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

点击翻译按钮获取中文摘要

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.