱性等因素的高温热害风险评价模型,并进行了风险分析与区划。结果表明：高温天气出现概率高的时段是7月下旬,其中7月第6候为最高。从高温热害风险指数上来看,7月第3候抽穗开花水稻的热害风险最高,此后随时间的推移,热害风险降低;湖北现行的一季中稻抽穗开花期处于风险较高的时段,推迟5天其热害风险指数可下降20%左右;推迟15天以上热害风险指数将降低50%以上。江汉平原稻区是湖北高温热害风险低发地区,鄂东南及鄂西北地区是热害风险高发地区;针对各区热害特点提出了风险应对措施。     

Changing Trends of Daily Temperature Extremes with Different Intensities in China

By comparing two sets of quality-controlled daily temperature observation data with and without the inhomogeneity test and adjustment from 654 stations in China during 1956-2004 and 1956-2010, impacts of inhomogeneity on changing trends of four percentile temperature extreme indices, including occurrences of cold days, cold nights, warm days, and warm nights with varying intensities, were discussed. It is found that the inhomogeneity affected the long-term trends averaged over extensive regions limitedly. In order to minimize the inhomogeneity impact, the 83 stations identified with obvious inhomogeneity impacts were removed, and an updated analysis of changing trends of the four temperature extreme indices with varying intensities during 1956-2010 was conducted. The results show that annual occurrences of both cold nights and cold days decreased greatly while those of warm nights and warm days increased significantly during the recent 20 years. The more extreme the event is, the greater the magnitude of changing trends for the temperature extreme index is. An obvious increasing trend was observed in annual occurrences of cold days and cold nights in the recent four years. The magnitude of changing trends of warm extreme indices was greater than that of cold extreme indices, and it was greater in northern China than in southern China. Trends for summer occurrence of cold days were not significant. Decreasing trends of occurrences of both cold nights and cold days were the greatest in December, January, and February (DJF) but the least in June, July, and August (JJA), while increasing trends of warm nights were the greatest in JJA. Cold nights significantly decreased from 1956 to 1990, and then the decreasing trend considerably weakened. The decreasing trend also showed an obvious slowdown in recent years for occurrence of cold days. However, increasing trends of warm nights and warm days both have been accelerated continuously since the recent decades. Further analysis presents that the evolution of the trends for occurrences of the four temperature extreme indices was dominated by the changes in northern China.     

The Characteristics and Controlling Factors of Water and Heat Exchanges over the Alpine Wetland in the East of the Qinghai–Tibet Plateau

Alpine wetland is one of the typical underlying surfaces on the Qinghai–Tibet Plateau. It plays a crucial role in runoff regulation. Investigations on the mechanisms of water and heat exchanges are necessary to understand the land surface processes over the alpine wetland. This study explores the characteristics of hydro-meteorological factors with in situ observations and uses the Community Land Model 5 to identify the main factors controlling water and heat exchanges.Latent heat flux and therm...     

近50年我国日平均气温的气候变化

应用近50年我国234个测站的日平均温度资料，研究了最高(低)日平均温度、各种界限温度日数、生长季节长度及有效积温的变化趋势。结果表明:近50年，夏季最高日平均温度以上升为主，新疆南部和黄淮的部分地区为下降趋势；最低日平均温度北方大部地区有较明显的升温趋势，新疆南部及长江流域则有下降趋势；在冬季，无论是最高日平均温度还是最低日平均温度的变化趋势均以上升为主，北方尤为明显；日平均温度高于30℃的炎热日数近50年来基本上没有什么变化，但日平均温度为20~30℃的温暖日数却有增加。低于5℃的冷日日数基本上也是减少的。日平均温度低于-10℃的严寒日数，在40o~45 o N的新疆、内蒙古西部、东北中南部地区减少得更为明显。除西南东部等少数地方外，我国大部分地区近50年来生长季节延长，有效积温增加。     

我国冬季感热温度分布和人体保暖所需服装量

本文从人体热量平衡观点出发,根据美国著名生物气象学家R·G·Steadman提出的感热温度理论(1—4),计算了我国各地冬季(12—2月)各月的平均感热温度,并讨论了人体保暖所需的服装量。     

