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1.
<正>冰冻圈是指地球陆地和海洋表面以及表面以下水以固体形式存在的区域的总称,包括海冰、湖冰、河冰、积雪、冰川、冰盖以及冻土(图1)。作为地球气候系统五大圈层之一,冰冻圈以其自身独有特点越来越受到科学界重视。IPCC第五次评估报告(AR5)展现了近10年来冰冻圈变化的最新研究结果。1冰冻圈变化的主要观测事实AR5~([1])介绍的全球冰冻圈变化的总趋势和第四次评估报告(AR4)~([2])相一致,即冰冻圈各要素的冰量都处于持续损失状态。AR5决策者摘要中指出"过 相似文献
2.
在气候系统五大圈层中,冰冻圈对气候变化高度敏感,近几十年来气候变暖已引起全球冰川、冻土、积雪和海冰等冰冻圈要素加速退缩,进而对区域水资源、生态环境、社会经济发展和人类福祉产生了深远影响。2018年10月,IPCC在韩国仁川公布了《全球1.5℃增暖特别报告》（SR1.5）。报告较系统地呈现了关于全球1.5℃温升目标的基本科学认知,并探讨了可持续发展及消除贫困目标下加强全球响应的路径。在冰冻圈相关内容方面,报告呈现了有关全球1.5℃和2℃温升下冰冻圈（主要是海冰和多年冻土）变化及其对大气圈、水圈、生物圈、岩石圈和人类圈影响的一些亮点结论,还关注了全球1.5℃和2℃温升下冰冻圈相关的气候变化热点（区）和地球系统临界因素。报告指出,随着温度不断升高,冰冻圈及其相关要素和热点（区）面临的风险将不断增加,但将全球温升控制在1.5℃而不是2℃或更高时的风险将大大降低。 相似文献
3.
冰冻圈影响区恢复力研究和实践:进展与展望 总被引：1，自引：0，他引：1
气候变化引起全球冰冻圈各要素普遍退缩,进而深刻影响着区域生态安全和社会经济发展。恢复力(resilience)以降低脆弱性为目标,维持和培育社会-生态系统应对外界胁迫和干扰的能力,为应对冰冻圈变化引起的负面影响、实现区域可持续发展提供了重要的理论和实践框架。文中辨识了全球变暖背景下冰冻圈过程和功能变化对主要社会-生态系统的影响,综述了当前冰冻圈影响区恢复力相关的主要研究和实践进展,探讨了加强冰冻圈影响区社会-生态系统恢复力的路径。我们认为未来要进一步加强区域和全球冰冻圈变化及其影响综合评估,深入研究冰冻圈影响区社会-生态系统变化的驱动机制、级联效应和稳态转换;在实践上将减缓、适应和转型有机结合,建立管控区域社会-生态系统演化的综合监测、评估、预警和决策系统,从而促进系统朝着更具恢复力和可持续的路径发展。 相似文献
4.
2019年9月,IPCC正式发布《气候变化中的海洋和冰冻圈特别报告》（SROCC）,这是IPCC首次以高山地区与极区冰冻圈和海洋为主题的评估报告。报告全面评估气候变化背景下海洋和冰冻圈变化及其广泛影响与风险,其核心结论包括：气候系统变暖背景下高山地区和极区的冰冻圈普遍退缩,未来冰冻圈将继续消融,高山地区和极区将面临更高的灾害风险;20世纪70年代以来全球海洋持续增暖,未来海洋将继续变暖、加速酸化,影响海洋生物多样性并危及海洋生态系统服务功能和人类社会;近几十年全球平均海平面加速上升,未来数百年海平面仍将持续上升,极端海面事件频发将加剧沿海地区社会-生态系统的灾害风险。报告强调,采取及时、积极、协调和持久的适应与减缓行动,是有效应对海洋和冰冻圈变化,实现气候恢复力发展路径和可持续发展目标的关键所在。本研究认为,需要高度重视海洋和冰冻圈在气候系统变化中的长期和不可逆影响,强化应对气候变化紧迫性认识;高度重视我国冰冻圈和沿海地区面临的气候风险,强化适应能力建设;推动我国牵头的国际大科学计划,强化跨学科、跨领域协同创新,持续提升我国在相关领域的国际影响力和科技支撑能力。 相似文献
5.
