Observationally-constrained climate projections following the Paris Agreement

最近生效的《巴黎协定》承诺，各签署国将把全球平均气温升幅控制在远低于工业化前水平2摄氏度的水平，并努力将气温升幅控制在比工业化前水平高1.5摄氏度的范围内。由于二氧化碳是主要的温室气体，而且由于一定总量的二氧化碳排放产生相同的升温，无论是一次性排放还是长期排放，1.5摄氏度的升温阈值可以与特定的二氧化碳排放总量或碳预算相关联。了解二氧化碳的最大排放量，同时很有可能将全球平均气温控制在1.5摄氏度和2.0摄氏度的阈值以下，是规划气候缓解战略和履行《巴黎协定》承诺的关键。 联合国政府间气候变化专门委员会(IPCC)上一份报告中提出的碳预算直接基于所有可用气候模型中的模拟排放量，并指出，按照目前的排放水平，不到十年就会超过1.5摄氏度预算的最佳估计，有可能已经超过了这一预算。然而，我们知道，历史上的二氧化碳排放，加上其他气候驱动因素，迄今仅导致全球变暖约1摄氏度。此外，我们知道，平均而言，IPCC上一份报告中考虑的气候模型平均比观测数据更温暖。我们能否利用对过去气候变化的观察来获得对未来气候变化的更好预测？已经提出了许多利用观测来限制预测的方法，包括放大或缩小模拟的气候变化以与观测的变化最佳匹配，根据模型与观测的一致性对模型进行加权，或者使用观测来筛选气候模型的输入或输出。该项目将探索一系列从观测上限制气候预测的方法，重点是获得改进的观测限制碳预算和全球平均气温预测。还将考虑将观测约束应用于其他变量，如区域温度变化、降雨量变化和海冰变化。

The Paris Agreement, which recently came into force, commits signatories to holding the increase in global average temperature to well below 2C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5C above pre-industrial levels'. Since carbon dioxide is the dominant greenhouse gas, and since a certain total amount of carbon dioxide emissions gives the same amount of warming irrespective of whether it is emitted all at once or over a long period, a warming threshold of 1.5C can be associated with a particular total amount of carbon dioxide emissions, or carbon budget. Knowing the maximum amount of carbon dioxide which can be emitted while having a good chance of limiting global mean temperature to below the 1.5C and 2.0C thresholds is key to planning climate mitigation strategies and fulfilling the commitments made in the Paris Agreement. Carbon budgets presented in the last report of the United Nations Intergovernmental Panel on Climate Change (IPCC) were based directly on simulated emissions in all available climate models, and indicated that the best estimate of the 1.5C budget would be exceeded in less than ten years at current emissions levels, with a chance that this budget has already been exceeded. However, we know that historical carbon dioxide emissions, in conjunction with other climate drivers, have led to only about 1C global warming to date. Further, we know that on average the climate models considered in the last IPCC report on average warm more than observations. Can we use observations of past climate change to obtain better projections of future climate change? A number of ways of using observations to constrain projections have been proposed, including scaling simulated climate change up or down to best match observed changes, weighting models based on how well they agree with observations, or using observations to screen climate models in or out. This project will explore a range of approaches to observationally-constraining climate projections, with a focus on obtaining improved observationally-constrained carbon budgets and projections of global mean temperature. The application of observational constraints to other variables, such as regional temperature changes, rainfall changes and sea ice changes, will also be considered.