Future heat vulnerability in California, Part I: projecting future weather types and heat events

Excessive heat significantly impacts the health of Californians during irregular but intense heat events. Through the 21st century, a significant increase in impact is likely, as the state experiences a changing climate as well as an aging population. To assess this impact, future heat-related mortality estimates were derived for nine metropolitan areas in the state for the remainder of the century. Here in Part I, changes in oppressive weather days and consecutive-day events are projected for future years by a synoptic climatological method. First, historical surface weather types are related to circulation patterns at 500mb and 700mb, and temperature patterns at 850mb. GCM output is then utilized to classify future circulation patterns via discriminant function analysis, and multinomial logistic regression is used to derive future surface weather type at each of six stations in California. Five different climate model-scenarios are examined. Results show a significant increase in heat events over the 21st century, with oppressive weather types potentially more than doubling in frequency, and with heat events of 2?weeks or longer becoming up to ten times more common at coastal locations.     

Synoptic Typing and Its Application for Evaluating Climatic Impact on Air Quality in Urumqi

An automated procedure employing principal-component analysis and a two-stage cluster analysis was developed to classify the synoptic meteorological conditions prevailing over Urumqi, one of the most heavily polluted cities in the world. Six clusters representing different circulation patterns and air-mass characteristics were classified using surface- and upper-meteorological variables during the heating period from 2001 to 2008, and the relationships between synoptic clusters and air quality were evaluated. The heaviest air-pollution episodes occurred when Urumqi was in either an extremely cold, strong anticyclone or at the front of a migrating cyclone, both with light winds, wet surface air, and relatively dry upper air. Moderate pollution was seen when Urumqi was in the pre-cold/cold frontal passages with lower temperatures and light winds or moderate anticyclone with relatively warmer, drier air. When Urumqi was at the front of a migrating anticyclone or in a weak anticyclone with moderate winds and most warm, dry air, or in the cold/post-cold frontal passages with relatively strongly northerly airflows and precipitation, relatively good air quality could be seen. These results suggest that air pollution in Urumqi is very closely related to the synoptic meteorological conditions, which provides an important basis for not only the prediction and control of urban air-quality problems here but also for the analysis of the differential impacts of weather and pollution on human morbidity.     

Synoptic comparison of cold events in winter and summerin Melbourne and Perth

Summary  Unseasonably cold weather episodes have the potential to cause dislocation to many aspects of society, regardless of the season in which they occur. In this work we devise a method for quantitatively identifying extreme cold events in such a way that it is not biased to the winter season (as is usual in most other studies). We have applied this method to the daily maximum temperatures (over the period January 1972 to June 1991) in the southern Australian cities of Melbourne and Perth. We identify 10 cold events in winter and summer for the cities. Analyses were performed to determine the synoptic environment in which these events occurred. The most common synoptic type in these samples was the ‘classic’, which is characterised by, amongst other factors, the passage of a cold front over the city on the day of the outbreak, and the transport of air from subantarctic latitudes. Melbourne recorded five such events in summer and six in winter, while seven and eight occurred in the two seasons for Perth. The circulation features and characteristics of other synoptic types identified with these episodes is also examined. The mean synoptic anomalies which are coincident with these cold events are analysed. For both cities and seasons there is a ‘high-low’ anomalous dipole in the regional MSLP pattern, with the high located in the ‘upstream’ quadrant from the anomalous cyclone. Having said this, the relative importance of the two features of the dipole in being associated with the cold event strongly depended on the city and season under consideration. The research shows that the regional structures associated with cold events in Melbourne and Perth bear some similarity, but also display a number of significant differences. These differences are associated partly with the different climatological and synoptic settings in which these cities find themselves, and the nature of their seasonality. Received October 10, 1999/Revised April 7, 2000     

Differences in Meteorological Conditions between Days with Persistent and Non-Persistent Pollution in Beijing,China

We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP–Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency (period < 90 days) variations in meteorological conditions on persistent pollution events (those lasting for at least 3 days). Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather conditions. Some results from this study are based on a limited number of events and thus require validation using more data.     