Future Changes in Extreme High Temperature over China at 1.5℃-5℃ Global Warming Based on CMIP6 Simulations

Extreme high temperature(EHT)events are among the most impact-related consequences related to climate change,especially for China,a nation with a large population that is vulnerable to the climate warming.Based on the latest Coupled Model Intercomparison Project Phase 6(CMIP6),this study assesses future EHT changes across China at five specific global warming thresholds(1.5℃-5℃).The results indicate that global mean temperature will increase by 1.5℃/2℃ before 2030/2050 relative to pre-industrial levels(1861-1900)under three future scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5),and warming will occur faster under SSP5-8.5 compared to SSP1-2.6 and SSP2-4.5.Under SSP5-8.5,global warming will eventually exceed 5℃ by 2100,while under SSP1-2.6,it will stabilize around 2℃ after 2050.In China,most of the areas where warming exceeds global average levels will be located in Tibet and northern China(Northwest China,North China and Northeast China),covering 50%-70%of the country.Furthermore,about 0.19-0.44 billion people(accounting for 16%-41%of the national population)will experience warming above the global average.Compared to present-day(1995-2014),the warmest day(TXx)will increase most notably in northern China,while the number of warm days(TX90p)and warm spell duration indicator(WSDI)will increase most profoundly in southern China.For example,relative to the present-day,TXx will increase by 1℃-5℃ in northern China,and TX90p(WSDI)will increase by 25-150(10-80)days in southern China at 1.5℃-5℃ global warming.Compared to 2℃-5℃,limiting global warming to 1.5℃ will help avoid about 36%-87%of the EHT increases in China.     

Trends in Temperature Extremes in Association with Weather-Intraseasonal Fluctuations in Eastern China

Trends in the frequencies of four temperature extremes (the occurrence of warm days, cold days, warm nights and cold nights) with respect to a modulated annual cycle (MAC), and those associated exclusively with weather-intraseasonal fluctuations (WIF) in eastern China were investigated based on an updated homogenized daily maximum and minimum temperature dataset for 1960–2008. The Ensemble Empirical Mode Decomposition (EEMD) method was used to isolate the WIF, MAC, and longer-term components from the temperature series. The annual, winter and summer occurrences of warm (cold) nights were found to have increased (decreased) significantly almost everywhere, while those of warm (cold) days have increased (decreased) in northern China (north of 40°N). However, the four temperature extremes associated exclusively with WIF for winter have decreased almost everywhere, while those for summer have decreased in the north but increased in the south. These characteristics agree with changes in the amplitude of WIF. In particular, winter WIF of maximum temperature tended to weaken almost everywhere, especially in eastern coastal areas (by 10%–20%); summer WIF tended to intensify in southern China by 10%–20%. It is notable that in northern China, the occurrence of warm days has increased, even where that associated with WIF has decreased significantly. This suggests that the recent increasing frequency of warm extremes is due to a considerable rise in the mean temperature level, which surpasses the effect of the weakening weather fluctuations in northern China.     

近56年我国暖冬气候事件变化

对冬季平均气温序列采用三分位方法确定单站暖冬阈值, 并将单站暖冬分为弱和强两个等级。以此为基础, 确定区域暖冬和全国暖冬的界定方法和等级划分标准。区域暖冬采用站点相对比例确定, 全国暖冬采用暖冬面积相对比例界定。对我国1952— 2007年的暖冬事件变化特征的分析结果表明:南方暖冬频率高于北方, 强暖冬多发区出现在我国中西部地区; 北方单站暖冬指数上升幅度大于南方, 表明北方暖冬事件上升趋势更加明显; 以1986年为界, 前期 (1952— 1985年) 南、北方各区域均很少出现暖冬, 南方各区暖冬频率略高于北方各区, 后期 (1986—2007年) 各区暖冬年大为增加, 北方各区增加最明显且超过了南方; 56年中, 全国性暖冬共发生15次 (年), 其中强暖冬共有5次 (年); 全国暖冬指数呈显著上升趋势, 在有效面积不变的情况下, 暖冬面积每10年增加10%。