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Paleoclimate reconstructions of the Early Eocene provide important data constraints on the climate and hydrologic cycle under extreme warm conditions. Available terrestrial water isotope records have been primarily interpreted to signal an enhanced hydrologic cycle in the Early Eocene associated with large-scale warming induced by high atmospheric CO2. However, orbital-scale variations in these isotope records have been difficult to quantify and largely overlooked, even though orbitally driven changes in solar irradiance can impact temperature and the hydrologic cycle. In this study, we fill this gap using water isotope-climate simulations to investigate the orbital sensitivity of Earth’s hydrologic cycle under different CO2 background states. We analyze the relative difference between climatic changes resulting from CO2 and orbital changes and find that the seasonal climate responses to orbital changes are larger than CO2-driven changes in several regions. Using terrestrial δ18O and δD records from the Paleocene-Eocene Thermal Maximum (PETM), we compare our modeled isotopic seasonal range to fossil evidence and find agreement between empirical and simulated isotopic compositions. Our conclusions consider systematic impacts on the proxy records, including the preservation state of the proxy, analytical uncertainty, and the relationship between δ18O or δD and environmental context, as well as illustrate the utility of fully coupled, isotope-enabled climate models when interpreting proxy records in times of extreme warmth.

The response of the terrestrial biosphere to warming remains one of the most poorly understood and quantified aspects of the climate system. One way to test the behavior of the Earth system in warm climate states is to examine the geological record. The abundance, distribution, and/or isotopic composition of source-specific organic molecules (biomarkers) have been used to reconstruct terrestrial paleoenvironmental change over a range of geological timescales. Here, we review new or recently improved biomarker approaches for reconstructing ( a) physical climate variables (land temperature, rainfall), ( b) ecosystem state variables (vegetation, fire regime), and ( c) biogeochemical variables (soil residence time, methane cycling). This review encompasses a range of key compound classes (e.g., lipids, lignin, and carbohydrates). In each section, we explore the concept behind key biomarker approaches and discuss their successesas paleoenvironmental indicators. We emphasize that analyzing several biomarkers in tandem can provide unique insights into the Earth system. ▪ Biomarkers can be used to reconstruct terrestrial environmental change over a range of geological timescales. ▪ A multi-proxy biomarker approach provides novel insights into climate and the environment.

Climate changes across the past 24,000 years provide key insights into Earth system responses to external forcing. Climate model simulations1,2 and proxy data3–8 have independently allowed for study of this crucial interval; however, they have at times yielded disparate conclusions. Here, we leverage both types of information using paleoclimate data assimilation9,10 to produce the first proxy-constrained, full-field reanalysis of surface temperature change spanning the Last Glacial Maximum to present at 200-year resolution. We demonstrate that temperature variability across the past 24 thousand years was linked to two primary climatic mechanisms: radiative forcing from ice sheets and greenhouse gases; and a superposition of changes in the ocean overturning circulation and seasonal insolation. In contrast with previous proxy-based reconstructions6,7 our results show that global mean temperature has slightly but steadily warmed, by ~0.5 °C, since the early Holocene (around 9 thousand years ago). When compared with recent temperature changes11, our reanalysis indicates that both the rate and magnitude of modern warming are unusual relative to the changes of the past 24 thousand years. Paleoclimate datasets are integrated with a climate model to reconstruct global surface temperature since the Last Glacial Maximum, showing sustained warming until the mid-Holocene.

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. This is a substantial obstacle for the application of this tool as soil calibrations underestimate temperature values when applied to lake sediments. Here, we present a comprehensive dataset ( N = 272 ) of lacustrine brGDGT distributions, consisting of both new and previously reported samples, spanning a wide range of geographical locations, air temperatures, and lakewater pH values. Empirical Orthogonal Function (EOF) analysis on the fractional abundance of brGDGTs indicates that temperature exerts a strong control (explaining 58 % of the variance) on brGDGT distribution. The influence of water chemistry is weaker, with pH and conductivity explaining 24 % of the variance. We use our dataset to generate a new Bayesian calibration to the mean temperature of Months Above Freezing (MAF), which has an R 2 = 0.82 and RMSE = 2.9 ° C. Application of the new temperature calibration to a previously published lake core record spanning the last 900 years demonstrates that it generates values comparable to instrumental observations of MAF. Our new calibration facilitates the use of lacustrine brGDGTs to reconstruct continental temperatures, a vital piece of information for understanding past climates.

