Assessment of the changes in extreme vulnerability over East Asia due to global warming

A number of indices have been employed to describe weather extremes on the basis of climate regimes and public concerns. In this study, we combined these traditional indices into four groups according to whether they relate to warm (T_warm), cold (T_cold), wet (P_wet), or dry (P_dry) extremes. Analysis of the combined indices calculated for the daily temperatures and precipitation at 750 meteorological stations in Korea, China, and Japan for 1960s?C2000s shows increasing trends in T_warm and P_dry events and decreasing trends in T_cold events in recent decades, particularly in the northern part of East Asia. A notable regional variation is an increase in the P_wet events in the Korean Peninsula. We applied the same analysis to a 200-year global climate model simulation for 1900?C2099 using the National Center for Atmospheric Research-Community Climate System Model 3. During the 20th century, the changes in T_warm and T_cold calculated from the model data are largely consistent with those calculated from the observations, especially in northern East Asia. The model projections for the 21st century indicate statistically significant increasing T_warm and decreasing T_cold trends in extreme events over the region. Results obtained from historical archives and model simulations using our combined weather extreme indices suggest that northern East Asia will be subject to increased warm and dry extremes and the Korea Peninsula will experience more wet extremes.     

资料均一化对沈阳站气温趋势和城市化偏差分析的影响

利用国家气象信息中心2013年发布的逐日均一化气温资料,对沈阳站资料均一化处理前后平均气温和极端气温指数序列的线性趋势及其城市化影响偏差进行了比较评价。结果表明:1)资料均一化处理对日最高气温及其衍生的极端气温指数序列趋势估计的影响较弱,但对日最低气温及其衍生的极端气温指数序列趋势估计具有显著影响。2)经资料均一化处理后,平均气温序列中的城市化影响偏差有所增大,平均最低气温序列中的城市化影响偏差增大尤其明显;与冷事件有关的极端气温指数序列的城市化影响偏差数值有所减小,与暖事件有关的极端气温指数序列的城市化影响偏差数值有所增加。3)资料均一化处理有效纠正了因迁站等原因造成的地面气温观测记录中的非均一性,但却在很大程度上还原了城市站地面气温观测记录中的城市化影响偏差。     

基于统计降尺度模型的江淮流域极端气候的模拟与预估

利用江淮流域29个代表站点1961--2000年逐日最高温度、最低温度和逐日降水资料,以及NCEP逐日大尺度环流场资料,引入基于多元线性回归与随机天气发生器相结合的统计降尺度模型SDSM（statistical downscalingmodel）,通过对每个站点建模,确立SDSM参数,并将该模型应用于SRESA2排放情景下HadCM3和cGcM3模式,得到了江淮流域各代表台站21世纪的逐日最高、最低温度和降水序列以及热浪、霜冻、强降水等极端气候指数。结果表明,当前气候下,统计降尺度方法模拟的极端温度指数与观测值有很好的一致性,能有效纠正耦合模式的“冷偏差”,如SDSM对江淮平均的冬季最高、最低温度的模拟偏差较CGCM3模式分别减少3℃和4．5℃。对于极端降水则能显著纠正耦合模式模拟的降水强度偏低的问题,如CGCM3对江淮流域夏季降水强度的模拟偏差为-60．6％,但降尺度后SDSM—CGCM3的偏差仅为-6％,说明降尺度模型SDSM的确有“增加值”的作用。21世纪末期在未来SRESA2情景下,对于极端温度,无论Had．CM3还是CGCM3模式驱动统计模型,江淮流域所有代表台站,各个季节的最高、最低温度都显著增加,且以夏季最为显著,增幅在2—4℃;与之相应霜冻天数将大幅减少,热浪天数大幅增多,各站点冬季霜冻天数减少幅度为5—25d,夏季热浪天数增加幅度为4～14d;对于极端降水指数,在两个不同耦合模式HadCM3和CGCM3驱动下的变化尤其是变化幅度的一致性比温度差,但大部分站点各个季节极端强降水事件将增多,强度增强,SDSM—HadCM3和SDSM-CGCM3预估的夏季极端降水贡献率将分别增加26％和27％。     

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.     

天气和气候极端事件的变化及其与全球变暖的联系——纪念2002年世界气象日“减低对天气和气候极端事件的脆弱性”

2002年3月23日世界气象日的主题是“减低天气和气候极端事件的脆弱性”。针对这个主题,作者对以下四方面问题作了阐述：（1）天气与气候极端事件以及脆弱性的定义;（2）近百年来全球天气与气候极端事件的变化及其与全球气候变化的关系;（3）未来天气与气候极端事件及其影响的预测;（4）天气与气候极端事件的适应与减缓对策。由于篇幅有限,未介绍中国在这方面的研究。     

Trends and periodicity of daily temperature and precipitation extremes during 1960–2013 in Hunan Province,central south China

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960–2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960–1986 and 1987–2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970–1980 and after 1992.     

