Stainforth David A, Downing Thomas E, Washington Richard, Lopez Ana, New Mark
Tyndall Centre for Climate Change Research, Environmental Change Institute, Centre for the Environment, University of Oxford, South Parks Road, Oxford, UK.
Philos Trans A Math Phys Eng Sci. 2007 Aug 15;365(1857):2163-77. doi: 10.1098/rsta.2007.2073.
There is a scientific consensus regarding the reality of anthropogenic climate change. This has led to substantial efforts to reduce atmospheric greenhouse gas emissions and thereby mitigate the impacts of climate change on a global scale. Despite these efforts, we are committed to substantial further changes over at least the next few decades. Societies will therefore have to adapt to changes in climate. Both adaptation and mitigation require action on scales ranging from local to global, but adaptation could directly benefit from climate predictions on regional scales while mitigation could be driven solely by awareness of the global problem; regional projections being principally of motivational value. We discuss how recent developments of large ensembles of climate model simulations can be interpreted to provide information on these scales and to inform societal decisions. Adaptation is most relevant as an influence on decisions which exist irrespective of climate change, but which have consequences on decadal time-scales. Even in such situations, climate change is often only a minor influence; perhaps helping to restrict the choice of 'no regrets' strategies. Nevertheless, if climate models are to provide inputs to societal decisions, it is important to interpret them appropriately. We take climate ensembles exploring model uncertainty as potentially providing a lower bound on the maximum range of uncertainty and thus a non-discountable climate change envelope. An analysis pathway is presented, describing how this information may provide an input to decisions, sometimes via a number of other analysis procedures and thus a cascade of uncertainty. An initial screening is seen as a valuable component of this process, potentially avoiding unnecessary effort while guiding decision makers through issues of confidence and robustness in climate modelling information. Our focus is the usage of decadal to centennial time-scale climate change simulations as inputs to decision making, but we acknowledge that robust adaptation to the variability of present day climate encourages the development of less vulnerable systems as well as building critical experience in how to respond to climatic uncertainty.
关于人为气候变化的现实存在科学共识。这促使人们做出了大量努力来减少大气中的温室气体排放,从而在全球范围内减轻气候变化的影响。尽管做出了这些努力,但至少在未来几十年里,我们仍将面临重大的进一步变化。因此,社会将不得不适应气候变化。适应和缓解都需要在从地方到全球的范围内采取行动,但适应可以直接受益于区域尺度的气候预测,而缓解可能仅仅由对全球问题的认识驱动;区域预测主要具有激励价值。我们讨论了如何解释气候模式模拟大型集合的最新发展,以提供这些尺度上的信息并为社会决策提供参考。适应作为一种影响,与那些无论气候变化如何都存在但在十年时间尺度上有后果的决策最为相关。即使在这种情况下,气候变化往往只是一个次要影响;也许有助于限制“无悔”策略的选择。然而,如果气候模式要为社会决策提供输入,正确解释它们很重要。我们将探索模式不确定性的气候集合视为可能提供不确定性最大范围的下限,从而提供一个不可忽视的气候变化范围。本文提出了一种分析途径,描述了这些信息如何有时通过一系列其他分析程序为决策提供输入,从而形成一连串的不确定性。初步筛选被视为这一过程的一个有价值的组成部分,它有可能避免不必要的努力,同时引导决策者应对气候建模信息中的可信度和稳健性问题。我们关注的是将十年到百年时间尺度的气候变化模拟用作决策的输入,但我们承认,对当今气候变率的稳健适应鼓励发展更具韧性的系统,并积累应对气候不确定性的关键经验。