Mistreatment of the economic impacts of extreme events in the Stern Review Report on the Economics of Climate Change

The Stern Review on the Economics of Climate Change has focused debate on the costs and benefits of alternative courses of action on climate change. This refocusing has helped to move debate away from science of the climate system and on to issues of policy. However, a careful examination of the Stern Review's treatment of the economics of extreme events in developed countries, such as floods and tropical cyclones, shows that the report is selective in its presentation of relevant impact studies and repeats a common error in impacts studies by confusing sensitivity analyses with projections of future impacts. The Stern Review's treatment of extreme events is misleading because it overestimates the future costs of extreme weather events in developed countries by an order of magnitude. Because the Stern Report extends these findings globally, the overestimate propagates through the report's estimate of future global losses. When extreme events are viewed more comprehensively the resulting perspective can be used to expand the scope of choice available to decision makers seeking to grapple with future disasters in the context of climate change. In particular, a more comprehensive analysis underscores the importance of adaptation in any comprehensive portfolio of responses to climate change.     

1961—2018年陕西极端气温时空变化特征

基于陕西1961—2018年94个气象台站逐日气温资料,选取世界气象组织(WMO)提出的10种极端气温指数,分陕北、关中和陕南三个气候区,采用线性趋势分析、Mann-Kendall突变分析和Morlet小波分析,分析了陕西极端气温事件的时空变化特征.结果表明:陕西各极端气温指数在近60 a发生了显著变化,热指数的增加趋...     

基于动态重现期的极端高温气候评估方法研究

利用全国754站逐日最高气温观测序列,在论证极端温度概率分布与非平稳性关系的基础上,构建和比较了多种非平稳广义极值模型,定义了极端高温的动态重现期和重现水平,提出了一种极端高温事件的新型评估思想和方法,并将其应用于极端气候变化研究。通过该方法可以更好地解释极端事件的真实极端性,有效地增强极端事件之间的可比性,从而保留更多历史极端气候事件的信息。动态重现期的变换运用可对当前极端事件发生的真实状态和趋势提出更准确评估。该方法的提出可有效澄清学术领域和公共舆论对于多年一遇极端事件的理解上长期混淆重现期的绝对值和概率性这一分歧和谬误。     

新、旧气候态差异及对中国地区气候和极端事件评估业务的影响

利用1961—2020年中国区域2089个地面观测站资料,分析了1991—2020年和1981—2010年新、旧气候态下,平均气温、最高气温、最低气温和降水量等变量的空间变化特征,探讨对气候距平值、极端事件等评估结果的影响。结果表明：新气候态下,全国三类气温年和季节平均均一致升高,年降水增加,空间上气温偏高（低）、降水偏多（少）的特征将弱（强）化;华北东部、华东中部和北部以及青海西南部的年平均风速和日照时数距平增加;极端高温年减少,低温年增多,其中平均气温和最低气温受到的影响较最高气温更大;夏季南北方两条雨带极端强降水年的发生概率降低,冬季东北中部和南部、华北、华东北部、西北东部极端弱降水年概率显著增加;全国超过一半的站点极端日高温、低温和强降水事件的历史频次发生改变;新气候态还减弱了极端日高温事件的增速,加快了极端日低温事件的降速。     

RCPs情景下汉江流域未来极端降水的模拟与预估

采用应用于跨行业影响模式比较计划(ISIMIP)的5个CMIP5全球气候模式模拟的历史和未来RCP排放情景下的逐日降水数据,在评估模式对汉江流域1961—2005年极端降水变化特征模拟能力的基础上,进一步计算了RCP2.6、RCP4.5和RCP8.5排放情景下汉江流域未来2016—2060年极端降水总量(R95p)、极端降水贡献率(PEP)、连续5 d最大降水(RX5d)和降水强度(SDII),结果表明:RCP4.5情景下的极端降水指数上升最明显,R95p和RX5d分别较基准期增加12.5%和8.2%,PEP增加3.2个百分点,SDII微弱上升。在不同排放情景下,PEP均有一定的增幅,以流域西北和东南部增幅较大;R95p在流域绝大部分区域表现出一定的增加,且流域东南部和北部是增幅高值区;RX5d在RCP2.6和RCP4.5情景下整体表现为增加的特征,但在RCP8.5情景下整体表现为减少的特征。对极端降水预估的不确定性中,SDII的不确定性最小,RX5d的不确定性最大;不确定性大值区主要位于流域东部、东南部和西北部部分区域。     

