Pre-industrial Climate Research Articles

UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model

Abstract. Many Coupled Model Intercomparison Project phase 6 (CMIP6) models have exhibited a substantial cold bias in the global mean surface temperature (GMST) in the latter part of the 20th century. An overly strong negative aerosol forcing has been suggested as a leading contributor to this bias. An updated configuration of UK Earth System Model (UKESM) version 1, UKESM1.1, has been developed with the aim of reducing the historical cold bias in this model. Changes implemented include an improved representation of SO2 dry deposition, along with several other smaller modifications to the aerosol scheme and a retuning of some uncertain parameters of the fully coupled Earth system model. The Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, a six-member historical ensemble and a subset of future scenario simulations are completed. In addition, the total anthropogenic effective radiative forcing (ERF), its components and the effective and transient climate sensitivities are also computed. The UKESM1.1 preindustrial climate is warmer than UKESM1 by up to 0.75 K, and a significant improvement in the historical GMST record is simulated, with the magnitude of the cold bias reduced by over 50 %. The warmer climate increases ocean heat uptake in the Northern Hemisphere oceans and reduces Arctic sea ice, which is in better agreement with observations. Changes to the aerosol and related cloud properties are a driver of the improved GMST simulation despite only a modest reduction in the magnitude of the negative aerosol ERF (which increases by +0.08 W m−2). The total anthropogenic ERF increases from 1.76 W m−2 in UKESM1 to 1.84 W m−2 in UKESM1.1. The effective climate sensitivity (5.27 K) and transient climate response (2.64 K) remain largely unchanged from UKESM1 (5.36 and 2.76 K respectively).

Climate model differences contribute deep uncertainty in future Antarctic ice loss.

Future projections of ice sheets in response to different climate scenarios and their associated contributions to sea level changes are subject to deep uncertainty due to ice sheet instability processes, hampering a proper risk assessment of sea level rise and enaction of mitigation/adaptation strategies. For a systematic evaluation of the uncertainty due to climate model fields used as input to the ice sheet models, we drive a three-dimensional model of the Antarctic Ice Sheet (AIS) with the output from 36 climate models to simulate past and future changes in the AIS. Simulations show that a few climate models result in partial collapse of the West AIS under modeled preindustrial climates, and the spread in future changes in the AIS's volume is comparable to the structural uncertainty originating from differing ice sheet models. These results highlight the need for improved representations of physical processes important for polar climate in climate models.

Processes Contributing to North American Cold Air Outbreaks Based on Air Parcel Trajectory Analysis

Abstract Wintertime cold air outbreaks are periods of extreme cold, often persisting for several days and spanning hundreds of kilometers or more. They are commonly associated with intrusions of cold polar air into the midlatitudes, but it is unclear whether the air mass’s initial temperature in the Arctic or its cooling as it travels is the determining factor in producing a cold air outbreak. By calculating air parcel trajectories for a preindustrial climate model scenario, we study the role of the origin and evolution of air masses traveling over sea ice and land and resulting in wintertime cold air outbreaks over central North America. We find that not all Arctic air masses result in a cold air outbreak when advected into the midlatitudes. We compare trajectories that originate in the Arctic and result in cold air outbreaks to those that also originate in the Arctic but lead to median temperatures when advected into the midlatitudes. While about one-third of the midlatitude temperature difference can be accounted for by the initial height and temperature in the Arctic, the other two-thirds are a result of differences in diabatic heating and cooling as the air masses travel. Vertical mixing of cold surface air into the air mass while it travels dominates the diabatic cooling and contributes to the cold events. Air masses leading to cold air outbreaks experience more negative sensible heat flux from the underlying surface, suggesting that preconditioning to establish a cold surface is key to producing cold air outbreaks. Significance Statement Wintertime cold air outbreaks can cause temperatures to plummet tens of degrees below freezing over the northern United States, with the potential to damage agriculture, infrastructure, and human health. Accurate predictions under climate change could help mitigate these effects, but there is disagreement over whether cold air outbreaks have declined in line with the already-observed global warming trend or persisted in spite of it. Focusing on cold air outbreaks that originate from the Arctic, we find that there must be additional cooling of the traveling air mass by mixing with very cold surface air as it moves south over North America in order to result in a cold outbreak.

Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)

Abstract. The assessment of uncertainties in landslide susceptibility modelling in a changing environment is an important, yet often neglected, task. In an Austrian case study, we investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In June 2009, extreme events of heavy thunderstorms occurred in the Styrian Basin, triggering thousands of landslides. Using a storyline approach, we discovered a generally lower landslide susceptibility for the pre-industrial climate, while for the future climate (2071–2100) a potential increase of 35 % in highly susceptible areas (storyline of much heavier rain) may be compensated for by much drier soils (−45 % areas highly susceptible to landsliding). However, the estimated uncertainties in predictions were generally high. While uncertainties related to within-event internal climate model variability were substantially lower than parametric uncertainties in the landslide susceptibility model (ratio of around 0.25), parametric uncertainties were of the same order as the climate scenario uncertainty for the higher warming levels (+3 and +4 K). We suggest that in future uncertainty assessments, an improved availability of event-based landslide inventories and high-resolution soil and precipitation data will help to reduce parametric uncertainties in landslide susceptibility models used to assess the impacts of climate change on landslide hazard and risk.

Modeled storm surge changes in a warmer world: the Last Interglacial

Abstract. The Last Interglacial (LIG; ca. 125 ka) is a period of interest for climate research as it is the most recent period of the Earth's history when the boreal climate was warmer than at present. Previous research, based on models and geological evidence, suggests that the LIG may have featured enhanced patterns of ocean storminess, but this remains hotly debated. Here, we apply state-of-the-art climate and hydrodynamic modeling to simulate changes in sea level extremes caused by storm surges, under LIG and pre-industrial climate forcings. Significantly higher seasonal LIG sea level extremes emerge for coastlines along northern Australia, the Indonesian archipelago, much of northern and eastern Africa, the Mediterranean Sea, the Gulf of Saint Lawrence, the Arabian Sea, the east coast of North America, and islands of the Pacific Ocean and of the Caribbean. Lower seasonal LIG sea level extremes emerge for coastlines along the North Sea, the Bay of Bengal, China, Vietnam, and parts of Central America. Most of these anomalies are associated with anomalies in seasonal sea level pressure minima and in eddy kinetic energy calculated from near-surface wind fields, and therefore seem to originate from anomalies in the meridional position and intensity of the predominant wind bands. In a qualitative comparison, LIG sea level extremes seem generally higher than those projected for future warmer climates. These results help to constrain the interpretation of coastal archives of LIG sea level indicators.

Consolidating historical instrumental observations in southern Australia for assessing pre-industrial weather and climate variability

Human-induced climate change has resulted in long-term drying trends across southern Australia, particularly during the cool season, with the most pronounced impacts observed in the southwest since the 1970s. Although these trends have been linked to changes in large-scale atmospheric circulation features, the limited number of daily weather datasets that extend into the pre-industrial period have so far prevented an assessment of the long-term context of synoptic-level changes associated with global warming. To address this need, we present the development of the longest sub-daily atmospheric pressure, temperature and rainfall records for Australia beginning in 1830. We first consolidate a range of historical observations from the two southern Australian cities of Perth and Adelaide. After assessing the quality and homogeneity of these records, we verify their ability to capture the weather and climate features produced by the Southern Hemisphere’s key climate modes of variability. Our analysis shows the historical observations are sensitive to the influence of large-scale dynamical drivers of Australian climate, as well as the relationship between southwestern and southeastern Australia. Finally, we demonstrate the ability of the dataset to resolve daily weather extremes by examining three severe storms that occurred in the nineteenth century associated with westerly storm tracks that influence southern Australia. The historical dataset introduced here provides a foundation for investigating pre-industrial weather and climate variability in southern Australia, extending the potential for attribution studies of anthropogenically-influenced weather and climate extremes.

Integrating a Disaster Displacement Dimension in Climate Change Attribution

Populations around the world have already experienced the increasing severity of extreme weather causing disaster displacement. Anthropogenic climate change can intensify these impacts. Extreme event attribution studies center around the question of whether impactful extreme events could have occurred in a pre-industrial climate. Here, we argue that the next step for attribution science is to focus on those most vulnerable populations to future extremes and impacts from climate change. Up until now, the vulnerability dimension has not been systematically addressed in attribution studies, yet it would add urgently needed context, given the vast differences in adaptive capacity. We propose three integrative points to cascade disaster displacement linked to anthropogenic climate change.

