Variability in the Rate and Pattern of Global Warming: Forced and Unforced Components

观测到的全球气温上升在时间上和空间上都有所不同，在变暖加剧或减弱的时期（如1998年至2013年之间所谓的“全球变暖中断”），在变暖高于或低于全球平均水平的地区。这项工作的目标是了解导致全球变暖速度和模式变化的不同过程。确定温室气体、人为气溶胶以及大气和海洋内部变率对观测到的温度变化的相对重要性，对于限制21世纪气候对进一步温室气体排放的响应至关重要。这项研究有助于弥合我们对全球气候变化的科学认识与了解它在特定地点和特定时间如何表现的实际需要之间的差距。在本项目下开发和测试的统计方法将为监测气候变率和变化提供宝贵的新资源，相关代码将公开共享。该项目涉及博士后研究员的支持和指导，从而有助于培养下一代气候科学家。该项目的成果将通过出版物、会议发言、新闻稿和向公众宣传等方式广泛传播。本项目旨在通过对气候模式输出和观测结果的统计分析，确定与气候变率和外部强迫（如温室气体或人为气溶胶）的特定机制相关的地表温度异常（或指纹）的空间格局。这些方法在将强迫气候响应与自然气候变率分离方面的技巧将在气候模式模拟的大集合中得到检验，其中每个模拟都有对内部变率的独特实现。然后将应用这些方法，对观测到的人为对地表温度变化的影响作出新的最佳估计。这些指纹有助于理清和理解外部强迫和内部变率对气候的影响，从而可以跟踪与外部强迫相关的气候信号的演变。该项目的研究结果将有助于了解热带太平洋和南大洋温度变化的机制，以及海洋在调节全球气候对人为扰动的响应中的作用。在这项工作中确定的温度指纹将有助于了解海洋观测在哪些方面可以最大程度地改进基于模型的多年气候预测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The observed increase in global temperature has varied in time, with periods of enhanced or reduced warming (such as the so-called "global warming hiatus" between 1998 and 2013) and in space, with regions that warm more or less than the global mean. The goal of this work is to understand the different processes contributing to this variability in the rate and pattern of global warming. Determining the relative importance of greenhouse gasses, anthropogenic aerosols, and internal atmospheric and oceanic variability for observed temperature changes is critical to constrain the climate response to further greenhouse gas emissions over the 21st century. This research helps bridge the gap between our scientific understanding of global climate change and the practical need to understand how it manifests in a particular place and at a particular time. The statistical methods to be developed and tested under this project will provide a valuable new resource for monitoring climate variability and change, and the associated code will be shared publicly. This project involves the support and mentoring of a postdoctoral researcher, thus helping to train the next generation of climate scientists. The results of this project will be disseminated widely through publications, conference presentations, press releases, and outreach to the public.This project aims to identify spatial patterns of surface temperature anomalies (or fingerprints) that are associated with particular mechanisms of climate variability and external forcings (e.g., due to greenhouse gasses or anthropogenic aerosols) by using statistical analysis of both climate model output and observations. The skill of these methods in separating forced climate responses from natural climate variability will be tested within large ensembles of climate model simulations where each simulation has a unique realization of internal variability. These methods will then be applied to give a new best estimate of the anthropogenic influence on surface temperature changes in observations. These fingerprints help disentangle and understand influences on climate from external forcings and internal variability such that the evolution of climate signals associated with external forcings can be tracked. The findings of this project will contribute new insights on the mechanisms of temperature variability in the tropical Pacific and Southern Ocean and on the role of the ocean in moderating the global climate response to anthropogenic perturbations. The temperature fingerprints identified in the work will help to understand where ocean observations can lead to the largest improvements in model-based multi-year forecasts of climate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.