Synoptic aspects of wet and dry conditions in central Australia: observations and GCM simulations for 1 × CO2 and 2 × CO2 conditions

Synoptic climatological patterns that produce anomalous wet conditions in central Australia during the period from September to April have been studied. The analysis was done by using observed daily rainfall data at a number of stations, wind and mean sea level pressure from the European Centre for Medium Range Weather Forecasts (ECMWF), Tropical Ocean and Global Atmosphere (TOGA) data from 1985 to 1991, and the CSIRO 9-level (CSIR09) global climate model (GCM) simulated data for 1 × CO₂ and 2 × CO₂ experiments. On the basis of rainfall values above 99.5 percentile in observed and simulated data, wet days have been selected to study the synoptic-scale weather systems that produce anomalous wet events in central Australia. As the vast majority of days in central Australia are dry, the same number of days with no rainfall for both observed and simulated conditions have been selected randomly. The observed synoptic climatological patterns have been compared with the results of the control simulation of CSIRO9. A comparison between CSIRO9 simulated synoptic patterns and observed synoptic patterns reveals that the model fairly well captures the synoptic climatological characteristics which produce anomalous wet and contrasting dry weather conditions during the period from September to April. Under enhanced greenhouse experiments, the main features of the synoptic patterns are intensified both for wet and dry conditions, which result in an increase in extreme weather conditions, an increase in rainfall intensity, a spatial expansion of the heavy rainfall region during wet days, and an expansion of the dry area during dry days. During anomalous wet conditions, the low pressure area is intensified, monsoonal winds and southeasterlies are strengthened and strong wind shear over tropical Australia is simulated. During this condition, the monsoon shear line moves poleward particularly over the Northern Territory. In contrast, during dry conditions, the anticyclonic circulation over the continent is strengthened.     

福州市空气高污染与气象条件关系

利用地面天气图、高空天气图、地面气象要素资料,统计分析了2003-2007年福州市41个空气高污染过程与天气系统以及地面气象要素间的关系,得出冬季、春季和夏秋季福州市空气高污染发生时主要的天气形势,并对地面气象要素与高污染过程的关系进行了半定量分析,得出福州市空气高污染过程的一些天气概念模型和气象要素指标。     

Possible impacts of climate change on extreme weather events at local scale in south–central Canada

Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south–central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century over south–central Canada under a changing climate. The implications of these increases need be taken into consideration and integrated into policies and planning for adaptation strategies, including measures to incorporate climate change into engineering infrastructure design standards and disaster risk reduction measures. This paper briefly summarized these climate change research projects, focusing on the modeling methodologies and results, and attempted to use plain language to make the results more accessible and interesting to the broader informed audience. These research projects have been used to support decision-makers in south–central Canada when dealing with future extreme weather events under climate change.     

关于气象与人体健康研究的几个问题

关于气象、环境与健康问题的研究可总结为如下几个问题:1)气候变化及其影响,2)天气、气候变化与人类健康,3)大气污染与人类健康,4)关于气象条件与疾病的机理研究,5)环境与健康危险度评价。作者认为以下几个问题值得我国学者予以关注:1)气象与健康问题的检测,2)气侯变化与人类健康,3)气象与人类健康关系的机理研究,4)应用数值模式研究气象与健康问题,5)环境与健康危险度评价,6)疾病预测和预警研究,7)多学科交叉研究和更多部门对气象与健康问题的介入。     

京津冀采暖期大气污染天气特征

选取2004—2006年京津冀地区采暖期155个区域大气污染日,对当日08:00(或前一日20:00)海平面气压场,结合高空环流特征进行了分析。对影响京津冀区域污染的天气形势划分为5种类型,即高压型、冷锋型、低压型、华北干槽型和均压场型,其中高压型最多,占40.0%。区域污染过程通常对应一次高空环流调整过程,连续性区域污染过程往往由多种天气型影响。地面辐合加上低层逆温和下沉运动阻碍污染物在水平和垂直方向的扩散,在污染源一定的条件下,稳定的大气层结和区域内特殊地形的影响是导致区域污染形成的重要原因。     