Attribution of the human influence on heavy rainfall associated with flooding events during the 2012, 2016, and 2018 March-April-May seasons in Kenya

The changing probabilities of extreme climate and weather events, in terms of frequency, intensity, spatial extent, duration, and timing is one of the most noticeable and damaging manifestations of human-induced climate change. During the March-April-May (MAM) rainfall season of 2012, 2016 and 2018, Kenya experienced high rainfall that caused both widespread and localised flooding, resulting in human and livestock deaths, destruction of infrastructure and property, bursting of riverbanks, submerging of farmlands and emergence of isolated cases of water-borne diseases. Here, we aim to quantify how the magnitude of heavy rainfall during these seasons may have been altered by human-induced climate change. We undertake a probabilistic attribution analysis using three different approaches utilising two observational datasets and two independent climate model experiment set-ups. We analyse three different seasonal heavy rainfall indices, maximum consecutive 5-day, 10-day, and 20-day rainfall, to compare the magnitude of maxima recorded in MAM 2012, 2016 and 2018 with the magnitude of maxima in a pre-industrial climate (with little or no anthropogenic influence). We find a shift towards intensification of extreme rainfall in today's climate, although these increases are not in all cases statistically distinguishable from our estimates of magnitudes in the preindustrial climate. Although we find no significant anthropogenic climate change influence, the intensification of extreme rainfall amid the observed drying trend and the projected increases in rainfall in the MAM season in Kenya, leave the already vulnerable societies with uncertainties about how to prepare for a changing climate. This study, therefore, provides a basis for an in-depth assessment of current and future trends of extreme rainfall in East Africa in adapting to changing climate risks for sustainable development in the already vulnerable and less resilient society.

Glacial‐Interglacial Controls on Ocean Circulation and Temperature During the Permo‐Carboniferous

AbstractThe apex of Earth's penultimate icehouse during the Permo‐Carboniferous coincided with dramatic glacial‐interglacial fluctuations in atmospheric CO2, sea level, and high‐latitude ice. Global transformations in marine fauna also occurred during this interval, including a rise to peak foraminiferal diversity, suggesting that glacial‐interglacial climate change impacted marine ecosystems. Nevertheless, changes in ocean circulation and temperature over the Permo‐Carboniferous and their influence on marine ecosystem change are largely unknown. Here, we present simulations of glacial and interglacial phases of the latest Carboniferous‐early Permian (∼305‐295 Ma) using the Community Earth System Model version 1.2 to provide estimates of global ocean circulation and temperature during this interval. We characterize general patterns of glacial and interglacial surface ocean currents, temperature, and salinity, and compare them to the documented abundance and distribution of Permo‐Carboniferous marine fauna as well as a preindustrial climate simulation. We then explore how glacial‐interglacial changes in atmospheric CO2, sea level, and high‐latitude ice extent impact thermohaline circulation. We find that glacial‐interglacial changes in equatorial surface temperatures are consistently ∼3–6°C. Ocean circulation is stronger overall in the glacial simulation, particularly as lower atmospheric CO2 enables deep convection in the Northern Hemisphere. Wind‐driven circulation, heat transport, and upwelling intensity are stronger overall in the Permo‐Carboniferous superocean relative to the preindustrial oceans at the same level of atmospheric CO2. We also find that CO2‐induced glacial conditions of the early Permian may have promoted foraminiferal diversity through increased thermal gradients and suppressed riverine input in marine shelf environments.

Using machine learning to identify novel hydroclimate states

Anthropogenic climate change is expected to alter drought risk in the future. However, droughts are not uncommon or unprecedented, as documented in tree-ring-based reconstructions of the summer average Palmer drought severity index (PDSI). Using an unsupervised machine-learning method trained on these reconstructions of pre-industrial climate, we identify outliers: years in which the spatial pattern of PDSI is unusual relative to ‘normal' variability. We show that in many regions, outliers are more frequently identified in the twentieth and twenty-first centuries. This trend is more pronounced when the regional drought atlases are combined into a single global dataset. By definition, outlier patterns at the 10% level are expected to occur once per decade, but from 1950 to 2000 more than 6 years per decade are identified as outliers in the global drought atlas (GDA). Extending the GDA through 2020 using an observational dataset suggests that anomalous global drought conditions are present in 80% of years in the twenty-first century. Our results indicate, without recourse to climate models, that the world is more frequently experiencing drought conditions that are highly unusual in the context of past natural climate variability.This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.