The Holocene thermal maximum, a period of global warmth evident in early to mid-Holocene proxy reconstructions, is controversial. Most model simulations of the Holocene have not reproduced this warming, leading to a disagreement known as the Holocene Temperature Conundrum. Pollen records document the expansion of vegetation in the early and mid-Holocene African Sahara and Northern Hemisphere mid- and high latitudes, which has been overlooked in previous modeling studies. Here, we use time slice simulations of the Community Earth System Model to assess the impact of Northern Hemisphere vegetation change on Holocene annual mean temperatures. Our simulations indicate that expansion of Northern Hemisphere vegetation 9000 and 6000 years ago warms Earth’s surface by ~0.8° and 0.7°C, respectively, producing a better match with proxy-based reconstructions. Our results suggest that vegetation change is critical for modeling Holocene temperature evolution and highlight its role in driving a mid-Holocene temperature maximum.

To celebrate the first anniversary of Nature Reviews Earth & Environment, we asked six researchers investigating weather and climate to outline notable developments within their discipline and provide thoughts on important work yet to be done.

The vertical distribution of subseafloor archaeal communities is thought to be primarily controlled by in situ conditions in sediments such as the availability of electron acceptors and donors, although sharp community shifts have also been observed at lithological boundaries suggesting that at least a subset of vertically stratified Archaea form a long-term genetic record of coinciding environmental conditions that occurred at the time of sediment deposition. To substantiate this possibility, we performed a highly resolved 16S rRNA gene survey of vertically stratified archaeal communities paired with paleo-oceanographic proxies in a sedimentary record from the northern Red Sea spanning the last glacial-interglacial cycle (i.e., marine isotope stages 1-6; MIS1-6). Our results show a strong significant correlation between subseafloor archaeal communities and drastic paleodepositional changes associated with glacial low vs. interglacial high stands (ANOSIM; R = .73; p = .001) and only a moderately strong correlation with lithological changes. Bathyarchaeota, Lokiarchaeota, MBGA, and DHVEG-1 were the most abundant identified archaeal groups. Whether they represented ancient cell lines from the time of deposition or migrated to the specific sedimentary horizons after deposition remains speculative. However, we show that the majority of sedimentary archaeal tetraether membrane lipids were of allochthonous origin and not produced in situ. Slow post-burial growth under energy-limited conditions would explain why the downcore distribution of these dominant archaeal groups still indirectly reflect changes in the paleodepositional environment that prevailed during the analyzed marine isotope stages. In addition, archaea seeded from the overlying water column such as Thaumarchaeota and group II and III Euryarchaeota, which were likely not have been able to subsist after burial, were identified from a lower abundance of preserved sedimentary DNA signatures, and represented direct markers of paleoenvironmental changes in the Red Sea spanning the last six marine isotope stages.

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 ( per doubling CO2).

A range of future climate scenarios are projected for high atmospheric CO2 concentrations, given uncertainties over future human actions as well as potential environmental and climatic feedbacks. The geological record offers an opportunity to understand climate system response to a range of forcings and feedbacks which operate over multiple temporal and spatial scales. Here, we examine a single interglacial during the late Pliocene (KM5c, ca. 3.205±0.01 Ma) when atmospheric CO2 exceeded pre-industrial concentrations, but were similar to today and to the lowest emission scenarios for this century. As orbital forcing and continental configurations were almost identical to today, we are able to focus on equilibrium climate system response to modern and near-future CO2. Using proxy data from 32 sites, we demonstrate that global mean sea-surface temperatures were warmer than pre-industrial values, by ∼2.3 ∘C for the combined proxy data (foraminifera Mg∕Ca and alkenones), or by ∼3.2–3.4 ∘C (alkenones only). Compared to the pre-industrial period, reduced meridional gradients and enhanced warming in the North Atlantic are consistently reconstructed. There is broad agreement between data and models at the global scale, with regional differences reflecting ocean circulation and/or proxy signals. An uneven distribution of proxy data in time and space does, however, add uncertainty to our anomaly calculations. The reconstructed global mean sea-surface temperature anomaly for KM5c is warmer than all but three of the PlioMIP2 model outputs, and the reconstructed North Atlantic data tend to align with the warmest KM5c model values. Our results demonstrate that even under low-CO2 emission scenarios, surface ocean warming may be expected to exceed model projections and will be accentuated in the higher latitudes.

