Predictions of future climate change are based in part on changes seen in geological records of times with different climates. Such times include the Last Glacial Maximum (LGM) 21 thousand years ago (a colder time with lower atmospheric carbon dioxide levels) and the Pliocene Epoch 5.3 to 2.6 million years ago (a warmer time with higher carbon dioxide). These periods can be used to estimate the sensitivity of climate to changes in greenhouse gases such as carbon dioxide. Those sensitivity estimates help predict the amount of global warming we should expect to see in response to future greenhouse gas emissions. However, recent work has shown that the climate?s sensitivity to greenhouse gases depends not only on the average surface temperature change but also on the geographic pattern of that change. Thus, use of geological paleoclimate records to estimate future warming must account for how the spatial pattern of temperature changes in the past differs from that expected in the future. This project will combine information from paleoclimate data and climate models to evaluate the spatial pattern of surface temperature changes during the LGM and Pliocene. It will then develop methods to account for temperature pattern differences when using data from these past periods to help estimate future global warming.
Earth?s equilibrium climate sensitivity (ECS) is the change in average surface temperature associated with a doubling of the atmospheric carbon dioxide concentration (CO2) relative to the pre-industrial atmosphere. The ECS is set by the radiative feedbacks that link surface warming to changes in the amount of radiation leaving Earth?s atmosphere. Recent studies have shown that global radiative feedbacks depend on the spatial pattern of sea-surface temperature (SST). Estimates of ECS based on the proxy record of past climate changes ? such as those during the Last Glacial Maximum (LGM) and Pliocene ? have traditionally been based on global mean energy budget constraints and thus do not account for how SST patterns in those states may be different from those in the future. This research will use recently developed data assimilation techniques, combining information from climate models and proxies, to reconstruct gridded SST fields for the LGM and Pliocene that are dynamically consistent with available proxy data. These SST fields will then be compared against those projected by global climate models under CO2 forcing. The sensitivity of radiative feedbacks to differences between LGM / Pliocene and CO2-forced SST patterns will then be quantified using a suite of atmospheric general circulation models and Green?s functions that link warming patterns to radiative feedbacks. By producing estimates of LGM and Pliocene surface temperature patterns and quantifying the impact of temperature pattern differences on radiative feedbacks, this research will improve our understanding of ECS derived from those past climate states. This work will further facilitate researchers? participation in activities aimed at introducing high school students to climate science, through Current Climate Science workshops for high school teachers facilitated by the University of Washington?s Program on Climate Change and through George Mason University?s Aspiring Scientists Summer Internship Program.
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.