Internal multi-centennial variability of the Atlantic Meridional Overturning Circulation simulated by EC-Earth3

We report a multi-centennial oscillation of the Atlantic Meridional Overturning Circulation (AMOC) simulated by the EC-Earth3 climate model under the pre-industrial climate. This oscillation has an amplitude of ~ 6 Sv and a period of ~ 150 years and significantly impacts the atmosphere. We find that it is a self-sustained low-frequency internal variability, driven by the accumulation of salinity anomalies in the Arctic and their release into the North Atlantic, affecting the water column stability and the deep convection. Sea ice plays a major role in creating the salinity anomaly in the Arctic, while the anomalous Arctic oceanic circulation, which drives the exchange of liquid freshwater between the Arctic and the open ocean, is the main responsible for its southward propagation. Interestingly, EC-Earth3 simulations with increased greenhouse concentrations, and therefore under a warmer climate, do not exhibit these strong AMOC fluctuations. We hypothesize that in a quasi-equilibrium climate with a global air surface temperature 4.5° higher than the pre-industrial period, the low amount of sea ice in the high latitudes of the North Atlantic is no longer able to trigger the mechanism.

Extending the Heat Index

Abstract The heat index is a widely used measure of apparent temperature that accounts for the effects of humidity using Steadman’s model of human thermoregulation. Steadman’s model, however, gives unphysical results when the air is too hot and humid or too cold and dry, leading to an undefined heat index. For example, at a relative humidity of 80%, the heat index is only defined for temperatures in the range of 288–304 K (59°–88°F). Here, Steadman’s thermoregulation model is extended to define the heat index for all combinations of temperature and humidity, allowing for an assessment of Earth’s future habitability. The extended heat index can be mapped onto physiological responses of an idealized human, such as heat exhaustion, heat stroke, and even heat death, providing an indication of regional health outcomes for different degrees of global warming. Significance Statement The existing heat index is well-defined for most combinations of high temperature and humidity experienced on Earth in the preindustrial climate, but global warming is increasingly generating conditions for which the heat index is undefined. Therefore, an extension of the original heat index is needed. When extending the heat index, we use the same physiological model as in the original work of Steadman to ensure backward compatibility. Following Steadman, each value of the heat index is mapped onto a measurable physiological variable, which can be useful for assessing the health impacts of various combinations of temperature and humidity, especially for outdoor workers.

Effects of Increasing the Category Resolution of the Sea Ice Thickness Distribution in a Coupled Climate Model on Arctic and Antarctic Sea Ice Mean State

AbstractMany modern sea ice models used in global climate models represent the subgrid‐scale heterogeneity in sea ice thickness with an ice thickness distribution (ITD), which improves model realism by representing the significant impact of the high spatial heterogeneity of sea ice thickness on thermodynamic and dynamic processes. Most models default to five thickness categories. However, little has been done to explore the effects of the resolution of this distribution (number of categories) on sea‐ice feedbacks in a coupled model framework and resulting representation of the sea ice mean state. Here, we explore this using sensitivity experiments in CESM2 with the standard 5 ice thickness categories and 15 ice thickness categories. Increasing the resolution of the ITD in a run with preindustrial climate forcing results in substantially thicker Arctic sea ice year‐round. Analyses show that this is a result of the ITD influence on ice strength. With 15 ITD categories, weaker ice occurs for the same average thickness, resulting in a higher fraction of ridged sea ice. In contrast, the higher resolution of thin ice categories results in enhanced heat conduction and bottom growth and leads to only somewhat increased winter Antarctic sea ice volume. The spatial resolution of the ICESat‐2 satellite mission provides a new opportunity to compare model outputs with observations of seasonal evolution of the ITD in the Arctic (ICESat‐2; 2018–2021). Comparisons highlight significant differences from the ITD modeled with both runs over this period, likely pointing to underlying issues contributing to the representation of average thickness.

Attributing observed permafrost warming in the northern hemisphere to anthropogenic climate change

Permafrost temperatures are increasing globally with the potential of adverse environmental and socio-economic impacts. Nonetheless, the attribution of observed permafrost warming to anthropogenic climate change has relied mostly on qualitative evidence. Here, we compare long permafrost temperature records from 15 boreholes in the northern hemisphere to simulated ground temperatures from Earth system models contributing to CMIP6 using a climate change detection and attribution approach. We show that neither pre-industrial climate variability nor natural drivers of climate change suffice to explain the observed warming in permafrost temperature averaged over all boreholes. However, simulations are consistent with observations if the effects of human emissions on the global climate system are considered. Moreover, our analysis reveals that the effect of anthropogenic climate change on permafrost temperature is detectable at some of the boreholes. Thus, the presented evidence supports the conclusion that anthropogenic climate change is the key driver of northern hemisphere permafrost warming.