We present results from an ensemble of eight climate models, each of which has carried out simulations of the early Eocene climate optimum (EECO, ∼ 50 million years ago). These simulations have been carried out in the framework of the Deep-Time Model Intercomparison Project (DeepMIP; http://www.deepmip.org, last access: 10 January 2021); thus, all models have been configured with the same paleogeographic and vegetation boundary conditions. The results indicate that these non-CO2 boundary conditions contribute between 3 and 5 ∘C to Eocene warmth. Compared with results from previous studies, the DeepMIP simulations generally show a reduced spread of the global mean surface temperature response across the ensemble for a given atmospheric CO2 concentration as well as an increased climate sensitivity on average. An energy balance analysis of the model ensemble indicates that global mean warming in the Eocene compared with the preindustrial period mostly arises from decreases in emissivity due to the elevated CO2 concentration (and associated water vapour and long-wave cloud feedbacks), whereas the reduction in the Eocene in terms of the meridional temperature gradient is primarily due to emissivity and albedo changes owing to the non-CO2 boundary conditions (i.e. the removal of the Antarctic ice sheet and changes in vegetation). Three of the models (the Community Earth System Model, CESM; the Geophysical Fluid Dynamics Laboratory, GFDL, model; and the Norwegian Earth System Model, NorESM) show results that are consistent with the proxies in terms of the global mean temperature, meridional SST gradient, and CO2, without prescribing changes to model parameters. In addition, many of the models agree well with the first-order spatial patterns in the SST proxies. However, at a more regional scale, the models lack skill. In particular, the modelled anomalies are substantially lower than those indicated by the proxies in the southwest Pacific; here, modelled continental surface air temperature anomalies are more consistent with surface air temperature proxies, implying a possible inconsistency between marine and terrestrial temperatures in either the proxies or models in this region. Our aim is that the documentation of the large-scale features and model–data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability, and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols.

International audience; 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 Summary The 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.

The climatic drivers of tropical rainfall and atmospheric circulation in the late Pleistocene are still debated. Some studies suggest that tropical precipitation primarily responded to precession (23–19 ky cycle), whereas others propose that glacial-interglacial (100 ky) changes in ice sheets and sea level dominate. Here we re-examine orbital influences on tropical-to-subtropical precipitation isotopes using singular spectrum analysis to isolate leading oscillatory modes from proxy records across the Indo-Pacific Warm Pool (IPWP) and Asian monsoon domain. We find that the IPWP, Bay of Bengal, and South China Sea are dominated by the 100 ky glacial-interglacial mode of variability, whereas eastern China clearly follows precession, suggesting that precipitation isotopes over the mid-latitude Asian continent respond to different mechanisms than those in the IPWP or Indian and East Asian monsoon regions. This study demonstrates that glacial cycles, rather than changes in local insolation, are the dominant driver of Pleistocene IPWP hydroclimate. Plain Language Summary Reconstructions of past changes in rainfall, derived from cave deposits and ancient leaf waxes, provide an opportunity to understand how the tropical Indo-Pacific Warm Pool, located between southeast Asia and Australia, responds to large-scale changes in global climate. Here we statistically analyze five long records of rainfall and atmospheric circulation across the Warm Pool, the Indian and East Asian monsoon regions, and eastern China to isolate different external drivers of change between regions for the last 600,000 years. We find that the signal over eastern China is dominated by seasonal changes in solar radiation over mid-latitudes in the Northern Hemisphere, whereas the signal in the Warm Pool and monsoon regions are dominated by changes in sea level and high latitude ice sheet growth. This clear spatial difference in the external drivers of regional circulation changes suggests that the cave records from China do not exclusively reflect East Asian monsoon rainfall. Additionally, this study supports a strong connection between high and low latitude climates during the last several hundred thousand years.

Contains the input datasets and code used to generate the analysis and figures detailed in the paper (doi: 10.1175/JCLI-D-20-0661.1). Also includes the final reconstructions exported to NetCDF. Please see either of the README files for detailed descriptions of the contents of this repository. (We recommend README.html, which will render as a page when opened with a web browser. However, README.md provides the same information as a text-based document rendered in markdown.), Funding Sources: NOAA Grant NA18OAR4310420 NOAA Grant NA18OAR4310426 NOAA Grant NA18OAR4310422 NSF Grant AGS-1702423 NSF Grant AGS-1803946 NSF Grant AGS-1602301 Heising-Simons Foundation Grant 2016-05

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.