Prediction of extreme rainfall event using weather pattern recognition and support vector machine classifier

A major component of flood alert broadcasting is the short-term prediction of extreme rainfall events, which remains a challenging task, even with the improvements of numerical weather prediction models. Such prediction is a high priority research challenge, specifically in highly urbanized areas like Mumbai, India, which is extremely prone to urban flooding. Here, we attempt to develop an algorithm based on a machine learning technique, support vector machine (SVM), to predict extreme rainfall with a lead time of 6–48 h in Mumbai, using mesoscale (20–200 km) and synoptic scale (200–2,000 km) weather patterns. The underlying hypothesis behind this algorithm is that the weather patterns before (6–48 h) extreme events are significantly different from those of normal weather days. The present algorithm attempts to identify those specific patterns for extreme events and applies SVM-based classifiers for extreme rainfall classification and prediction. Here, we develop the anomaly frequency method (AFM), where the predictors (and their patterns) for SVM are identified with the frequency of high anomaly values of weather variables at different pressure levels, which are present before extreme events, but absent for non-extreme conditions. We observe that weather patterns before the extreme rainfall events during nighttime (1800 to 0600Z) is different from those during daytime (0600 to 1800Z) and, accordingly, we develop a two-phase support vector classifier for extreme prediction. Though there are false alarms associated with this prediction method, the model predicts all the extreme events well in advance. The performance is compared with the state-of-the-art statistical technique fingerprinting approach and is observed to be better in terms of false alarm and prediction.     

Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events

The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate.Many investigations have been conducted to reveal the relationship between the Arctic and Eurasian extreme events from the perspective of climatological statistics.As a prediction source for extreme events in Eurasia,Arctic conditions are crucial for extreme event predictions.Therefore,it is urgent to explore the Arctic influence on the predictability of Eurasian extreme events due to the large uncertainties in Arctic conditions.Considering the sensitivity and nonlinearity of the atmospheric circulations in midlatitude to Arctic conditions,it is necessary to investigate the Arctic influences on Eurasian extreme weather events in case studies at weather time scales.Previous studies indicate that only perturbations in specific patterns have fast growth.Thus,the conditional nonlinear optimal perturbation approach is recommended for exploring the uncertainties in Arctic initial and boundary conditions and their synergistic effect on Eurasian extreme events.Moreover,the mechanism for extreme event formation may differ in different cases.Therefore,more extreme cases should be investigated to reach robust conclusions.     

Improved atmospheric circulation over Europe by the new generation of CMIP6 earth system models

Global Climate Models (GCMs) generally exhibit significant biases in the representation of large-scale atmospheric circulation. Even after a sensible bias adjustment these errors remain and are inherited to some extent by the derived downscaling products, impairing the credibility of future regional projections. In this study we perform a process-based evaluation of state-of-the-art GCMs from CMIP5 and CMIP6, with a focus on the simulation of the synoptic climatological patterns having a most prominent effect on the European climate. To this aim, we use the Lamb Weather Type Classification (LWT, Lamb British isles weather types and a register of the daily sequence 736 of circulation patterns 1861-1971. METEOROL OFF, GEOPHYS MEM; 737 GB; DA 1972; NO 116; PP 1-85; BIBL 2P1/2, 1972), a subjective classification of circulation weather types constructed upon historical simulations of daily mean sea level pressure. Observational uncertainty has been taken into account by considering four different reanalysis products of varying characteristics. Our evaluation unveils an overall improvement of salient atmospheric circulation features consistent across observational references, although this is uneven across models and large frequency biases still remain for the main LWTs. Some CMIP6 models attain similar or even worse results than their CMIP5 counterparts, although in most cases consistent improvements have been found, demonstrating the ability of the new models to better capture key synoptic conditions. In light of the large differences found across models, we advocate for a careful selection of driving GCMs in downscaling experiments with a special focus on large-scale atmospheric circulation aspects.