试论我国气象灾害防御的应急管理

文章从气象灾害入手,以气象灾害应急管理为核心,着重探讨了气象灾害防御应急管理的重要性,并结合我国应急管理体制的特点和运行机制提出了加强应急管理工作、提升应急管理水平的方法和措施。     

Extreme precipitation events identified using detrended fluctuation analysis (DFA) in Anhui,China

Extreme weather events include unusual, severe or unseasonal weather, and weather at the extremes of the historical distribution. They have become more frequent and intense under global warming, especially in mid-latitude areas. They bring about great agricultural and economic losses. It is important to define the threshold of extreme weather event because it is the starting point of extreme weather event research, though it has been of seldom concern. Taking extreme precipitation events in Anhui, China as an example, the detrended fluctuation analysis (DFA) method is introduced to define the threshold of extreme weather events. Based on it, the spatial and temporal distributions of extreme precipitation events are analyzed. Compared to the traditional percentile method, DFA is based on the long-term correlation of time series. Thresholds calculated by DFA are much higher than the 99th percentile and the values are higher in the south and lower in the north. This spatial pattern is similar to the annual precipitation spatial pattern. There is an obvious increasing trend in the number of days with extreme precipitation, especially after the 1980s. This observation supports the point that more extreme events happen under global warming.     

Assessment of indices of temperature extremes simulated by multiple CMIP5 models over China

Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity (absolute indices and threshold indices), duration (duration indices), and frequency (percentile indices) of extreme temperature. The overall performance of each model is summarized by a "portrait" diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.     

Changes in weather and climate extremes: phenomenology and empirical approaches

The terms “weather extremes” and “climate extremes” are widely used in meteorology, often in relation to climate change. This paper reviews the empirical investigations into parallel changes in extreme events and climate change published in recent years and looks at their relevance for the global energy system. Empirical investigation into the correlation of extremes with global warming covers five groups: changes in temperature, precipitation, wind (storm) extremes, tropical and extra-tropical circulation phenomena. For temperature extremes, extensive analyses demonstrate that extreme hot days and nights will likely become more frequent, and extreme cold days and nights less frequent. Intense precipitation events will likely become more frequent in most continental regions. Scientific confidence in the trends of the frequency, duration, and intensity of tropical cyclones, is still low. A poleward shift is observed for extratropical cyclones, whereas no convincing tendencies of many smaller-scale phenomena, for example, tornados, or hail, can yet be detected. All these extremes have serious implications for the energy sector.     

极端天气和气候事件的变化

自1950年以来的观测证据表明,有些极端天气和气候事件已经发生了变化。全球尺度上,人为影响可能已经导致极端日最低和最高温度升高;由于平均海平面上升,人类活动可能已对沿海极端高水位事件的增加产生了影响;具有中等信度的是,人为影响已导致全球强降水增加;由于热带气旋历史记录的不确定性、缺乏对热带气旋与气候变化之间关联的物理机制的完整认识及热带气旋自然变率的程度,将可检测到的热带气旋活动变化归因于人为影响仅具有低信度。将单一的极端事件变化归因于人为气候变化具有挑战性。对极端事件变化预估的信度取决于事件的类型、区域和季节、观测资料的数量和质量、基本物理过程的认知水平及模式对其模拟的可靠性。     

A Review of Climate Change Attribution Studies

This paper reviews recent progress in climate change attribution studies. The focus is on the attribution of observed long-term changes in surface temperature, precipitation, circulation, and extremes, as well as that of specific extreme weather and climate events. Based on new methods and better models and observations, the latest studies further verify the conclusions on climate change attribution in the IPCC AR5, and enrich the evidence for anthropogenic influences on weather and climate variables and extremes. The uncertainty of global temperature change attributable to anthropogenic forcings lies in the considerable uncertainty of estimated total radiative forcing due to aerosols, while the uncertainty of precipitation change attribution arises from the limitations of observation and model simulations along with influences from large internal variability. In terms of extreme weather and climate events, it is clear that attribution studies have provided important new insights into the changes in the intensity or frequency of some of these events caused by anthropogenic climate change. The framing of the research question, the methods selected, and the model and statistical methods used all have influences on the results and conclusions drawn in an event attribution study. Overall, attribution studies in China remain inadequate because of limited research focus and the complexity of the monsoon climate in East Asia. Attribution research in China has focused mainly on changes or events related to temperature, such as the attribution of changes in mean and extreme temperature and individual heat wave events. Some progress has also been made regarding the pattern of changes in precipitation and individual extreme rainfall events in China. Nonetheless, gaps remain with respect to the attribution of changes in extreme precipitation, circulation, and drought, as well as to the event attribution such as those related to drought and tropical cyclones. It can be expected that, with the continual development of climate models, ongoing improvements to data, and the introduction of new methods in the future, climate change attribution research will develop accordingly. Additionally, further improvement in climate change attribution will facilitate the development of operational attribution systems for extreme events, as well as attribution studies of climate change impacts.     