Attribution matters: Revisiting the link between extreme weather experience and climate change mitigation responses

The literature suggests that extreme weather experiences have potential to increase climate change engagement by influencing the way people perceive the proximity and implications of climate change. Yet, limited attention has been directed at investigating how individual differences in the subjective interpretation of extreme weather events as indications of climate change moderate the link between extreme weather experiences and climate change attitudes. This article contends that subjective attribution of extreme weather events to climate change is a necessary condition for extreme weather experiences to be translated into climate change mitigation responses, and that subjective attribution of extreme weather to climate change is influenced by the psychological and social contexts in which individuals appraise their experiences with extreme weather. Using survey data gathered in the aftermath of severe flooding across the UK in winter 2013/2014, personal experience of this flooding event is shown to only directly predict perceived threat from climate change, and indirectly predict climate change mitigation responses, among individuals who subjectively attributed the floods to climate change. Additionally, subjective attribution of the floods to climate change is significantly predicted by pre-existing climate change belief, political affiliation and perceived normative cues. Attempts to harness extreme weather experiences as a route to engaging the public must be attentive to the heterogeneity of opinion on the attributability of extreme weather events to climate change.     

中国极端温度的群发性研究

从极端事件再现时间的角度研究了中国极端高、低温事件再现时间序列的长程相关性、群发性以及二者的关系。发现极端温度事件再现时间序列具有长程相关性,表征长程相关性的标度指数分布存在着明显的区域性特征,并与大气环流有关,当中国大陆在盛夏或隆冬稳定的西风环流控制下,极端温度的长程相关性较好,标度指数较大。通过定义极端事件的群发指数,对极端高、低温进行研究,发现具有长程相关性再现时间序列的极端温度呈现群发现象,且极端温度再现时间序列的标度指数和群发指数二者在空间分布上有较好的对应,极端温度再现时间序列的长程相关性可能是导致极端温度群发性的原因。从年际变化的角度看,极端高温Ⅰ级群发区域的群发指数增长趋于平缓,而极端低温Ⅰ级群发区域的群发指数有下降趋势,这与近几十年来全球变暖一致。在年代际尺度上,群发指数分布的演变特征明显,极端高温Ⅰ级群发区域总体面积变化不大,而极端低温Ⅰ级群发区域面积明显减少。因此,极端低温事件群发性减弱很可能是年代际气候变暖的主要原因。     

山区孕灾环境下地震和极端天气气候对地质灾害的影响

开展多致灾因子耦合作用下的地质灾害研究对山区综合风险防范和可持续发展至关重要。在山区孕灾环境中,极端降水和地震是触发滑坡等地质灾害的主要因素。以往研究多在山地孕灾环境稳定的假设下,研究极端降水或强震单独导致的地质灾害过程,而对孕灾环境变化下的极端天气和地震致灾因子共同诱发地质灾害的关注不足。针对这一问题,梳理了国内外发生在山区的地震和极端降水共同导致滑坡等地质灾害的研究案例,系统总结了山区强震与极端降水引发滑坡等地质灾害的相互作用过程。现有研究已在地震和极端降水引发滑坡等地质灾害的问题上取得了以下认识：(1)山区地震可强烈改变孕灾环境,显著提升震后降水引发地质灾害的可能性,放大极端降水-滑坡灾害链;(2)地震对降水引发滑坡的影响随着震后时间的推移逐渐减弱,该现象可能受控于气候因素;(3)在全球气候变化背景下,极端天气气候事件增多,定量研究山区强震和极端天气气候二者“遭遇”下的地质灾害链将面临更多挑战。由于观测案例不足,针对山区地震与极端降水共同导致地质灾害的研究仍缺少定量分析,触发机理也需进一步明确。     

Characterising climate change discourse on social media during extreme weather events