全球山地冰冻圈变化、影响与适应 总被引：1，自引：0，他引：1
冰冻圈是高山地区不可或缺的重要组成部分,居住着全球约10%的人口。近几十年来,冰冻圈变化对山区和周围地区的自然和人类系统产生了广泛而深远的影响,对海洋也发挥着重要作用。IPCC最新发布的《气候变化中的海洋和冰冻圈特别报告》（SROCC）指出,过去几十年全球高山区气温显著升高,使山地冰冻圈发生了大范围显著退缩。观测到的山地（特别是低海拔山区）积雪期缩短、雪深和积雪覆盖范围减小;冰川物质持续亏损,其中全球最大的冰川负物质平衡出现在南安第斯山、高加索山和欧洲中部,亚洲高山区冰川负物质平衡最小;多年冻土温度升高、厚度减薄,地下冰储量减少;河、湖冰持续时间缩短。随着气候持续变暖,山地冰冻圈在21世纪仍将呈继续退缩状态。到21世纪末,低海拔山区积雪深度和积雪期将减少,冰川物质损失继续增加,多年冻土持续退化。冰冻圈变化已经或将改变山地灾害发生频率和强度,并对水资源、生态系统和经济社会系统产生重要影响。应对山地冰冻圈变化应从管理和优化利用冰冻圈资源、加强冰冻圈变化灾害风险的有效治理、增强国际合作及公约制定等适应策略着手开展,增强适应能力,从而有益于推动山地生态系统和经济社会系统可持续发展。 相似文献
6.
冰冻圈服务功能及其价值评估初探 总被引：2，自引：0，他引：2
冰冻圈通过气候调节作用为人类营造了适宜的地球人居环境,提供了大量的淡水资源、高山水电和天然气水合物等清洁能源、多样的冰冻圈旅游产品、独特的冰冻圈文化形态,以及特有生物种群栖息地等资源,因此,冰冻圈具有独特的经济社会服务功能。在气候变暖驱动和人类活动干预下,冰冻圈服务功能具有增强与衰弱等过程,也存在功能丧失的阈限,因而其服务价值是动态的,是可评估和计算的。通过明晰冰冻圈系统功能,辨识全球不同时空尺度冰冻圈服务功能,初步建立了冰冻圈系统服务功能价值评估体系,可以提高决策者和民众对冰冻圈及其服务功能的认知程度和保护意识。同时,对于全球不同冰冻圈及其重点影响区各级政府实施冰冻圈服务功能的可持续利用和环境保护宏观决策,以避免追求短期经济行为而带来的负面影响,具有深远的历史意义和重要的现实意义。 相似文献
7.
介绍了世界气候研究计划 (WCRP) /气候与冰冻圈 (CliC) 计划所代表的国际冰冻圈研究基本特点与未来趋势;分析了我国冰冻圈独特的区域特点, 阐明我国冰冻圈是维系干旱区绿洲经济发展和确保寒区生态系统稳定的重要水源保障, 其气候效应、环境效应、资源效应和生态效应正日趋显著并广泛地影响到西部生态与环境安全和水资源持续利用, 因而不仅具有科学上的重要性, 而且具有国家战略需求上的紧迫性。 提出未来我国冰冻圈研究应重点加强冰冻圈过程研究、记录研究、冰冻圈与气候模拟、冰冻圈与水资源以及冰冻圈变化的影响、适应与对策综合评估等5个方面的工作, 逐步完善并形成我国冰冻圈科学体系。 相似文献
8.
地球北极和南极部分地区正在经历着以变暖和冰冻圈退缩为主要特征的显著变化,不仅深刻影响着当地生态环境和社会经济,而且具有半球乃至全球效应。IPCC在2019年9月发布的《气候变化中的海洋和冰冻圈特别报告》（SROCC）第三章对极地系统变化及其影响与适应做了系统评估,主要呈现了IPCC第五次评估报告（AR5）之后极地冰冻圈、海洋、生态和社会系统相互作用的最新科学认知,探讨了降低脆弱性和风险、增强适应性和恢复力的路径。文中对SROCC第三章进行扼要解读,主要内容包括：(1)极地海洋、海冰、积雪/冻土/淡水冰、冰盖与冰川等极地系统要素过去和未来变化及其影响以及极地与中低纬度天气气候之间的关联;(2)人类响应极地系统变化的策略和不足以及应对未来变化的不确定性;(3)当前加强极地恢复力建设的主要行动及其实施进展。 相似文献
9.
基于乌鲁木齐河流域普通民众对气候变化及冰冻圈变化感知情况的问卷调查,结合有关监测研究结果,分析了普通民众对流域气候变化及冰冻圈变化的感知情况,探讨了环境变化对流域水资源和农业生产的可能影响.普通民众对气候变化和冰冻圈变化的感知基本与科学监测事实相符.对气候变化和冰冻圈变化条件下普通民众对水资源紧缺的适应措施的分析发现:... 相似文献
10.
IPCC第六次评估报告(AR6)于2021年8月在IPCC第一工作组第14次联合大会上得到审议通过,并得到了IPCC第54届全会接受和批准.文中主要对该报告第九章"海洋、冰冻圈和海平面"中与海洋环流的相关评估内容进行解读.与以前的IPCC报告相比,AR6进一步确认人类活动对海洋环流的影响,并基于最新的数值模式给出对未来... 相似文献
11.