     

2015—2018年海南省臭氧污染特征及其天气类型

根据2015—2018年海南省18个市县32个空气质量监测站O₃浓度资料,分析了区域性O₃污染（O₃-8h浓度超标市县≥3个）时空变化特征,并对造成O₃污染的天气系统进行主观分型。结果表明：2015—2018年海南省共有40 d发生了区域性O₃污染,发生概率为2.73%。其中2015年和2017年达到了13 d,发生概率为3.56%,2018年为11 d（3.01%）,2016年仅为3 d（0.82%）。发生区域性O₃污染主要有4种天气类型：冷空气偏西下型、冷空气偏东下型、变暖高压脊型和热带系统型。其中冷空气偏西下型是最主要的天气类型,共出现了14 d,占所有天数的35%,且污染较重。不同天气类型下海南省O₃污染表现出不同的分布特征。500 hPa有下沉气流、低层受东北风控制,有相对湿度低值区从中国东部向海南省延伸,地面位于冷高压底部或热带气旋西北侧,温度露点差在5 ℃以上等条件均有利于海南省区域性O₃污染天气出现。     

Using synoptic classification and trajectory analysis to assess air quality during the winter heating period in Ürümqi,China

Synoptic patterns identified by an automated procedure employing principal- component analysis and a two-stage cluster analysis, and backward trajectory analysis clustered by the HYSPLIT4.9 model were used to examine air quality patterns over¨ Uru¨mqi, China, one of the most heavily polluted cities in the world. Six synoptic patterns representing different atmospheric circulation patterns and air-mass characteristics were classified during the winter heating periods from 2001 to 2008, and seven trajectory clusters representing different paths of air masses arriving at ürümqi were calculated during the winter heating periods from 2005 to 2008. Then air quality was evaluated using these two approaches, and significant variations were found across both synoptic patterns and trajectory clusters. The heaviest air-pollution episodes occurred when ürümqi was either in an extremely cold, strong anticyclone or at the front of a migrating cyclone. Both conditions were characterized by with light winds, cold, wet surface air, and relatively dry upper air. ürümqi was predominately influenced by air masses from the southwest and from local areas. Air pollution index (API) levels were highest for air masses originating from the southwest with a longer path or for the local area, because of transport from semi-desert/desert regions by strong winds and because of local heavy pollution emissions, respectively. The interactions between these two analytical approaches showed that poor diffusion conditions, together with local circulation, enhanced air pollution, besides, regional air-mass transport caused by strong winds contributed to serious air quality under relatively good diffusion conditions.     

Synoptic and mesoscale weather conditions during air pollution episodes in Athens,Greece

Based on regular climatological and air quality data from the Greater Athens Area (GAA), the air pollution episodes observed in Athens during the period 1983–1990 were analysed and classified. The main characteristics of atmospheric conditions during days with high air pollution concentrations are summarized too. Model simulations show that the worst air pollution episodes in Athens occur during days with a critical balance between synoptic and mesoscale circulations and/or during days with warm advection in the lower troposphere.     

辽宁空气中度污染和重污染天气类型分析

统计分析了2005-2009年辽宁省14个城市5种污染物逐日的污染指数API数据,基于东北低压型、南大风型、干冷锋北大风型和夏秋大雾型四种易形成辽宁地区沙尘污染的天气类型,对污染天气类型进行归类统计分析。结果表明：重污染和中度污染天气中PM10污染所占比例最高,污染天气类型主要是干冷锋北大风型。     

Synoptic Climatology of the Southern Beaufort Sea Troposphere with Comparisons to Surface Winds

Synoptic-scale atmospheric circulation patterns drive wind forcing of dynamic and thermodynamic processes in Arctic sea ice. Synoptic typing and compositing are common techniques used to identify a limited number of prevailing weather classifications that govern a region's climate. This work investigates atmospheric circulation patterns (surface to 250?hPa) for the southern Beaufort Sea and corresponding surface wind regimes within each synoptic type. Significant changes (p?<?0.05) in relative frequencies of a number of synoptic types were attributed to declining summer sea ice. Corresponding upper-level circulation anomalies show increasingly meridional atmospheric circulation. Synoptic Types 9 and 11 were identified as key October-November-December circulation features that represent deepening of the Aleutian low with concomitant strengthening of pressure gradients over the southern Beaufort Sea. Classification of coastal-based wind observations shows a shift towards increased easterly wind forcing. A case study of surface wind data from the CCGS Amundsen (2009–2011) provided a direct example of the surface wind regime within the marginal ice zone within each synoptic type during a period of reduced Arctic sea-ice cover.     