A new global surface temperature reconstruction for the Last Glacial Maximum

Abstract. We present a new reconstruction of surface air temperature and sea surface temperature for the Last Glacial Maximum. The method blends model fields and sparse proxy-based point estimates through a data assimilation approach. Our reconstruction updates that of Annan and Hargreaves (2013), using the full range of general circulation model (GCM) simulations which contributed to three generations of the PMIP database, three major compilations of gridded sea surface temperature (SST) and surface air temperature (SAT) estimates from proxy data, and an improved methodology based on an ensemble Kalman filter. Our reconstruction has a global annual mean surface air temperature anomaly of -4.5±0.9 ∘C relative to the pre-industrial climate. This is slightly colder than the previous estimate of Annan and Hargreaves (2013), with an upwards revision on the uncertainty due to different methodological assumptions. It is, however, substantially less cold than the recent reconstruction of Tierney et al. (2020). We show that the main reason for this discrepancy is in the choice of prior. We recommend the use of the multi-model ensemble of opportunity as potentially offering a credible prior, but it is important that the range of models included in the PMIP ensembles represent the main sources of uncertainty as realistically and comprehensively as practicable if they are to be used in this way.

SnowClim v1.0: high-resolution snow model and data for the western United States

Abstract. Seasonal snowpack dynamics shape the biophysical and societal characteristics of many global regions. However, snowpack accumulation and duration have generally declined in recent decades, largely due to anthropogenic climate change. Mechanistic understanding of snowpack spatiotemporal heterogeneity and climate change impacts will benefit from snow data products that are based on physical principles, simulated at high spatial resolution, and cover large geographic domains. Most existing datasets do not meet these requirements, hindering our ability to understand both contemporary and changing snow regimes and to develop adaptation strategies in regions where snowpack patterns and processes are important components of Earth systems. We developed a computationally efficient process-based snow model, SnowClim, that can be run in the cloud. The model was evaluated and calibrated at Snowpack Telemetry (SNOTEL) sites across the western United States (US), achieving a site-median root-mean-squared error for daily snow water equivalent (SWE) of 64 mm, bias in peak SWE of −2.6 mm, and bias in snow duration of −4.5 d when run hourly. Positive biases were found at sites with mean winter temperature above freezing where the estimation of precipitation phase is prone to errors. The model was applied to the western US (a domain covering 3.1 million square kilometers) using newly developed forcing data created by statistically downscaling pre-industrial, historical, and pseudo-global warming climate data from the Weather Research and Forecasting (WRF) model. The resulting product is the SnowClim dataset, a suite of summary climate and snow metrics, including monthly SWE and snow depth, as well as annual maximum SWE and snow cover duration, for the western US at 210 m spatial resolution (Lute et al., 2021). The physical basis, large extent, and high spatial resolution of this dataset enable novel analyses of changing hydroclimate and its implications for natural and human systems.

Stratosphere‐Troposphere Exchanges of Air Mass and Ozone Concentration in the Last Glacial Maximum

AbstractStratosphere‐troposphere exchange (STE) of ozone represents a significant source term in the tropospheric ozone budget and can impact surface ozone concentrations, tropospheric oxidation capacity, and methane lifetime. Using the Whole Atmosphere Community Climate Model 6, changes in the air mass and ozone STEs in the Last Glacial Maximum (LGM) as compared with preindustrial (PI) climate are investigated. We use dynamic isentropic surfaces that are determined by fitting to the tropical tropopauses as the upper boundary of the lowermost stratosphere in a mass budget approach, a method particularly suitable for estimating air mass and ozone STEs across different climates. Relative to the PI, the magnitude of ozone STE in the LGM is decreased by 14%–19%, 18%–24%, 18%–23%, 16%–21%, and 15%–21% over the Northern hemisphere extratropics, Southern hemisphere extratropics, the tropics, the extratropics, and the globe, respectively. The extratropical and global decreases are mainly caused by decreased ozone in the extratropical lower stratosphere associated with a weakening of Brewer‐Dobson circulation, while changes in air mass fluxes play a minor role because the effects of weakening Brewer‐Dobson circulation and increased isentropic density partly cancel each other. Analysis of the modeled tropospheric ozone budget indicates that the ozone STE in the LGM is 28% of the tropospheric ozone production rate, as compared to about 9% in the modern climate (year 2000) and 19% in the PI.

