The Last Glacial Maximum (LGM), one of the best-studied paleoclimatic intervals, o↵ers a prime opportunity to investigate how the climate system responds to changes in greenhouse gases (GHGs) and the cryosphere. Previous work has sought to constrain the magnitude and pattern of glacial cooling from paleothermometers, but the uneven distribution of the proxies, as well as their uncertainties, has challenged the construction of a full-field view of the LGM climate state. Here, we combine a large collection of geochemical proxies for sea-surface temperature with an isotope-enabled climate model ensemble to produce a field reconstruction of LGM temperatures using data assimilation. The reconstruction is validated with withheld proxies as well as independent ice core and speleothem 18 O measurements. Our assimilated product provides a precise constraint on global mean LGM cooling of 5.9 C (6.3-5.6 C, 95% CI). Given assumptions concerning the radiative forcing of GHGs, ice sheets, and aerosols, this cooling translates to an equilibrium climate sensitivity (ECS) of 3.2 C (2.2-4.3 C, 95% CI), a value that is higher than previous estimates and but consistent with the traditional consensus range of 2-4.5 C.

et al. # a comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cutoff values slackened in datasparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. the multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format.

The Mg/Ca ratio of planktic foraminifera is a widely used proxy for sea-surface temperature but is also sensitive to other environmental factors. Previous work has relied on correcting Mg/Ca for nonthermal influences. Here, we develop a set of Bayesian models for Mg/Ca in four major planktic groups-Globigerinoides ruber (including both pink and white chromotypes), Trilobatus sacculifer, Globigerina bulloides, and Neogloboquadrina pachyderma (including N. incompta)-that account for the multivariate influences on this proxy in an integrated framework. We use a hierarchical model design that leverages information from both laboratory culture studies and globally distributed core top data, allowing us to include environmental sensitivities that are poorly constrained by core top observations alone. For applications over longer geological timescales, we develop a version of the model that incorporates changes in the Mg/Ca ratio of seawater. We test our models-collectively referred to as BAYMAG-on sediment trap data and on representative paleoclimate time series and demonstrate good agreement with observations and independent sea-surface temperature proxies. BAYMAG provides probabilistic estimates of past temperatures that can accommodate uncertainties in other environmental influences, enhancing our ability to interpret signals encoded in Mg/Ca. Plain Language SummaryThe amount of magnesium (Mg) incorporated into the calcite shells of tiny protists called foraminifera is determined by the temperature of the water in which they grew. This allows paleoclimatologists to measure the magnesium-to-calcium (Mg/Ca) ratio of fossil foraminiferal shells and determine how past sea-surface temperatures have changed. However, other factors can influence Mg/Ca, like the salinity and pH of seawater. Here, we develop Bayesian models of foraminiferal Mg/Ca that account for all of the influences on Mg/Ca and show how we can use these to improve our interpretations of Mg/Ca data. Culture experiments provide precise constraints on environmental sensitivities but are limited in that laboratory conditions are not perfect analogs for the natural environment. Sediment traps have an advantage in that seasonality of foraminiferal occurrence and corresponding ocean temperatures are well constrained, but they do not account for the effects of dissolution or bioturbation. Sedimentary core tops integrate effects associated with both occurrence and preservation and are thus better analogs for the conditions typical of the geological record, but uncertainties in seasonal preferences and the depth of calcification can in some cases lead to misleading inference of secondary environmental sensitivities (Hertzberg & Schmidt, 2013;Hönisch et al., 2013).Here, we use both core top and laboratory culture data to develop a suite of Bayesian hierarchical models for Mg/Ca. We collate over 1,000 sedimentary Mg/Ca measurements to formulate new calibrations for four major planktic groups: Globigerinoides ruber (including both pink and white chromotypes), Trilobat...

The Last Glacial Maximum (LGM), one of the best-studied paleoclimatic intervals, offers a prime opportunity to investigate how the climate system responds to changes in greenhouse gases (GHGs) and the cryosphere. Previous work has sought to constrain the magnitude and pattern of glacial cooling from paleothermometers, but the uneven distribution of the proxies, as well as their uncertainties, has challenged the construction of a full-field view of the LGM climate state. Here, we combine a large collection of geochemical proxies for sea-surface temperature with an isotope-enabled climate model ensemble to produce a field reconstruction of LGM temperatures using data assimilation. The reconstruction is validated with withheld proxies as well as independent ice core and speleothem d18O measurements. Our assimilated product provides a precise constraint on global mean LGM cooling of -5.9˚C (-6.3 – -5.6˚C, 95% CI). Given assumptions concerning the radiative forcing of GHGs, ice sheets, and aerosols, this cooling translates to an equilibrium climate sensitivity (ECS) of 3.2˚C (2.2 – 4.3˚C, 95% CI), a value that is higher than previous estimates and but consistent with the traditional consensus range of 2 – 4.5˚C.

The oxygen isotopic composition of planktic foraminiferal calcite ( δ18Oc) is one of the most prevalent proxies used in the paleoceanographic community. The relationship between δ18Oc, temperature, and seawater oxygen isotopic composition ( δ18Ow) is firmly rooted in thermodynamics, and experimental constraints are commonly used for sea surface temperature (SST) reconstructions. However, in marine sedimentary applications, additional sources of uncertainty emerge, and these uncertainty constraints have not as of yet been included in global calibration models. Here, we compile a global data set of over 2,600 marine sediment core top samples for five planktic species: Globigerinoides ruber, Trilobatus sacculifer, Globigerina bulloides, Neogloboquadrina incompta, and Neogloboquadrina pachyderma. We developed a suite of Bayesian regression models to calibrate the relationship between δ18Oc and SST. Spanning SSTs from 0.0 to 29.5 °C, our annual model with species pooled together has a mean standard error of approximately 0.54‰. Accounting for seasonality and species‐specific differences improves model validation, reducing the mean standard error to 0.47‰. Example applications spanning the Late Quaternary show good agreement with independent alkenone‐based estimates. Our pooled calibration model may also be used for reconstruction in the deeper geological past, using modern planktic foraminifera as an analog for non‐extant species. Our core top‐based models provide a robust assessment of uncertainty in the δ18Oc paleothermometer that can be used in statistical assessments of interproxy and model‐proxy comparisons. The suite of models is publicly available as the Open Source software library bayfox, for Python, R, and MATLAB/Octave.