When extreme weather events occur, people often turn to social media platforms to share information, opinions and experiences. One of the topics commonly discussed is the role climate change may or may not have played in influencing an event. Here, we examine Twitter posts that mentioned climate change in the context of three high-magnitude extreme weather events – Hurricane Irene, Hurricane Sandy and Snowstorm Jonas – in order to assess how the framing of the topic and the attention paid to it can vary between events. We also examine the role that contextual factors can play in shaping climate change coverage on the platform. We find that criticism of climate change denial dominated during Irene, while political and ideological struggle frames dominated during Sandy. Discourse during Jonas was, in contrast, more divided between posts about the scientific links between climate change and the events, and posts contesting climate science in general. The focus on political and ideological struggle frames during Sandy reflects the event’s occurrence at a time when the Occupy movement was active and the 2012 US Presidential Election was nearing. These factors, we suggest, could also contribute to climate change being a more prominent discussion point during Sandy than during Irene or Jonas. The Jonas frames, meanwhile, hint at lesser public understanding of how climate change may influence cold weather events when compared with tropical storms. Overall, our findings demonstrate how event characteristics and short-term socio-political context can play a critical role in determining the lenses through which climate change is viewed.     

环渤海地区城市化对夏季极端暖夜的影响

城市化对人类生活息息相关的一些指标(如夏季极端暖夜等)的影响研究尚少.取环渤海地区气象观测站的夏季(6-8月)逐日最低气温资料(1958-2009年),使用广义极值(GEV)分布拟合夏季极端暖夜气温分布,并对拟合函数的3个分布特征参数的年际变化进行分析,根据特征参数变化特征进行城市化对极端暖夜的影响程度的分离.研究结果表明,环渤海地区,在极端暖夜气温分布的3个参数的年际变化中,以位置参数的代表性最好.在城市快速发展时期,城市偏高气温出现的可能性大,但极端气温变化幅度也较大.城市化对环渤海不同类型城市夏季极端暖夜气温的贡献均为上升作用,增温速度最大约为0.3℃/(10a).     

基于ETCCDI指数2017年中国极端温度和降水特征分析

利用中国1961—2017年2419站均一化逐日气候数据,计算了气候变化检测和指数联合专家组定义的26个极端气候指数,分析2017年中国极端温度和降水特征。结果表明：2017年中国区域平均的所有极端高温指数均高于1961—1990年30年平均,所有极端低温指数均低于1961—1990年30年平均。中国区域平均的多个极端温度指数达到或者接近历史极值,其中年最小日最高气温(TXn)和年最小日最低气温(TNn)均达到历史最高值,冷夜(TN10p)、冷昼(TX10p)和持续冷日日数(CSDI)达到历史最低值。年最大日最高气温(TXx)、年最大日最低气温(TNx)、暖夜(TN90p)、霜冻(FD)、冰冻(ID)、热夜(TR)、生长期长度(GSL)排在1961年以来的第2或第3位,其余极端温度指数全部排在了1961年以来前10位。2017年中国区域平均的10个极端降水指数中,有7个指数值处于1961—2017年1个标准差范围内,指示2017年的极端降水接近正常年。     

无锡极端气温事件的气候分析

为了解气候增暖情况下,无锡地区极端最高和最低气温的气候特征,用阈值检测方法对无锡市1959-2007年的日最高气温、日最低气温进行了研究,分析了极端事件的发生规律,得出主要结论:(1)从年代际看,不论是日最高气温或日最低气温,2001-2007年偏高事件最多,偏低事件最少.(2)最低气温从1980s初开始稳定上升.(3)在3、5、7、12月比较容易出现异常的气温.月内异常气温出现次数多少主要与季节更替和天气系统的转换有关.(4)日最低气温不论冬春夏秋,都是明显升高.日最高气温冬、春、秋季呈升高趋势,而夏季震荡加大.即在夏季,日最高气温偏高的事件增多,日最高气温偏低的事件也增多.     