为了提供有价值且可靠的概率(或者不确定性)预报,最新的全球集合预报系统已在美国国家环境预报中心日常业务运行,以满足社会需求。通过对各个关键要素的概率预报统计检验,可为广大用户提供这些概率预报的信心指数。但是预报(或集合预报)能力不仅取决于我们使用的预测要素,而且与时间和空间分辨率,极端事件或者高影响天气,以及预报时效有关。以大尺度天气系统预报为例,通常选择北半球500 hPa位势高度距平相关指数或概率指数表征模式的预报能力。如参照北半球500 hPa位势高度的距平相关指数(60%AC)或概率预报技巧指数(25%CRPSS),美国全球集合预报系统能够提供大约10 d的技巧预报。从全球集合预报系统输出的各预报要素,满足不同时空尺度需求的角度进行讨论,其可预报性(或预报极限)能够为模式研发人员、一线预报员和用户提供参考。尤其是对大气可预报性的深入研究,对于从科学与技术角度全面提升数值预报系统水平非常重要。当能够确定可预报性(或是预报误差)的真实来源时,科学家(包括模式研发人员)就能够有针对性地修改与完善。将传统的可预报性研究与改进的能够更客观地表述预报不确定性的集合预报相结合,所得可预报性将提供另一种有价值的参考。可预报性研究总体表明,全球集合预报系统对行星波、大尺度和天气尺度的系统(或者过程)可能分别具备约15、12、10 d的预报能力。对于热带天气过程的预报,如果进一步改善模式偏差和物理参数化过程,其MJO(Madden-Julian Oscillation)预报技巧可以延长至32.5 d。 相似文献
12.
Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness. 相似文献
13.
Climate Change Prediction 总被引：4，自引：0，他引：4
The concept of climate change prediction in response to anthropogenic forcings at multi-decadal time scales is reviewed. This
is identified as a predictability problem with characteristics of both first kind and second kind (due to the slow components
of the climate system). It is argued that, because of the non-linear and stochastic aspects of the climate system and of the
anthropogenic and natural forcings, climate change contains an intrinsic level of uncertainty. As a result, climate change
prediction needs to be approached in a probabilistic way. This requires a characterization and quantification of the uncertainties
associated with the sequence of steps involved in a climate change prediction. A review is presented of different approaches
recently proposed to produce probabilistic climate change predictions. The additional difficulties found when extending the
prediction from the global to the regional scale and the implications that these have on the choice of prediction strategy
are finally discussed. 相似文献
14.
The North Atlantic is one of the few places on the globe where the atmosphere is linked to the deep ocean through air–sea
interaction. While the internal variability of the atmosphere by itself is only predictable over a period of one to two weeks,
climate variations are potentially predictable for much longer periods of months or even years because of coupling with the
ocean. This work presents details from the first study to quantify the predictability for simulated multidecadal climate variability
over the North Atlantic. The model used for this purpose is the GFDL coupled ocean-atmosphere climate model used extensively
for studies of global warming and natural climate variability. This model contains fluctuations of the North Atlantic and
high-latitude oceanic circulation with variability concentrated in the 40–60 year range. Oceanic predictability is quantified
through analysis of the time-dependent behavior of large-scale empirical orthogonal function (EOF) patterns for the meridional
stream function, dynamic topography, 170 m temperature, surface temperature and surface salinity. The results indicate that
predictability in the North Atlantic depends on three main physical mechanisms. The first involves the oceanic deep convection
in the subpolar region which acts to integrate atmospheric fluctuations, thus providing for a red noise oceanic response as
elaborated by Hasselmann. The second involves the large-scale dynamics of the thermohaline circulation, which can cause the
oceanic variations to have an oscillatory character on the multidecadal time scale. The third involves nonlocal effects on
the North Atlantic arising from periodic anomalous fresh water transport advecting southward from the polar regions in the
East Greenland Current. When the multidecadal oscillatory variations of the thermohaline circulation are active, the first
and second EOF patterns for the North Atlantic dynamic topography have predictability time scales on the order of 10–20 y,
whereas EOF-1 of SST has predictability time scales of 5–7 y. When the thermohaline variability has weak multidecadal power,
the Hasselmann mechanism is dominant and the predictability is reduced by at least a factor of two. When the third mechanism
is in an extreme phase, the North Atlantic dynamic topography patterns realize a 10–20 year predictability time scale. Additional
analysis of SST in the Greenland Sea, in a region associated with the southward propagating fresh water anomalies, indicates
the potential for decadal scale predictability for this high latitude region as well. The model calculations also allow insight
into regional variations of predictability, which might be useful information for the design of a monitoring system for the
North Atlantic. Predictability appears to break down most rapidly in regions of active convection in the high-latitude regions
of the North Atlantic.