Calendar effects on surface air temperature and precipitation based on model-ensemble equilibrium and transient simulations from PMIP4 and PACMEDY

Abstract. Numerical modeling enables a comprehensive understanding not only of the Earth's system today, but also of the past. To date, a significant amount of time and effort has been devoted to paleoclimate modeling and analysis, which involves the latest and most advanced Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). The definition of seasonality, which is influenced by slow variations in the Earth's orbital parameters, plays a key role in determining the calculated seasonal cycle of the climate. In contrast to the classical calendar used today, where the lengths of the months and seasons are fixed, the angular calendar calculates the lengths of the months and seasons according to a fixed number of degrees along the Earth's orbit. When comparing simulation results for different time intervals, it is essential to account for the angular calendar to ensure that the data for comparison are from the same position along the Earth's orbit. Most models use the classical calendar, which can lead to strong distortions of the monthly and seasonal values, especially for the climate of the past. Here, by analyzing daily outputs from multiple PMIP4 model simulations, we examine calendar effects on surface air temperature and precipitation under mid-Holocene, Last Interglacial, and pre-industrial climate conditions. We came to the following conclusions. (a) The largest cooling bias occurs in boreal autumn when the classical calendar is applied for the mid-Holocene and Last Interglacial, due to the fact that the vernal equinox is fixed on 21 March. (b) The sign of the temperature anomalies between the Last Interglacial and pre-industrial in boreal autumn can be reversed after the switch from the classical to angular calendar, particularly over the Northern Hemisphere continents. (c) Precipitation over West Africa is overestimated in boreal summer and underestimated in boreal autumn when the classical seasonal cycle is applied. (d) Finally, month-length adjusted values for surface air temperature and precipitation are very similar to the day-length adjusted values, and therefore correcting the calendar based on the monthly model results can largely reduce the artificial bias. In addition, we examine the calendar effects in three transient simulations for 6–0 ka by AWI-ESM, MPI-ESM, and IPSL-CM. We find significant discrepancies between adjusted and unadjusted temperature values over continents for both hemispheres in boreal autumn, while for other seasons the deviations are relatively small. A drying bias can be found in the summer monsoon precipitation in Africa (in the classical calendar), whereby the magnitude of bias becomes smaller over time. Overall, our study underlines the importance of the application of calendar transformation in the analysis of climate simulations. Neglecting the calendar effects could lead to a profound artificial distortion of the calculated seasonal cycle of surface air temperature and precipitation.

Integrating attribution with adaptation for unprecedented future heatwaves

Citizens in many countries are now experiencing record-smashing heatwaves that were intensified due to anthropogenic climate change. Whether today’s most impactful heatwaves could have occurred in a pre-industrial climate, traditionally a central focus of attribution research, is fast becoming an obsolete question. The next frontier for attribution science is to inform adaptation decision-making in the face of unprecedented future heat.

Did agriculture beget agriculture during the past several millennia?

The Early Anthropogenic Hypothesis posits that carbon emissions from ancient farming caused global warming by raising greenhouse gas concentrations (GHG) during the late-Holocene, in contrast to declining GHG during prior interglacials. Here, we explore whether this hypothesized pre-industrial anthropogenic climate change also fostered agriculture by creating more favorable growing conditions. We investigate this question using transient GCM experiments and the Cultivation Suitability Index, CSI, which quantifies farming potential based on climatic and soil factors. The Community Earth System Model (CESM) simulated the climate of the last 6000 years under two alternative forcing scenarios: (1) ACTUAL: orbital variations, historical land cover change, and observed GHG increase; and (2) NATURAL: orbital variations, fixed (natural) land cover, and expected natural GHG decline. The CSI was computed using CESM model output and observed soil properties. Ancient land clearance affected the simulated climate both biogeochemically (via carbon emissions) and biogeophysically (altered surface albedo and land-atmosphere energy fluxes). Biogeochemical effects generally dominated, as evidenced by a warmer (and slightly wetter) global climate in ACTUAL versus NATURAL by year 1850. But a few regions were cooler in ACTUAL, especially interior Eurasia during winter-spring, due to a higher surface albedo from cropland. The expansion of agriculture generally mitigated the orbitally induced decline in cultivation potential in boreal extratropics but worsened it in low latitudes. Our results suggest that ancient farming may have thus promoted a “push-pull” migration during the late-Holocene by inducing climate changes that encouraged a northward spread of agriculture.