The response of the Arctic regions to changing climate

北极地区对气候变化的反应

基本信息

  • 批准号:
    NE/H000437/1
  • 负责人:
  • 金额:
    $ 44.78万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2010
  • 资助国家:
    英国
  • 起止时间:
    2010 至 无数据
  • 项目状态:
    已结题

项目摘要

The anthropogenic burning of fossil fuels is affecting the climate system via raised atmospheric CO2 concentrations. But are there aspects of the natural Earth system that, when forced by imposed climate change, have themselves a major impact on the carbon cycle? Such climate-carbon (C) cycle feedbacks might be positive - that is, they may cause a reduction in the current capability of natural systems to mitigate anthropogenic CO2 emissions, or may even force natural systems to become direct sources of CO2. Such positive feedbacks are a major cause for concern, and their initiation could be regarded as a climate 'tipping point'. It has been hypothesised that the Arctic land surface could be one such 'tipping point', whereby global warming is sufficient to induce soil C losses greater than any extra draw-down of C through enhanced tundra (shrub) and boreal forest growth in a warmer, CO2-enriched environment. In addition, a warmer climate will impact on the on the energy and water cycles, with less snow cover in Northern Latitudes reducing surface reflectivity and so inducing additional warming. In reality the energy, water and C cycles are all strongly linked and need to be modelled interactively to provide robust estimates of the future. Global Circulation Models (GCMs) are designed to emulate the climate system and the global carbon cycle, and in the process, provide pointers to potential 'tipping points' in the climate system. But their predictions for the Arctic region will only be as good as the hydrology, ecology and energy interactions depicted in the land surface model for that region. This project therefore has two aims - to provide much more physical realism in land surface models, and then to see how this enhancement impacts on modelled future climate. Does the Arctic region eventually enhance human-induced climate change by increasing future levels of atmospheric carbon dioxide? Modelling the land surface for the Arctic region is complicated. To get this correct, we will need to capture how the vegetation may grow and expand in a warmer environment, and how this might change soil C stocks. We also need to model how the snow interacts with vegetation - snow cover will change with climate, and will influence the energy inputs, the water cycle, the frozen ground and the vegetation distribution. For example, deeper snow will occur in areas of tall vegetation and thus vegetation structure influences not only the timing of snow melt but also the thermal regime as deeper snow actually insulates the soils. There is thus a knock-on effect on soil respiration and vegetation growth. This project will model all of these features, dynamically, such that the impact of future temperature and snowfall patterns on the Arctic ecosystems can be assessed. Extensive use will be made of existing observational datasets developed by the PIs and others over the last decade and, in particular the International Polar Year. This new knowledge of the Arctic land surface will be introduced within a pan-Arctic gridded modelling system. The local and regional behaviours will be integrated to determine net land-atmosphere CO2 fluxes. However, major future changes in land surface behaviour might have strong feedbacks on other aspects of the climate system e.g. surface temperatures and soil moisture. Hence, the last component of this project is to make coupled land-atmosphere simulations, thereby capturing all feedbacks. We will achieve this through our existing and on-going collaboration with the Hadley Centre (a world leading centre for modelling the climate system, who make predictions with their family of GCMs). This link will allow a final assessment to be made of whether the Arctic land-surface could pass an unwelcome climate 'tipping point', and thus feedback on existing warming, either locally through enhancing warming further or through the global C cycle.
人为燃烧化石燃料正在通过提高大气中的二氧化碳浓度来影响气候系统。但是,当受到气候变化的影响时,自然地球系统的某些方面是否会对碳循环产生重大影响?这种气候-碳(C)循环反馈可能是积极的——也就是说,它们可能导致自然系统当前减缓人为二氧化碳排放的能力下降,甚至可能迫使自然系统成为二氧化碳的直接来源。这种积极的反馈是引起关注的主要原因,它们的开始可以被视为气候的“临界点”。据推测,北极陆地表面可能是这样一个“引爆点”,即全球变暖足以导致土壤C的损失,而不是在一个更温暖、富含二氧化碳的环境中,通过加强苔原(灌木)和北方森林的生长而导致的任何额外的C下降。此外,气候变暖将影响能量和水循环,北纬地区积雪减少会降低地表反射率,从而导致额外的变暖。实际上,能源、水和碳循环都紧密相连,需要建立互动模型,以提供对未来的可靠估计。全球环流模型(GCMs)旨在模拟气候系统和全球碳循环,并在此过程中为气候系统中潜在的“临界点”提供指针。但是他们对北极地区的预测只能与该地区陆地表面模型中描述的水文、生态和能源相互作用一样准确。因此,这个项目有两个目标——在陆地表面模型中提供更多的物理真实性,然后观察这种增强对模拟的未来气候的影响。北极地区是否会通过增加未来大气中二氧化碳的含量而最终加剧人为引起的气候变化?北极地区陆地表面的模拟是复杂的。为了得到正确的答案,我们需要捕捉到植被如何在温暖的环境中生长和扩张,以及这可能如何改变土壤C储量。我们还需要建立雪与植被相互作用的模型——积雪将随着气候变化而变化,并将影响能量输入、水循环、冻土和植被分布。例如,较深的雪将发生在高植被的地区,因此植被结构不仅影响融雪的时间,而且影响热状态,因为较深的雪实际上隔离了土壤。因此,这对土壤呼吸和植被生长产生了连锁反应。该项目将动态模拟所有这些特征,以便评估未来温度和降雪模式对北极生态系统的影响。将广泛利用国家气象局和其他机构在过去十年,特别是在国际极地年开发的现有观测数据集。这种关于北极陆地表面的新知识将在一个泛北极网格模拟系统中引入。将综合当地和区域的行为,以确定陆地-大气二氧化碳净通量。然而,未来陆地表面行为的重大变化可能会对气候系统的其他方面产生强烈的反馈,例如地表温度和土壤湿度。因此,该项目的最后一个组成部分是进行陆地-大气耦合模拟,从而获取所有反馈。我们将通过与哈德利中心(一个世界领先的气候系统建模中心,利用其gcm家族进行预测)现有的和正在进行的合作来实现这一目标。这一联系将有助于最终评估北极陆地表面是否会越过一个不受欢迎的气候“临界点”,从而对现有的变暖做出反馈,要么通过进一步增强局部变暖,要么通过全球C循环。