Received: 28 October 1996 / Accepted: 21 March 1997 相似文献
15.
气候系统中的水循环处于不断运转演化和更新中。近年来在全球变暖和人类活动的双重影响下,水文循环发生了显著变化,引起了社会和学界的广泛关注。水文循环是气候系统的核心,是连接气候子系统的纽带,也是水文气象学研究的核心问题。近年来国内外学者采用各种观测手段及海-陆-气耦合模型检测和模拟水文循环变化,取得了丰硕成果。对其变化的物理机制和驱动因素有了深入的理解,提高了对其未来可能变化的预测预估水平。文中对最近20余年与水文气象学相关的水文循环发生的变化,引起全球、区域及流域水文循环通量变化的原因,以及未来变化的预测等问题所取得的进展做了较全面的阐述。最后对水文气象学领域水文循环变化研究应关注的问题进行了探讨。 相似文献
16.
A Demonstration of the Uncertainty in Projections of UK Climate Change Resulting from Regional Model Formulation 总被引：1，自引：0，他引：1
David P. Rowell 《Climatic change》2006,79(3-4):243-257
Regional climate models (RCMs) are now commonly used to downscale climate change projections provided by global coupled models
to resolutions that can be utilised at national and finer scales. Although this extra tier of complexity adds significant
value, it inevitably contributes a further source of uncertainty, due to the regional modelling uncertainties involved. Here,
an initial attempt is made to estimate the uncertainty that arises from typical variations in RCM formulation, focussing on
changes in UK surface air temperature (SAT) and precipitation projected for the late twenty-first century. Data are provided
by a relatively large suite of RCM and global model integrations with widely varying formulations. It is found that uncertainty
in the formulation of the RCM has a relatively small, but non-negligible, impact on the range of possible outcomes of future
UK seasonal mean climate. This uncertainty is largest in the summer season. It is also similar in magnitude to that of large-scale
internal variations of the coupled climate system, and for SAT, it is less than the uncertainty due to the emissions scenario,
whereas for precipitation it is probably larger. The largest source of uncertainty, for both variables and in all seasons,
is the formulation of the global coupled model. The scale-dependency of uncertainty due to RCM formulation is also explored
by considering its impact on projections of the difference in climate change between the north and south of the UK. Finally,
the implications for the reliability of UK seasonal mean climate change projections are discussed. 相似文献
17.
Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing
a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate.
In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the
projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric
circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local
scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric
convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are
highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty,
while high resolution regional climate models (RCMs) are more suitable to quantify the third level.
Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather
narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first
disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part
which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of
global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate
the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in
the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results
for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined
statistical–dynamical downscaling approach, with the statistical relations based on regional model output. 相似文献
18.
Climate predictability on interannual to decadal time scales: the initial value problem 总被引：1，自引：1，他引：0
M. Collins 《Climate Dynamics》2002,19(8):671-692
Any initial value forecast of climate will be subject to errors originating from poorly known initial conditions, model imperfections, and by "chaos" in the sense that, even if the initial conditions were perfectly known, infinitesimal errors can amplify and spoil the forecast at some lead time. Here the latter source of error is examined using a "perfect model" approach whereby small perturbations are made to a coupled atmosphere-ocean general circulation model and the spread of nearby model trajectories, on time and space scales appropriate to seasonal-decadal climate variability, is measured to assess the lead time at which the error saturates. The study therefore represents an estimate of the upper limit of the predictability of climate (appropriate to the initial value problem) given a perfect model and near perfect knowledge of the initial conditions. It is found that, on average, surface air temperature anomalies are potentially predictable on seasonal to interannual time scales in the tropical regions and are potentially predictable on decadal time scales over the ocean in the North Atlantic. For mid-latitude surface air temperature anomalies over land, model trajectories rapidly diverge and there is little sign of any potential predictability on time scales greater than a season or so. For mean sea level pressure anomalies, there is potential predictability on seasonal time scales in the tropics, and for some global scale annual-decadal anomalies, although not those associated with the North Atlantic Oscillation. For precipitation, the only potential for predictability is for seasonal time anomalies associated with the El-Niño Southern Oscillation. For the majority of the highly populated regions of the world, climate predictability on interannual to decadal time scales based in the initial value approach is likely to be severely limited by chaotic error growth. It is found however that there can be cases in which the potential predictability can be higher than average indicating that there is perhaps some utility in making initial value forecasts of climate in those regions which show low predictability on average. 相似文献
19.
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least. 相似文献