Experience is not enough: A dynamic explanation of the limited adaptation to extreme weather events in public organizations

This study advances theory articulating the micro-level processes behind public organization adaptation to extreme weather. It tackles a persistent puzzle about the limited adaptation to extreme weather among public organizations: why does adaptation remain deficit after public organizations have experienced repeated extreme weather and some catastrophic consequences? We develop a computational agent-based model that integrates extant theory and data from semi-structured interviews of U.S. public transit agency managers, and use the model to investigate how micro-level cognition and behavior interact with environmental constraints to facilitate or impede the diffusion of adaptation. We articulate in greater detail how experience with influential extreme weather events matters to adaptation, highlighting that such experience is insufficient for adaptation to occur. A key insight is that the potential benefits from both increased risk perception and additional financial resources stemming from disaster- or non-disaster-induced opportunities can be underutilized, absent effective coupling between heightened risk perception and availability of resources that creates windows for adaptation. Using this insight, we further identify managerial and policy interventions with maximum leverage to promote adaptation to extreme weather in public organizations. The experiments show that slowing risk perception decay and synchronizing opportunities with extreme weather occurrences can stimulate adaptation.     

Quantifying uncertainty in changes in extreme event frequency in response to doubled CO2 using a large ensemble of GCM simulations

We discuss equilibrium changes in daily extreme surface air temperature and precipitation events in response to doubled atmospheric CO₂, simulated in an ensemble of 53 versions of HadSM3, consisting of the HadAM3 atmospheric general circulation model (GCM) coupled to a mixed layer ocean. By virtue of its size and design, the ensemble, which samples uncertainty arising from the parameterisation of atmospheric physical processes and the effects of natural variability, provides a first opportunity to quantify the robustness of predictions of changes in extremes obtained from GCM simulations. Changes in extremes are quantified by calculating the frequency of exceedance of a fixed threshold in the 2 × CO₂ simulation relative to the 1 × CO₂ simulation. The ensemble-mean value of this relative frequency provides a best estimate of the expected change while the range of values across the ensemble provides a measure of the associated uncertainty. For example, when the extreme threshold is defined as the 99th percentile of the 1 × CO₂ distribution, the global-mean ensemble-mean relative frequency of extremely warm days is found to be 20 in January, and 28 in July, implying that events occurring on one day per hundred under present day conditions would typically occur on 20–30 days per hundred under 2 × CO₂ conditons. However the ensemble range in the relative frequency is of similar magnitude to the ensemble-mean value, indicating considerable uncertainty in the magnitude of the increase. The relative frequencies in response to doubled CO₂ become smaller as the threshold used to define the extreme event is reduced. For one variable (July maximum daily temperature) we investigate this simulated variation with threshold, showing that it can be quite well reproduced by assuming the response to doubling CO₂ to be characterised simply as a uniform shift of a Gaussian distribution. Nevertheless, doubling CO₂ does lead to changes in the shape of the daily distributions for both temperature and precipitation, but the effect of these changes on the relative frequency of extreme events is generally larger for precipitation. For example, around one-fifth of the globe exhibits ensemble-mean decreases in time-averaged precipitation accompanied by increases in the frequency of extremely wet days. The ensemble range of changes in precipitation extremes (relative to the ensemble mean of the changes) is typically larger than for temperature extremes, indicating greater uncertainty in the precipitation changes. In the global average, extremely wet days are predicted to become twice as common under 2 × CO₂ conditions. We also consider changes in extreme seasons, finding that simulated increases in the frequency of extremely warm or wet seasons under 2 × CO₂ are almost everywhere greater than the corresponding increase in daily extremes. The smaller increases in the frequency of daily extremes is explained by the influence of day-to-day weather variability which inflates the variance of daily distributions compared to their seasonal counterparts.     