With CO2 concentrations similar to today (410 ppm), the Pliocene Epoch offers insights into climate changes under a moderately warmer world. Previous work suggested a low zonal sea surface temperature (SST) gradient in the tropical Pacific during the Pliocene, the so‐called “permanent El Nino.” Here, we recalculate SSTs using the alkenone proxy and find moderate reductions in both the zonal and meridional SST gradients during the mid‐Piacenzian warm period. These reductions are captured by coupled climate model simulations of the Pliocene, especially those that simulate weaker Walker circulation. We also produce a spatial reconstruction of mid‐Piacenzian warm period Pacific SSTs that closely resembles both Pliocene and future, low‐emissions simulations, a pattern that is, to a first order, diagnostic of weaker Walker circulation. Therefore, Pliocene warmth does not require drastic changes in the climate system—rather, it supports the expectation that the Walker circulation will weaken in the future under higher CO2.

UTIG Postdoctoral Fellowship; Brown Presidential Postdoctoral Fellowship; NSF National Science Foundation (NSF) [AGS-1204011, OCN-1304910]; David and Lucile Packard Foundation Fellowship in Science and Engineering; Bundesministerium fuer Bildung und Forschung [03G0184A-PABESIA, 03G0189A-SUMATRA, 03G0806B-CARIMA]

Heising-Simons Foundation [2016-015]; National Science FoundationNational Science Foundation (NSF) [AGS-1602156]

Reconstructions of past hydroclimate provide a means to understand precipitation responses to global ocean-atmosphere climate dynamics beyond the scope of that in the instrumental record. Late glacial climate was characterized by abrupt variability in ice and ocean dynamics, however the implications for hydroclimate are not as well known. Here we present organic geochemical proxy evidence for precipitation isotopes based on plant leaf wax hydrogen isotopic compositions (δDwax) and temperature proxy evidence based upon the branched glycerol dialkyl glycerol tetraethers (brGDGTs), that derive from the membrane lipids of bacteria, each extracted from a sedimentary archive in Lake Elsinore, California spanning 32–9 ka. We add proxy evidence for vegetation and salinity from additional biomarker analyses and compare to prior pollen and sedimentological evidence from the same core. Our record indicates a strong deglacial warming of 10 °C in Lake Elsinore (beginning at 14.5 ka) that accompanied a D-enrichment of precipitation of +90‰ and more C4 vegetation (12–10 ka), after a cold, wet and C3-dominated phase (20–14.5 ka), indicating winter-dominated precipitation during the Last Glacial Maximum and Heinrich Stadial 1. During the late glacial (32–20 ka) we find abrupt variability, with precipitation isotopic shifts (∼70‰) that are independent of temperature swings implicating changes in storm track, rather than local temperature as drivers of the precipitation isotope signal. Temperature is however not irrelevant for hydroclimate: we find extreme warmth at 29.4 ka and 26.8 ka, the latter coincident with existing reports of an extended dry period (27.5–25.5 ka), suggesting a long hot and dry interlude during the generally cooler glacial period. We compare δDwax with speleothem δ 18 O from Nevada, also within the winter-dominated precipitation region. Our results corroborate the Last Glacial Maximum and deglacial signals, and fill gaps revealing storm-track instability from 32–20 ka, however the pacing and magnitude of the biomarker signals merit cautious interpretation.

The Indo-Pacific Warm Pool is the largest source of heat and rainfall on Earth, but the mechanisms driving long-term climate variability in this region remain uncertain. Some studies suggest that precessional variations in insolation exert a primary role; alternatively, sea level change may be more important, with exposure of the Sunda and Sahul shelves leading to weakened Walker circulation across the Indian Ocean during glacial periods. The limited number of paleoclimate records from the warm pool that extend beyond the Last Glacial Maximum makes it difficult to test these competing hypotheses. Here, we present a 450,000-year long reconstruction of sea surface temperatures, sub-surface temperatures, and regional vegetation from southern Sumatra. We show that the dominant signal in each record is the 100 ky glacial cycle. We find that both surface and sub-surface temperatures cool during glacial periods, but the sub-surface cools more, reflecting a shoaling of the thermocline. Southern Sumatra and western Java consistently exhibit increased C4 grass coverage and an enhanced dry season during glacial periods. The observed changes in the thermocline and rainfall seasonality are consistent with the shelf exposure mechanism, suggesting that sea level changes exert a prominent role in warm pool climate over glacial-interglacial timescales.

