Description: In this work we used controlled microcosms to study the effect of temperature and pH on brGDGTs in lake water. We collected surface water from Kennedy Lake, Tucson, AZ, a shallow eutrophic artificial reservoir previously described by Martínez-Sosa & Tierney (2019). From the collected samples we set up a series of microcosms, consisting of 1L glass flasks filled with lake water, and manipulated single environmental factors including temperature and pH. For our temperature incubations, we selected four conditions (9C, 18C, 27C and 35C) and incubated 3 1L flasks under each condition for two periods of time (4 or 6 weeks). For the pH incubations, we used commercially available freshwater aquarium non-phosphate buffers (Proprietary composition, Seachem, Madison, GA, USA) to manipulate the pH of the microcosms. For these experiments we targeted four pH conditions (4, 5, 6 and 7), and included two control samples: one where we added enough buffer to maintain the initial pH (Control + Buffer), and another to which we added no buffer (Control - Buffer). GDGTs were analyzed on an Agilent 1260 Infinity HPLC coupled to an Agilent 6120 single quadrupole mass spectrometer using two BEH HILIC silica columns (2.1 x 150 mm, 1.7 um; Waters) and the methodology of Hopmans et al. (2016). We calculated peak areas using the MATLAB package software ORIGAmI (Fleming et al. 2016) and estimated the concentration of brGDGTs by comparing the obtained peaks with a C46 internal standard (Huguet et al. 2006) normalized to the volume of each sample.

Description: The stable hydrogen isotopes of C30-Alkanoic acids were measured from marine sediment core MD98-2152, collected off the southern coast of Sumatra, likely reflecting rainfall over southern Sumatra and western Java. The record extends to ~450,000 years before present and includes the five most recent glacial periods. To purify the leaf wax fatty acids for analysis, organic material was extracted from the sediment using an Accelerated Solvent Extractor, leaf waxes were isolated from each total lipid extract using column chromatography then methylated with methanol of a known isotopic composition to form fatty acid methyl esters, and purified with a final column. Hydrogen isotopes were measured using a gas chromatography-isotope ratio-monitoring mass spectrometer against Vienna Standard Mean Ocean Water (VSMOW). The hydrogen isotopes of the leaf wax fatty acids were then used in tandem with previously measured carbon isotopes of the same samples to calculate the hydrogen isotope values of precipitation, accounting for vegetation changes, through time following the methods in Tierney et al. (2017). This data was collected with the purpose of examining rainfall variability in the southern Indo-Pacific Warm Pool during glacial climates and to improve the spatial coverage of precipitation isotope records in the region. The age model and leaf wax carbon isotopes for MD98-2152 are available in Windler et al. (2019).

Description: Despite widespread use of branched glycerol dialkyl glycerol tetraethers (brGDGTs) for paleo-temperature reconstruction, no global calibration for their application in lakes has been generated since improved analytical methods have allowed for the separation of the structural isomers [Hopmans et al., 2016]. This is a substantial obstacle for the application of this tool as soil calibrations underestimate temperature values when applied to lake sediments. In order to generate a global calibration, we present a comprehensive dataset (N = 272) of lacustrine brGDGT distributions, consisting of both new and previously reported samples [Boldt et al., 2015; Dang et al., 2018; 2016; Li et al., 2017; Stefanescu et al., 2021], spanning a wide range of geographical locations. In addition, we compiled environmental information from these locations through in situ measurements [Li et al., 2017] and literature search for pH, conductivity, and nutrient content. For parameters such as mean annual air temperature (MAAT), temperature of months above freezing (MAF), mean annual precipitation (MAP), we estimated values from either the CRU [Osborn and Jones, 2014] or PRISM [https://prism.oregonstate.edu/] products depending on the location. Our new calibration [Martínez-Sosa et al., 2021] facilitates the use of lacustrine brGDGTs to reconstruct continental temperatures, a vital piece of information for understanding past climates.

Description: A collection of geochemical SST proxy from the Last Glacial Maximum (23-19 ka) and the Late Holocene (4-0 ka) and results from data assimilation with iCESM 1.2. Includes raw proxy data from the LGM (Tierney2020_LGMProxyData.csv) and LH (Tierney2020_LHProxyData.csv) time slices, with calibrated absolute SSTs; "paired" (data in the same location) proxies with calibrated SST anomalies (Tierney2020_ProxyDataPaired.csv); a 5˚ x 5˚ gridded product of the paired proxies in netCDF format (Tierney2020_ProxyData_5x5_deltaSST.nc); and the results from the DA in netCDF format. The DA results are split into atmospheric variables (SAT, d18O of precipitation; Tierney2020_DA_atm.nc) and oceanic variables (SST, SSS, and d18O of seawater; Tierney2020_DA_ocn.nc). The ocean data are provided on their native tripolar grid (Tierney2020_DA_ocn.nc) as well as a 1 x 1 regridded version (Tierney2020_DA_ocn_regrid.nc).

Description: We examine a single interglacial during the late Pliocene (KM5c, ca. 3.205 +/- 0.01 Ma) when atmospheric CO2 concentrations were higher than pre-industrial, but similar to today and to the lowest emission scenarios for this century. As orbital forcing and continental configurations were also similar to today, we are able to focus on equilibrium climate system response to modern and near-future CO2. We have synthesised largely published datasets, scrutinised their age models, and generated mean absolute SSTs and their anomaly relative to the pre-industrial. Here we present those values for both alkenone and foraminifera-Mg/Ca proxies.

Description: Accurate estimates of past global mean surface temperature (GMST) help to contextualise future climate change and are required to estimate the sensitivity of the climate system to CO2 forcing through Earth's history. Previous GMST estimates for the latest Paleocene and early Eocene (∼57 to 48 million years ago) span a wide range (∼9 to 23 ∘C higher than pre-industrial) and prevent an accurate assessment of climate sensitivity during this extreme greenhouse climate interval. Using the most recent data compilations, we employ a multi-method experimental framework to calculate GMST during the three DeepMIP target intervals: (1) the latest Paleocene (∼57 Ma), (2) the Paleocene–Eocene Thermal Maximum (PETM; 56 Ma), and (3) the early Eocene Climatic Optimum (EECO; 53.3 to 49.1 Ma). Using six different methodologies, we find that the average GMST estimate (66 % confidence) during the latest Paleocene, PETM, and EECO was 26.3 ∘C (22.3 to 28.3 ∘C), 31.6 ∘C (27.2 to 34.5 ∘C), and 27.0 ∘C (23.2 to 29.7 ∘C), respectively. GMST estimates from the EECO are ∼10 to 16 ∘C warmer than pre-industrial, higher than the estimate given by the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (9 to 14 ∘C higher than pre-industrial). Leveraging the large “signal” associated with these extreme warm climates, we combine estimates of GMST and CO2 from the latest Paleocene, PETM, and EECO to calculate gross estimates of the average climate sensitivity between the early Paleogene and today. We demonstrate that “bulk” equilibrium climate sensitivity (ECS; 66 % confidence) during the latest Paleocene, PETM, and EECO is 4.5 ∘C (2.4 to 6.8 ∘C), 3.6 ∘C (2.3 to 4.7 ∘C), and 3.1 ∘C (1.8 to 4.4 ∘C) per doubling of CO2. These values are generally similar to those assessed by the IPCC (1.5 to 4.5 ∘C per doubling CO2) but appear incompatible with low ECS values (〈1.5 per doubling CO2).

Description: The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.