极端天气气候事件变化对荒漠化、土地退化和粮食安全的影响

土地是人类赖以生存的重要资源,在受气候变化影响的同时其状况变化也在气候系统中起着关键作用。IPCC最新发布的气候变化与土地特别报告（SRCCL）系统反映了关于荒漠化、土地退化、可持续土地管理、粮食安全和陆地生态系统碳通量方面的最新科学认知,并探讨了如何进行更加可持续性的土地利用和管理以应对与土地相关的气候变化问题。文中从极端事件变化及其影响的角度,结合SRCCL与其他相关文献,予以分析和总结。结果表明,在全球变暖的背景下,极端天气气候事件的变化已经并将继续影响荒漠化和土地退化进程并对粮食安全造成冲击;而土地对气候系统的反馈作用,又会加剧气候变化并提高极端事件发生的概率和严重程度。面对气候变化尤其是极端事件给土地带来的巨大压力,必须坚持可持续的土地管理,通过减少包括土地和粮食系统在内的所有行业的排放,才有可能实现到21世纪末将全球平均升温控制在相对工业化前水平2℃以内的目标,以减轻气候变化对土地和粮食系统的负面影响。     

基于公众天气预报预测塑料大棚逐日极端气温

利用浙江省慈溪市的公众天气预报和草莓大棚内极端气温的观测数据,构建一个以室外日最高气温、最低气温、相对湿度、最大风级、白天和夜间天空状况作为输入变量,棚内日最高气温和日最低气温作为输出变量的BP神经网络预测模型。用以预测草莓大棚室内日最高气温和日最低气温。结果表明,该模型对大棚内日最高气温、日最低气温的训练值和实测值之间的均方根误差分别为4.0℃和1.3℃,绝对误差则分别为3.2℃和1.0℃;日最高气温和日最低气温的预测值和实测值之间的均方根误差分别为3.6℃和1.2℃,绝对误差为3.0℃和1.0℃。该模型数据获取方便,实用性强,模拟精度较高,可以较准确的预测未来温室内的极端气温,为温室管理和调控提供依据。     

Extremely high temperatures in France at the end of the century

Power plant construction requires anticipation to achieve a liable dimensioning on the long functioning time of the installation. In the present climate change context, dimensioning towards extremely high temperature for installations intended to run until the 2070s or later implies an evaluation of plausible extreme values at this time scale. This study is devoted to such an estimation for France, using both observation series and climate model simulation results. The climate model results are taken from the European PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects) project database of regional climate change scenarios for Europe. Comparison of high summer temperature distributions given by observations and climate models under current climate conditions, conducted using Generalized Extreme Value distribution, reveals that only a few models are able to correctly reproduce it. For these models, climate change under IPCC A2 and B2 scenarios leads to differences in the variability of high values, whose proportion has an important impact on future 100-year return levels. This study was first presented at the EGU General Assembly in Vienna, 2–7 April 2006.     

气候变化情景下泥石流危险性响应分析

通过中国1950—2010年降水日值0.5°×0.5°格点数据和CMIP5的6个气候模式数据,以2010年舟曲8·7特大山洪泥石流为例,估算此次灾害发生的降雨重现期,并估算未来同等重现期下的降雨量,基于HEC-HMS和FLO-2D模型模拟该降雨量下山洪泥石流堆积面积与泥沙冲出量,进而得到了气候变化背景下的泥石流危险性变化。结果表明：2010年舟曲8·7山洪泥石流灾害的降雨重现期为1500 a,未来相同重现期下降雨量为113.7 mm。设防水平不变条件下,舟曲县城泥石流堆积面积可达2010年灾害的173%,总泥沙量增加到148%,且泥石流堆积面积增加的区域主要位于2010年舟曲县城人口密集区。可见,灾后重建中舟曲县城一半以上居民的转移安置政策有利于弱化未来气候变化背景下泥石流危险性增加的不利影响,是一种有效的气候变化适应性举措。     

江苏省近45a极端气候的变化特征

利用江苏省35个测站1960—2004年45 a的逐日最高温度、最低温度、日降水量资料集,分析了近45 a江苏省极端高温、极端低温以及极端降水的基本变化特征。结果表明:(1)多年平均年极端高温的空间分布表现为西高东低,而极端低温则表现为自北向南的显著增加,极端降水的发生频次自南向北逐渐减少;(2)极端高温在江苏中部以及南部大部分地区有上升趋势,而西北地区则有弱的下降趋势;全省极端低温表现为显著的升高趋势;极端降水频次在南部地区有增加的趋势,北部减少趋势,中部则无变化趋势。(3)江苏极端高温、低温和极端降水的年际和年代际变化具有区域性差异,其中极端降水频次变化的区域性差异最为明显。