Content area
Determining modern climate sensitivity, i.e., the global surface warming from doubling preindustrial concentrations of CO2, is an urgent task as it controls how much the planet will warm from greenhouse-gas emissions. The upper bound on estimates of climate sensitivity has been highly uncertain for decades, but paleoclimates now provide a strong constraint. In this dissertation, we combine proxy data from paleoclimate data assimilation with atmospheric general circulation models to show that the climate sensitivity inferred from paleoclimates is systematically higher than the climate sensitivity that applies to modern warming from CO2. This difference in climate sensitivity arises because (a) ice sheets, topography, and vegetation changes drive atmospheric stationary waves that alter the spatial patterns of sea-surface temperature (SST) over distant oceans during both the cold Last Glacial Maximum and the warm Pliocene; and (b) these paleoclimate SST patterns are associated with amplifying cloud feedbacks that make past climates more sensitive than the modern climate. Accounting for these differences between climates leads to a substantial reduction (→1.0→C) in the upper bound on modern climate sensitivity compared to recent community assessments, such as IPCC AR6 (Forster et al., 2021).
The leading role of spatial patterns of temperature change in determining climate sensitivity also compels a re-evaluation of the historical climate record (c. 1850–present). Previous studies have identified major discrepancies in radiative feedbacks due to differences in the patterns of sea-surface temperature across instrumental datasets. These discrepancies result from statistical infilling of the expansive gaps between sparse SST observations over the global oceans. In this dissertation, we use coupled data assimilation, which optimally combines observational and dynamical constraints from all climate fields simultaneously, to reconstruct monthly and globally resolved SST, near-surface air temperature, sea ice, and sea-level pressure over 1850–2023. The reconstruction provides a novel and internally consistent perspective on coupled climate variability and recent trends, which informs investigation of radiative feedbacks in the historical record.
Chapter 1 introduces the research topics addressed in this dissertation. Chapter 2 quantifies Last Glacial Maximum pattern effects and their impacts on modern climate sensitivity. Chapter 3 quantifies Pliocene pattern effects and provides stronger constraints on both modern climate sensitivity and 21st-century warming. Chapter 4 presents a reconstruction of the historical climate record (1850–2023) using linear inverse models and coupled data assimilation. Chapter 5 reviews the conclusions of the dissertation.