项目成果

期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Modelled sensitivity of the snow regime to topography, shrub fraction and shrub height
  • DOI:
    10.5194/hess-18-2375-2014
  • 发表时间:
    2014-01-01
  • 期刊:
  • 影响因子:
    6.3
  • 作者:
    Menard, C. B.;Essery, R.;Pomeroy, J.
  • 通讯作者:
    Pomeroy, J.
Processing arctic eddy-flux data using a simple carbon-exchange model embedded in the ensemble Kalman filter.
使用集成卡尔曼滤波器中嵌入的简单碳交换模型处理北极涡通量数据。
Turnover of recently assimilated carbon in arctic bryophytes.
北极苔藓植物中最近同化的碳的周转。
  • DOI:
    10.1007/s00442-011-1988-y
  • 发表时间:
    2011
  • 期刊:
  • 影响因子:
    2.7
  • 作者:
    Street LE
  • 通讯作者:
    Street LE
An assessment of the carbon balance of Arctic tundra: comparisons among observations, process models, and atmospheric inversions
  • DOI:
    10.5194/bg-9-3185-2012
  • 发表时间:
    2012-01-01
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    McGuire, A. D.;Christensen, T. R.;Yi, Y.
  • 通讯作者:
    Yi, Y.
Comparing microbial and chemical kinetics for modelling soil organic carbon decomposition using the DecoChem v1.0 and DecoBio v1.0 models
  • DOI:
    10.5194/gmd-7-1519-2014
  • 发表时间:
    2014-07
  • 期刊:
  • 影响因子:
    5.1
  • 作者:
    G. Xenakis;M. Williams
  • 通讯作者:
    G. Xenakis;M. Williams
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Richard Essery其他文献

Using just a canopy height model to obtain lidar-level accuracy in 3D forest canopy shortwave transmissivity estimates
仅使用冠层高度模型来获得 3D 森林冠层短波透射率估计的激光雷达级精度
  • DOI:
    10.1016/j.agrformet.2023.109429
  • 发表时间:
    2023-07-15
  • 期刊:
  • 影响因子:
    5.700
  • 作者:
    Clare Webster;Richard Essery;Giulia Mazzotti;Tobias Jonas
  • 通讯作者:
    Tobias Jonas

Richard Essery的其他文献

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{{ truncateString('Richard Essery', 18)}}的其他基金

The Big Thaw: gauging the past, present and future of our mountain water resources
大解冻:衡量山区水资源的过去、现在和未来
  • 批准号:
    NE/X005194/1
  • 财政年份:
    2022
  • 资助金额:
    $ 44.78万
  • 项目类别:
    Research Grant
Reducing Snow-Climate Uncertainty in Earth System modelling (ReSCUES)
减少地球系统建模中的雪气候不确定性 (ReSCUES)
  • 批准号:
    NE/P011926/1
  • 财政年份:
    2017
  • 资助金额:
    $ 44.78万
  • 项目类别:
    Research Grant
Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes
异质景观上的雪-植被-大气相互作用
  • 批准号:
    NE/H008187/1
  • 财政年份:
    2010
  • 资助金额:
    $ 44.78万
  • 项目类别:
    Research Grant

相似国自然基金

北半球Polar和Arctic环流变化对中高纬度气候异常的影响
  • 批准号:
    41775067
  • 批准年份:
    2017
  • 资助金额:
    68.0 万元
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    面上项目

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NNA Research: Development of a Nonlinear Reduced Order Modeling Framework for Marine Structures Operating in The Arctic and Sub-Arctic Regions
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