Much of the inter-model spread in equilibrium climate sensitivity (ECS) estimates is attributed to cloud and convective parameterizations which model cloud and water vapor feedbacks. These parameterizations also directly influence water isotopes, which may be retrieved not only from modern observations, but also a plethora of paleoclimate archives that represent a much broader range of variability than is available in modern measurements. And thus, these water isotope tracers can be used to constrain ECS by flagging unrealistic parts of the parameterization phase space via model biases in a perturbed parameterization ensemble (PPE) of paleoclimate simulations. In this proof-of-concept study, we evaluate a suite of isotope-enabled atmosphere-only GISS-E2.1 simulations, each with varying cloud and convective perturbations, against speleothem and ice core δ18O for the Last Glacial Maximum (LGM, 21000 years ago), mid-Holocene (MH, 6000 years ago) and pre-Industrial periods. The first-order spatial pattern of δ18O of precipitation (δ18Op) is in excellent agreement between proxy data and all parameterizations across all time periods. While the simulations generally capture large scale δ18Op patterns, the magnitude of change is consistently smaller in all simulations than those of the proxies, highlighting uncertainties in both models and proxies. Not a single set of parameterizations worked well in all climate states, indicating that improving future simulations requires determining all plausible parameter combinations critical in refining ECS. Further, it may be that certain parameterization choices represent certain types of variability better than others, and there may be a non-unique solution to ideal clouds/convection parameterization choices that is modulated by the question asked.

Summary Glycerol Dialkyl Glycerol Tetraethers (GDGTs) are a group of molecules that have been successfully used for paleoclimate reconstructions in a wide range of environments. GDGTs have shown to be useful biomarkers as they are widely available, and their structure is relatively resistant to diagenetic alteration. Specific GDGTs are associated with particular environments, which suggests that they could potentially be used to classify ancient depositional conditions in cases where the exact paleoenvironment is not known. In this work we present a comprehensive branched and iGDGT dataset from published and novel analyses, with more than 1000 modern samples from marine, lake and river sediments as well as soils and peat samples. Unsupervised and supervised machine learning techniques were applied to this dataset to generate GDGT and environmentally based clusters and train a classification algorithm. The trained algorithm has the potential to be applied to samples formed in unclear or transitional depositional environments, allowing us to identify the potential environment in which they were formed. Furthermore, the classification model can help determine which environmental calibration is most appropriate for the setting, thereby improving paleoenvironmental reconstructions.

This study aims to evaluate whether machine learning techniques can be successfully applied to process the complex information contained within the molecular abundance distributions of plant wax n-alkane and n-alkanoic acid homologous series. We trained five vegetation identification models using plant wax chain length distributions from modern plants in the Mojave Desert (hyperarid) and the San Bernardino Mountains (conifer forest) and previously published data for macrophytes from Blood Pond (USA) and Mt Kenya (Kenya). All vegetation identification models proved accurate (mean classification accuracy = 0.81) at classifying the modern plant wax chain length distributions into desert plants, conifer and macrophyte categories. We then applied the models to fossil waxes extracted from a 76 m lacustrine sediment core drilled in Searles Valley, CA with an approximate age range of 10 to 150 kyrs (SLAPP-SRLS17) to reconstruct the proportion of desert plants, conifer woodland and lake vegetation. We compared our machine learning models with a previously published linear mixing model and validated our modelled plant type distributions by comparing the results with the archaeol caldarchaeol ecometric (ACE), a proxy for lake salinity, measured in the same core. We found a moderate positive correlation (r = 0.40) between the modelled desert plant proportion and high lake salinity in our models as well as a negative correlation (r = –0.45) between modelled macrophyte plants and ACE, validating the ability of the machine learning techniques to detect both xeric and macrophyte plant communities. Our results suggest that machine learning of plant wax molecular abundance distributions has potential to reconstruct past plant communities, given information from two compound classes and highly differentiated vegetation types.