中国当代强对流天气研究与业务进展

对当代中国几十年来强对流天气研究和业务进展做了阐述，主要包括强对流系统产生的环境背景和主要组织形态，以及具体强对流天气的有利环境条件、触发机制、卫星云图特征、多普勒天气雷达回波特征以及预报、预警技术等诸方面。总体来看，中国学者对强对流以及不同类型强对流天气（强冰雹、龙卷、雷暴大风）发生、发展的环流背景以及通过雷达和卫星观测到的组织结构及其演变特征都已有了明确认识，研究了对流系统的多种触发机制，深入认识了超级单体、飑线等对流系统的环境条件、组织结构特征和维持机制，了解了中国中尺度对流系统的组织形态和气候分布特征，获得了强冰雹、龙卷、下击暴流和雷暴大风等的雷达、卫星和闪电等的多尺度观测特征、形成机制和现场灾害调查特征，发展了各类强对流天气识别、监测和分析方法以及基于“配料法”和深度学习方法等的预报、预警技术等。因此，强对流天气业务预报水平已得到显著提升。      

DIURNAL VARIATION OF SST IN RELATION TO SEASON AND WEATHER PHENOMENA IN THE BOHAI REGION

This study investigated the relationships between sea surface temperature(SST) and weather phenomena in different seasons in the Bohai region(China). Five categories of weather phenomena were screened(i.e., fine, cloudy,foggy, rainy and windy conditions) and their relationships with the difference between air temperature and SST observed at Oil Platform A during 2003-2010 were analyzed statistically. The effects of the difference between air temperature and SST in different weather phenomena were examined using the flux method of the atmospheric boundary layer and a formula for the difference between air temperature and SST. The results revealed diurnal variation of the difference between air temperature and SST of-1.0 to +1.0 ℃, i.e., air temperature above the sea surface is subtracted from the SST in corresponding weather phenomena in different seasons in the Bohai region. Moreover,according to the formula for the difference between air temperature and SST, wind and shortwave radiation are the most important factors in terms of the effects of SST on weather processes. In conclusion, the effects of SST on weather phenomena are manifest via the exchange of momentum and energy from sea to air. When the air temperature above the sea surface is lower than the SST, the SST helps develop mesoscale convection systems within the synoptic system through moisture and sensible heat fluxes. When the air temperature above the sea surface is greater than the SST,synoptic systems transfer energy into the sea through heat flux, which affects SST variation. Moreover, a mesoscale convection system will weaken if the synoptic system passes over a colder underlying surface.     

基于自组织映射的长江中下游夏季天气分型及其降水特征

利用欧洲中心1979—2015年夏季6—8月ERA-Interim逐日再分析资料和国家气候中心CN05.1格点化降水观测数据集,引入基于自组织映射SOM(Self-Organizing Maps)方法进行长江中下游地区夏季海平面气压空间距平场的客观分型,得到该地区25种地面天气型及其系统演变特征,发现天气型的稳定、转移与天气系统强弱有关。高低压系统越强,天气型停滞频率越高,天气型越稳定;反之,天气型越不稳定。基于SOM天气型转移概率,发现三条与局地降水联系的系统演变路径,其中1号路径暖空气势力强盛,副高北上,推动锋面北抬,产生江北降水型,多发生在7月;路径2反映冷空气势力强盛推动锋面南下的天气过程,产生沿江降水型,该天气型在6、7月均易发生;路径3表现为台风移动变化对长江下游江南地区降水的影响,为江南降水型,且集中在8月。通过引入SOM方法对逐日天气尺度环流进行分型,从气候态上捕捉与降水有关的天气系统的移动变化特征,体现SOM方法在模拟天气系统演变的优势。