Learning about the Tail of the Probability Density Function for Equilibrium Climate Sensitivity

人类引起的气候变化的重要性主要取决于平衡气候敏感性（以下称为气候敏感性，即，工业化前大气中二氧化碳浓度加倍导致的全球表面空气温度的变化）。政府间气候变化专门委员会（IPCC）历史上评估了1.5至4.5摄氏度范围内的气候敏感性。 PI记录表明，气候敏感性极有可能超出这一范围，概率密度函数（PDF）具有较厚的上尾。最近的IPCC报告提出了一些敏感性的PDF，所有这些都有一个厚的上尾。本研究的重点是厚上尾。测试真实的气候系统是否位于这一厚厚的上尾，不仅是一个诱人的科学难题，而且还可以提供巨大的经济价值，因为它可以为改进气候政策的设计提供信息。最近的一项经济分析表明，当前气候敏感性估计的厚上尾可以主导拟议的气候变化战略在其效益/成本比方面的排名。这背后的直觉是，决策者可能会相当重视不同气候变化战略的代价高昂的结果，这些战略与当前气候敏感性估计的厚上尾被揭示为系统真实状态的情况有关。PI将使用他们的简单气候模型和更新的观测数据来测试五个假设：（1）自1998年以来增加的近地面气温观测将降低气候敏感性的90%置信区间;（2）考虑非硫酸盐气溶胶辐射强迫将增加气候敏感性的90%置信区间，这是因为由此产生的负辐射强迫将大于单独的硫酸盐气溶胶：（3）包括海洋热含量数据将降低气候敏感性的90%置信区间;（4）这三个数据集的综合效应将是气候敏感性的90%置信区间的减小;（5）由于气候噪声引起的气候敏感性的不确定性可以通过随着时间的推移了解气候敏感性来减小。此外，PI将研究气候变率和古气候信息如何影响气候敏感性的pdf估计。他们将使用的贝叶斯平均方法将使他们能够了解不同的辐射强迫模型，并将其相关的后报能力纳入气候敏感性分布的估计中。该研究的智力价值在于，它将使用额外的观测结果从频率和贝叶斯的角度改进对气候敏感性的估计：更新的地表气温，海洋热含量，古气候数据和非硫酸盐气溶胶的辐射强迫。这些知识将使决策者了解为“.”所需减少人为温室气体排放的幅度和速度。防止对气候系统的危险的人为干扰”，这是《联合国气候变化框架公约》第2条的要求。这也是该研究最重要的广泛影响。第二个更广泛的影响将是其他科学家利用研究结果来研究人类引起的气候变化的影响和政策含义。第三个更广泛的影响将是公共宣传和沟通。PI将通过向公众，商界领袖和政策制定者发表演讲来继续这一点。

The importance of human-induced climate change depends critically on the equilibrium climate sensitivity (referred to as climate sensitivity hereafter, i.e., the change in global surface air temperature resulting from a doubling of the pre industrial atmospheric carbon dioxide concentration). The Intergovernmental Panel on Climate Change (IPCC) historically assessed the climate sensitivity at a range from 1.5 to 4.5 degrees Celsius. The PIs document that there is a significant likelihood that the climate sensitivity lies outside this range, with probability density functions (pdfs) that have a thick upper tail. The most recent IPCC report presents a number of pdfs for the sensitivity, all of which have a thick upper tail. This research focuses on the thick upper tail. Testing whether or not the real climate system is located in this thick upper tail is not just a tantalizing scientific puzzle, but can also provide large economic value, as it can inform the design of improved climate policies. A recent economic analysis shows that the thick upper tail of current climate sensitivity estimates can dominate the ranking of proposed climate-change strategies in terms of their benefit/cost ratio. The intuition behind this is that a decision maker may give considerable weight to the very costly outcomes of different climate change strategies that are associated with the cases where the thick upper tail of current climate sensitivity estimates is revealed to be the true state of the system.The PIs will use their simple climate model and updated observational data to test five hypotheses: (1) The inclusion of the additional near-surface air temperature observations since 1998 will reduce the 90% confidence interval of climate sensitivity; (2) The inclusion of non-sulfate aerosol radiative forcing will increase the 90% confidence interval of climate sensitivity, this because the resulting negative radiative forcing will be greater than that for sulfate aerosol alone; (3) The inclusion of oceanic heat-content data will reduce the 90% confidence interval of climate sensitivity; (4) The combined effect of these three datasets will be a reduction of the 90% confidence interval of climate sensitivity; (5) The uncertainty in climate sensitivity due to climatic noise can be reduced by learning about climate sensitivity overtime. In addition, the PIs will examine how climate variability and paleoclimatic information influence the estimation of the pdf of climate sensitivity. The Bayesian averaging method that they will use will allow them to learn about different radiative forcing models and incorporate their associated hindcast abilities into the estimation of the distribution of climate sensitivity. The intellectual merit of the research is that it will produce improved estimates of climate sensitivity from both the Frequency and Bayesian points of view using additional observations: updated surface air temperatures, ocean heat content, paleoclimatic data, and radiative forcing from non-sulfate aerosols. This knowledge will inform decision-makers about the magnitude and rate of reductions in the anthropogenic emission of greenhouse gases that are needed to "...prevent dangerous anthropogenic interference with the climate system", as required by Article 2 of the UN Framework Convention on Climate Change. This is also the most important broader impact of the research. The second broader impact will be the use of the results by other scientists to study the impacts and policy implications of human-induced climatic change. The third broader impact will be public outreach and communication. The PI will continue this via his lectures to the public, business leaders and policymakers.