The Indo‐Pacific Warm Pool (IPWP) is home to the warmest sea surface temperatures in the world oceans, favoring strong tropospheric convection and heavy rainfall. The mechanisms controlling long‐term change in the region’s hydroclimate are still uncertain. Here, we present a 450,000‐year record of precipitation δD from southern Sumatra that records a consistent pattern of glacial isotopic enrichment and interglacial depletion. We synthesize existing paleo‐indicators of precipitation δD and δ18O in the IPWP and compare results with water isotope‐enabled climate simulations of the Last Glacial Maximum (LGM). The simulations show glacial isotopic enrichment over the eastern Indian Ocean extending into the southern IPWP and isotopic depletion over southeast Asia, the west Pacific, and Australia. The pattern of simulated LGM isotopic change agrees generally well with our proxy synthesis. We conclude that reorganization of regional circulation under glacial conditions controls precipitation isotope variability in the IPWP: low‐level tropospheric convergence dominates the signal in the north/east, whereas divergence controls the response in the south/west. Additional sensitivity simulations suggest that the LGM ice sheets and the associated lowering in sea level, rather than decreased greenhouse gases, are responsible for the distinctive spatial pattern in glacial changes of precipitation isotopes and hydroclimate across the IPWP.

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 cut-off values slackened in data-sparse 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. Fil: Kaufman, Darrell. Northern Arizona University.; Estados Unidos Fil: McKay, Nicholas. Northern Arizona University.; Estados Unidos Fil: Routson, Cody. Northern Arizona University.; Estados Unidos Fil: Erb, Michael. Northern Arizona University.; Estados Unidos Fil: Davis, Basil. University Of Lausanne; Suiza Fil: Heiri, Oliver. University Of Basel; Suiza Fil: Jaccard, Samuel. University Of Bern; Suiza Fil: Tierney, Jessica. University of Arizona; Estados Unidos Fil: Dätwyler, Christoph. University Of Bern; Suiza Fil: Axford, Yarrow. Northwestern University; Estados Unidos Fil: Brussel, Thomas. University of Utah; Estados Unidos Fil: Cartapanis, Olivier. University Of Bern; Suiza Fil: Chase, Brian. Universite de Montpellier; Francia Fil: Dawson, Andria. Mount Royal University; Canadá Fil: de Vernal, Anne. Université du Québec a Montreal; Canadá Fil: Engels, Stefan. University of London; Reino Unido Fil: Jonkers, Lukas. University Of Bremen; Alemania Fil: Marsicek, Jeremiah. University of Wisconsin-Madison; Estados Unidos Fil: Moffa Sánchez, Paola. University of Durham; Reino Unido Fil: Morrill, Carrie. University of Colorado; Estados Unidos Fil: Orsi, Anais. Université Paris-Saclay; Francia Fil: Rehfeld, Kira. Heidelberg University; Alemania Fil: Saunders, Krystyna. Australian Nuclear Science And Technology Organisation; Australia Fil: Sommer, Philipp. University Of Lausanne; Suiza Fil: Thomas, Elizabeth. University At Buffalo; Estados Unidos Fil: Tonello, Marcela Sandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentina Fil: Tóth, Mónika. Balaton Limnological Institute; Hungría Fil: Vachula, Richard. Brown University; Estados Unidos Fil: Andreev, Andrei. Alfred Wegener Institut Helmholtz Centre for Polar and Marine Research; Alemania Fil: Bertrand, Sebastien. Ghent University; Bélgica Fil: Massaferro, Julieta. Administración de Parques Nacionales. Parque Nacional "Nahuel Huapi"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

The future in the past A major cause of uncertainties in climate projections is our imprecise knowledge of how much warming should occur as a result of a given increase in the amount of carbon dioxide in the atmosphere. Paleoclimate records have the potential to help us sharpen that understanding because they record such a wide variety of environmental conditions. Tierney et al. review the recent advances in data collection, statistics, and modeling that might help us better understand how rising levels of atmospheric carbon dioxide will affect future climate. Science , this issue p. eaay3701

The TEX86 paleothermometer is based upon the distribution of archaeal membrane lipids ('GDGTs') in marine sediments. GDGTs are ubiquitous, abundant and relatively resistant to degradation; as such, the TEX86 paleothermometer has been used to reconstruct sea surface temperature (SST) during the Cenozoic and early Mesozoic. We review the principles of the TEX86 proxy and developments made over the last two decades. We also discuss its application as a paleotemperature proxy and explore existing challenges and limitations.

