On the relationship between climate sensitivity and modelling uncertainty
On the relationship between climate sensitivity and modelling uncertainty
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DOI：
10.1080/16000870.2017.1327765
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发表时间：
2017-01
期刊：
影响因子：
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通讯作者：
C. Mauritzen;T. Živković;Vidyunmala Veldore
中科院分区：
文献类型：
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作者：
C. Mauritzen;T. Živković;Vidyunmala Veldore
气候模式预估用于研究气候变化对未来天气、农业、水资源、人类健康和全球经济等方面的潜在影响。然而，气候预测具有广泛的相关不确定性，在影响研究和风险评估中考虑到这些不确定性是一项挑战。了解哪些不确定性是重要的，哪些可以通过科学研究或政治决策来减少，可以帮助决策者做出明智的决策，帮助科学家集中资源，帮助企业建立对无法避免的不确定性的抵御能力。在全球范围内，目前的政治阻力或从协议转向重大行动的能力为气候预测提供了最大的不确定性，其次是与气候模型本身相关的不确定性。在这里，我们表明，气候敏感性是全球大部分地区模式不确定性的一个非常重要的来源，不仅对于温度，而且对于降水和风力预测也是如此。由于“气候敏感性”是一个集合术语，涵盖了气候系统中广泛的反馈机制，我们可能在很长一段时间内都无法知道气候敏感性高还是低的模式与21世纪的预测更相关。然而，对气候影响的调查不能等待。在这里，我们认为，将气候敏感性高低的气候模型混合在一起在物理上和统计上都是不合理的，任何影响研究所选择的子集都应该取决于人们试图回答的问题。
Abstract Climate model projections are used to investigate the potential impacts of climate change on future weather, agriculture, water resources, human health, the global economy, etc. However, climate projections have a broad range of associated uncertainties, and it is a challenge to take account of these uncertainties in impact studies and risk assessments. Knowing which uncertainties matter and which may be reduced via scientific research or political decisions can help policy-makers in making informed decisions, scientists in focusing their resources, and businesses in building resilience to uncertainties that cannot be avoided. On the global scale, the present political resistance or ability to move from agreements to significant action provides the largest uncertainty in climate projections, followed by the uncertainty associated with climate modelling itself. Here, we show that climate sensitivity is a very important source of model uncertainty over large parts of the globe not only for temperature, but also for precipitation and wind projections. Because ‘climate sensitivity’ is a collective term that encompasses a wide range of feedback mechanisms in the climate system, we may not know for a long time whether models with high or low climate sensitivities are more relevant for the twenty-first century projections. Nevertheless, investigations of climate impacts cannot wait. Here we argue that it is physically and statistically unsound to mix climate model with high and low climate sensitivities, and that the subset chosen for any impact study should depend on the question one is trying to answer.