近40年我国极端温度变化趋势和季节特征

利用1961—2000年我国194个测站逐日最高温度和最低温度器测资料,结合具有实际意义的季节极端温度指数,分析了我国近40年极端温度事件的年变化趋势和季节特征。对年极端气候指数的研究表明:绝对阈值定义的冷暖指数由于无法考虑南北气候差异,其结果不理想。百分比阈值所得的冷暖指数中,冷日指数和暖日指数具有不对称性,冷夜指数和暖夜指数具有较强的对称性。对季节极端温度指数研究表明:冬季极端冷指数变化趋势最为明显,夏季极端暖指数的变化趋势次之,春、秋两季极端冷指数的变化趋势不明显;年和季节尺度的极端冷暖指数均反映出增暖趋势。     

副热带极端事件查询与环流检索一体化平台及其应用

基于实时基本气象要素、大气环流客观分析场及历史相关资料,结合副热带地区重要天气气候事件指标和异常相似型的客观划定,设计了具有查询和检索2个模块的副热带极端事件查询与环流检索一体化平台。平台基于ASP.NET技术,使用C#语言开发而成,实现了重要天气气候事件及异常查询、气象要素监测绘图、近期环流检索和自定义环流检索等功能。平台通过采用Browser/Server系统结构,进一步提高了查询的便捷性。文中给出了业务应用的实例,检验了系统的实用性,实践表明该平台可以作为副热带地区长—中—短一体化预报业务的重要支撑。     

Climate change and extreme weather events: can developing countries adapt?

Developing countries are vulnerable to extremes of normal climatic variability, and climate change is likely to increase the frequency and magnitude of some extreme weather events and disasters. Adaptation to climate change is dependent on current adaptive capacity and the development models that are being pursued by developing countries. Various frameworks are available for vulnerability and adaptation (V&A) assessments, and they have both advantages and limitations. Investments in developing countries are more focused on recovery from a disaster than on the creation of adaptive capacity. Extreme climatic events create a spiral of debt burden on developing countries. Increased capacity to manage extreme weather events can reduce the magnitude of economic, social and human damage and eventually, investments, in terms of borrowing money from the lending agencies. Vulnerability to extreme weather events, disaster management and adaptation must be part of long-term sustainable development planning in developing countries. Lending agencies and donors need to reform their investment policies in developing countries to focus more on capacity building instead of just investing in recovery operations and infrastructure development.     

极端天气气候事件监测与预测研究进展及其应用综述

极端天气气候事件(简称"极端事件")分为单站极端事件和区域性极端事件。本文回顾了极端事件的研究进展,首先回顾了单站极端温度、极端降水和干旱事件的观测研究及相关指数,进而对近年来不断增多的区域性极端事件研究做了简要回顾,最后还回顾了极端事件气候预测研究进展。同时,对国内外在极端事件气候监测和预测业务现状进行了初步总结,并指出:在极端事件气候监测方面中国的业务产品较丰富,并率先开展了针对区域性极端事件的监测业务,但在产品表现形式上缺乏统一组织,特别是英文产品表现力严重不足;在极端事件气候预测方面,国家气候中心发展了两种方法:一个是基于物理统计的BP-CCA和OSR的干旱预测方法,另一个基于国家气候中心月动力延伸预报模式(DERF)的高温预测方法。最后,对极端事件监测和预测业务发展及相关科学问题给出展望,指出应根据极端事件的业务需求继续加强相关研究和业务能力建设。     

Long-term Observations for Monitoring Extremes in the Americas

In this paper we discuss data available from Argentina, Mexico, the United States and Canada that are suitable for the analysis of extreme temperature and precipitation events. We also discuss some of the problems of homogeneity and quality control that can potentially affect the observation of extreme values. It is clear that even in countries like the United States and Canada that have a potentially rich source of climate data there are still problems in obtaining homogeneous data necessary to perform thorough studies of time varying changes in extreme events. These types of problems may be compounded if data are needed from countries that do not have a tradition of maintaining large climate archives or observing networks.We also provide two examples of analyses that can be performed with these types of data: (1) the development of climate extremes indices for Canada, and (2) analyses of freezing events for Florida and the effect on the citrus industry. The Canadian example provides a good basis for countries to take indices developed for one country or region and through minor modifications make the index relevant to their own needs. The analysis of freezing events in Florida is a timely example of how extreme events have both ecological and societal impact.     

Climate change and extreme weather events: can developing countries adapt?

Abstract

Developing countries are vulnerable to extremes of normal climatic variability, and climate change is likely to increase the frequency and magnitude of some extreme weather events and disasters. Adaptation to climate change is dependent on current adaptive capacity and the development models that are being pursued by developing countries. Various frameworks are available for vulnerability and adaptation (V&A) assessments, and they have both advantages and limitations. Investments in developing countries are more focused on recovery from a disaster than on the creation of adaptive capacity. Extreme climatic events create a spiral of debt burden on developing countries. Increased capacity to manage extreme weather events can reduce the magnitude of economic, social and human damage and eventually, investments, in terms of borrowing money from the lending agencies. Vulnerability to extreme weather events, disaster management and adaptation must be part of long-term sustainable development planning in developing countries. Lending agencies and donors need to reform their investment policies in developing countries to focus more on capacity building instead of just investing in recovery operations and infrastructure development.