A new climate feedback framework (REFRAME)

新的气候反馈框架（REFRAME）

• 批准号: EP/Y036123/1
• 负责人: Paulo Ceppi
• 金额: $ 161.76万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY036123%2F1
• 关键词: new; climate; feedback; framework; REFRAME

Substantial uncertainties remain in global climate change projections, and reducing these is an urgent requirement for policymaking. At the heart of these uncertainties are climate feedbacks - processes that can amplify or dampen global warming in response to an external climate forcing, e.g. due to greenhouse gases. A major challenge in assessing these feedbacks is their inconstancy: present-day feedbacks differ from those in the future, and while we can only observe the former, we need the latter to constrain future climate projections.I propose that the apparent inconstancy of climate feedbacks is due to missing physics in the current feedback framework, which assumes feedback processes to solely depend on global-mean surface temperature. Instead, recent work has shown that the feedbacks also respond to patterns of surface temperature, through changes in low cloud amount and hence solar reflection. REFRAME will thus introduce a new feedback framework that quantitatively accounts for this missing physics. It will then exploit this new framework to (1) quantify the coupling between climate variability and the feedbacks, which observations suggest is unrealistic in climate models; and (2) constrain future climate change, focusing on the risk of strongly amplifying feedbacks and high global warming levels.REFRAME will leverage my prior work elucidating the physical linkages between surface temperature pat- terns and the feedbacks, thus making optimal use of my expertise. The effort is timely and novel: I have recently demonstrated the power of statistical learning to constrain cloud feedback, creating new opportunities to constrain climate change from the short observational record which this project will exploit. By addressing a fundamental problem in the theory of climate dynamics, the project has the potential to reduce uncertainties in climate projections and carbon budgets on policy-relevant scales, thereby impacting climate policy over the next 10-20 years.

在全球气候变化预测方面仍然存在很大的不确定性，减少这些不确定性是决策的迫切要求。这些不确定性的核心是气候反馈-这一过程可以放大或抑制全球变暖，以应对外部气候强迫，例如温室气体。评估这些反馈的一个主要挑战是它们的不稳定性：现在的反馈不同于未来的反馈，虽然我们只能观察到前者，但我们需要后者来约束未来的气候projects.I建议，气候反馈的明显不稳定性是由于当前反馈框架中缺少物理学，该框架假设反馈过程仅取决于全球平均表面温度。相反，最近的研究表明，反馈也会对地表温度的模式做出反应，通过低云量的变化，从而改变太阳反射。REFRAME将引入一个新的反馈框架，定量地解释这个缺失的物理学。然后，它将利用这个新的框架（1）量化气候变率和反馈之间的耦合，观测表明这在气候模式中是不现实的;和（2）限制未来的气候变化，重点是强烈放大反馈和高全球变暖水平的风险。REFRAME将利用我以前的工作阐明表面温度模式和反馈之间的物理联系，从而充分利用我的专业知识这项工作是及时和新颖的：我最近证明了统计学习的力量，以约束云反馈，创造新的机会，以限制气候变化的短期观测记录，本项目将利用。通过解决气候动力学理论中的一个基本问题，该项目有可能减少气候预测和政策相关尺度上的碳预算的不确定性，从而影响未来10-20年的气候政策。