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 cut-off values slackened in data-sparse 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., Measurement(s)climateTechnology Type(s)digital curationFactor Type(s)temporal interval • geographic location • proxy typeSample Characteristic - Environmentclimate systemSample Characteristic - LocationEarth (planet) Machine-accessible metadata file describing the reported data: https://www.ncdc.noaa.gov/paleo/study/27330

Author(s): Feakins, Sarah J; Liddy, Hannah M; Tauxe, Lisa; Galy, Valier; Feng, Xiaojuan; Tierney, Jessica E; Miao, Yunfa; Warny, Sophie

Greenhouse warming could activate a mode of climate variability in the Indian Ocean unprecedented in historical observations., Presently, the Indian Ocean (IO) resides in a climate state that prevents strong year-to-year climate variations. This may change under greenhouse warming, but the mechanisms remain uncertain, thus limiting our ability to predict future changes in climate extremes. Using climate model simulations, we uncover the emergence of a mode of climate variability capable of generating unprecedented sea surface temperature and rainfall fluctuations across the IO. This mode, which is inhibited under present-day conditions, becomes active in climate states with a shallow thermocline and vigorous upwelling, consistent with the predictions of continued greenhouse warming. These predictions are supported by modeling and proxy evidence of an active mode during glacial intervals that favored such a state. Because of its impact on hydrological variability, the emergence of such a mode would become a first-order source of climate-related risks for the densely populated IO rim.

The close temporal correlation between the emplacement of large igneous provinces and environmental crises in the geological record suggests a causal relationship. One such example is the emplacement of the North Atlantic Igneous Province (NAIP) and the Paleocene-Eocene Thermal Maximum (PETM), an extreme climate change event that occurred ~56 Ma. The main pulse of activity from the NAIP is around this time, but current radioisotopic ages are too low-resolution to constrain whether this activity was before, during and/or after the PETM. An ideal locality for understanding the initiation and development of the PETM is the island of Fur, northwest Denmark. The sedimentary sequence consists of clays and diatomites deposited in an epicontinental, shallow marine sea. The high sedimentation rates and close proximity to the NAIP means there are numerous volcanic and climatic proxies in the strata that can be used to provide high-resolution records constraining the relative and absolute timings of these events.Here we present the findings of the project ‘Ashlantic’, which focuses on pre- to post-PETM strata. We adopt a multiproxy approach using volcanic tracers, including tephra horizons, Hg anomalies, and Os isotopes, to infer the intensity and timing of NAIP activity. Volcanic glass morphology and chemistry suggests a hydromagmatic origin for key tephra intervals, while U-Pb dating of magmatic zircon constrains the timing of NAIP activity and the development of the PETM. Detailed chemostratigraphic logs and datasets (e.g. δ13C analyses) define the onset and duration of the PETM, while clay chemistry, Li isotopes, total organic carbon (TOC), and the paleothermometer TEX86 are used to assess the climate response to global warming during the PETM. In concert, our results suggest that the NAIP was active just before, during, and after the PETM, but the relationship between the NAIP and the marine and terrestrial environments is complex. These findings call for further work, such as ICDP and/or IODP drilling of North Sea sediments.

A range of future climate scenarios are projected for high atmospheric CO2 concentrations, given uncertainties over future human actions as well as potential environmental and climatic feedbacks. The geological record offers an opportunity to understand climate system response to a range of forcings and feedbacks which operate over multiple temporal and spatial scales. Here, 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 almost identical to today, we are able to focus on equilibrium climate system response to modern and near-future CO2. Using proxy data from 32 sites, we demonstrate that global mean sea-surface temperatures were warmer than pre-industrial, by ~2.3 ºC for the combined proxy data (foraminifera Mg/Ca and alkenones), or by ~3.2ºC (alkenones only). Compared to the pre-industrial, reduced meridional gradients and enhanced warming in the North Atlantic are consistently reconstructed. There is broad agreement between data and models at the global scale, with regional differences reflecting ocean circulation and/or proxy signals. An uneven distribution of proxy data in time and space does, however, add uncertainty to our anomaly calculations. The reconstructed global mean sea-surface temperature anomaly for KM5c is warmer than all but three of the PlioMIP2 model outputs, and the reconstructed North Atlantic data tend to align with the warmest KM5c model values. Our results demonstrate that even under low CO2 emission scenarios, surface ocean warming may be expected to exceed model projections, and will be accentuated in the higher latitudes.