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Understanding the transport mechanisms of terrestrial biomarkers to marine sediments is critical for interpreting past environmental and climate changes from these valuable archives. Here, we produce new estimates of two classes of terrestrial plant biomarkers, n-alkane waxes and pentacyclic triterpene methyl ethers (PTMEs), from a transect of marine core top sediments that span the full length of the West African margin. We determine the chain length distributions, mass accumulation rates, carbon isotope signatures (δ13C) of n-alkanes and the mass accumulation rates of PTMEs and assess the extent to which these proxy characteristics reflect vegetation and climate patterns within source areas on adjacent land. We achieve this via comparisons with a variety of satellite-based vegetation and climate data sets and with atmospheric back trajectory and river basin estimates. The mass accumulation rate of grass-produced PTMEs to core top marine sediments shows good spatial agreement with the presence of C4 grasses on land and appears to have shorter transport distances than n-alkanes. The mass accumulation rate of n-alkanes roughly corresponds to changes in the landscape net primary productivity. The δ13C signature of n-alkanes records changes in landscape C3 versus C4 vegetation balance while longer chain length n-alkane distributions indicate drier conditions and grassier vegetation. Apparent discrepancies between the zonal distribution of biomarkers in the marine sediments versus the observed vegetation patterns can mostly be explained by the influence of long-range atmospheric transport, with modest contributions from river inputs. 

Reconstructions of past climates in both time and space provide important insight into the range and rate of change within the climate system. However, producing a coherent global picture of past climates is difficult because indicators of past environmental changes (proxy data) are unevenly distributed and uncertain. In recent years, paleoclimate data assimilation (paleoDA), which statistically combines model simulations with proxy data, has become an increasingly popular reconstruction method. Here, we describe advances in paleoDA to date, with a focus on the offline ensemble Kalman filter and the insights into climate change that this method affords. PaleoDA has considerable strengths in that it can blend multiple types of information while also propagating uncertainty. Drawbacks of the methodology include an overreliance on the climate model and variance loss. We conclude with an outlook on possible expansions and improvements in paleoDA that can be made in the upcoming years. 

A long-term record of global mean surface temperature (GMST) provides critical insight into the dynamical limits of Earth’s climate and the complex feedbacks between temperature and the broader Earth system. Here, we present PhanDA, a reconstruction of GMST over the past 485 million years, generated by statistically integrating proxy data with climate model simulations. PhanDA exhibits a large range of GMST, spanning 11° to 36°C. Partitioning the reconstruction into climate states indicates that more time was spent in warmer rather than colder climates and reveals consistent latitudinal temperature gradients within each state. There is a strong correlation between atmospheric carbon dioxide (CO₂) concentrations and GMST, identifying CO₂as the dominant control on variations in Phanerozoic global climate and suggesting an apparent Earth system sensitivity of ~8°C. 

Abstract. 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 δ2H records from the Paleocene–Eocene Thermal Maximum (PETM), we compare our modeled isotopic seasonal range to fossil evidence and find approximate agreement between empirical and simulated isotopic compositions. The limitations surrounding the equilibrated snapshot simulations of this transient event and empirical data include timing and time interval discrepancies between model and data, the preservation state of the proxy, analytical uncertainty, the relationship between δ18O or δ2H and environmental context, and vegetation uncertainties within the simulations. In spite of the limitations, this study illustrates the utility of fully coupled, isotope-enabled climate models when comparing climatic changes and interpreting proxy records in times of extreme warmth. 

Here, we show that the Last Glacial Maximum (LGM) provides a stronger constraint on equilibrium climate sensitivity (ECS), the global warming from increasing greenhouse gases, after accounting for temperature patterns. Feedbacks governing ECS depend on spatial patterns of surface temperature (“pattern effects”); hence, using the LGM to constrain future warming requires quantifying how temperature patterns produce different feedbacks during LGM cooling versus modern-day warming. Combining data assimilation reconstructions with atmospheric models, we show that the climate is more sensitive to LGM forcing because ice sheets amplify extratropical cooling where feedbacks are destabilizing. Accounting for LGM pattern effects yields a median modern-day ECS of 2.4°C, 66% range 1.7° to 3.5°C (1.4° to 5.0°C, 5 to 95%), from LGM evidence alone. Combining the LGM with other lines of evidence, the best estimate becomes 2.9°C, 66% range 2.4° to 3.5°C (2.1° to 4.1°C, 5 to 95%), substantially narrowing uncertainty compared to recent assessments. 

Paleohydrologic proxy data and climate models show how and why eccentricity and precession influenced early Eocene hydroclimate. 

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 successes as 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. ▪ Analyzing several biomarkers in tandem can provide unique insights into the Earth system. Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 50 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.