Sensitivity of the Eocene climate to CO₂ and orbital variability

The early Eocene, from about 56 Ma, with high atmospheric CO2 levels, offers an analogue for the response of the Earth’s climate system to anthropogenic fossil fuel burning. In this study, we present an ensemble of 50 Earth system model runs with an early Eocene palaeogeography and variation in the forcing values of atmospheric CO2 and the Earth’s orbital parameters. Relationships between simple summary metrics of model outputs and the forcing parameters are identified by linear modelling, providing estimates of the relative magnitudes of the effects of atmospheric CO2 and each of the orbital parameters on important climatic features, including tropical–polar temperature difference, ocean–land temperature contrast, Asian, African and South (S.) American monsoon rains, and climate sensitivity. Our results indicate that although CO2 exerts a dominant control on most of the climatic features examined in this study, the orbital parameters also strongly influence important components of the ocean–atmosphere system in a greenhouse Earth. In our ensemble, atmospheric CO2 spans the range 280–3000 ppm, and this variation accounts for over 90 % of the effects on mean air temperature, southern winter high-latitude ocean– land temperature contrast and northern winter tropical–polar temperature difference. However, the variation of precession accounts for over 80 % of the influence of the forcing parameters on the Asian and African monsoon rainfall, and obliquity variation accounts for over 65 % of the effects on winter ocean–land temperature contrast in high northern latitudes and northern summer tropical–polar temperature difference. Our results indicate a bimodal climate sensitivity, with values of 4.36 and 2.54 ◦C, dependent on low or high states of atmospheric CO2 concentration, respectively, with a threshold at approximately 1000 ppm in this model, and due to a saturated vegetation–albedo feedback. Our method gives a quantitative ranking of the influence of each of the forcing parameters on key climatic model outputs, with additional spatial information from singular value decomposition providing insights into likely physical mechanisms. The results demonstrate the importance of orbital variation as an agent of change in climates of the past, and we demonstrate that emulators derived from our modelling output can be used as rapid and efficient surrogates of the full complexity model to provide estimates of climate conditions from any set of forcing parameters

Precessional forcing of tropical vegetation carbon storage

Since the Mid-Pleistocene Revolution, which occurred about one million years ago, global temperatures have fluctuated with a quasi-periodicity of ~100 thousand years (kyr). The pattern of past change in the extent of woodlands, and therefore by inference vegetation carbon storage, has been demonstrated to have a strong positive link with this global temperature change at high and mid latitudes. However, understanding of climate systems and ecosystem function indicates that the pattern of woodland change at low latitudes may follow a fundamentally different pattern. We present output from the intermediate complexity model GENIE-1, comprising a single transient simulation over the last 800 kyr and a 174-member ensemble of 130 kyr transient simulations over the last glacial cycle. These simulations suggest that whilst vegetation carbon storage in mid-high northern latitudes robustly follows the characteristic ~100 kyr cycle, this signal is not a robust feature of tropical vegetation which is subject to stronger direct forcing by the precessional (21 kyr) orbital cycle (albeit with a highly uncertain response). We conclude that the correlation of palaeoenvironmental records from low latitudes with global temperature change must be done with caution

Inferring late-Holocene climate in the Ecuadorian Andes using a chironomid-based temperature inference model

Presented here is the first chironomid calibration data set for tropical South America. Surface sediments were collected from 59 lakes across Bolivia (15 lakes), Peru (32 lakes), and Ecuador (12 lakes) between 2004 and 2013 over an altitudinal gradient from 150 m above sea level (a.s.l) to 4655 m a.s.l, between 0–17◦ S and 64–78◦ W. The study sites cover a mean annual temperature (MAT) gradient of 25 ◦ C. In total, 55 chironomid taxa were identified in the 59 calibration data set lakes. When used as a single explanatory variable, MAT explains 12.9% of the variance (λ1/λ2 =1.431). Two inference models were developed using weighted averaging (WA) and Bayesian methods. The best performing model using conventional statistical methods was a WA (inverse) model (R2jack= 0.890; RMSEPjack= 2.404 ◦C, RMSEP – root mean jack squared error of prediction; mean biasjack = −0.017 ◦C; max biasjack = 4.665 ◦C). The Bayesian method produced a model with R2jack = 0.909, RMSEPjack = 2.373 ◦C, mean jack biasjack = 0.598 ◦C, and max biasjack = 3.158 ◦C. Both models were used to infer past temperatures from a ca. 3000-year record from the tropical Andes of Ecuador, Laguna Pindo. Inferred temperatures fluctuated around modern-day conditions but showed significant departures at certain intervals (ca. 1600 cal yr BP; ca. 3000–2500 cal yr BP). Both methods (WA and Bayesian) showed similar patterns of temperature variability; however, the magnitude of fluctuations differed. In general the WA method was more variable and often underestimated Holocene temperatures (by ca. −7 ± 2.5 ◦C relative to the modern period). The Bayesian method provided temperature anomaly estimates for cool periods that lay within the expected range of the Holocene (ca. −3 ± 3.4 ◦C). The error associated with both reconstructions is consistent with a constant temperature of 20 ◦C for the past 3000 years. We would caution, however, against an over-interpretation at this stage. The reconstruction can only currently be deemed qualitative and requires more research before quantitative estimates can be generated with confidence. Increasing the number, and spread, of lakes in the calibration data set would enable the detection of smaller climate signals

PLASIM–GENIE v1.0: a new intermediate complexity AOGCM

We describe the development, tuning and climate of Planet Simulator (PLASIM)–Grid-ENabled Integrated Earth system model (GENIE), a new intermediate complexity Atmosphere–Ocean General Circulation Model (AOGCM), built by coupling the Planet Simulator to the ocean, sea-ice and land-surface components of the GENIE Earth system model. PLASIM–GENIE supersedes GENIE-2, a coupling of GENIE to the Reading Intermediate General Circulation Model (IGCM). The primitive-equation atmosphere includes chaotic, three-dimensional (3-D) motion and interactive radiation and clouds, and dominates the computational load compared to the relatively simpler frictional-geostrophic ocean, which neglects momentum advection. The model is most appropriate for long-timescale or large ensemble studies where numerical efficiency is prioritised, but lack of data necessitates an internally consistent, coupled calculation of both oceanic and atmospheric fields. A 1000-year simulation with PLASIM–GENIE requires approximately 2 weeks on a single node of a 2.1 GHz AMD 6172 CPU. We demonstrate the tractability of PLASIM–GENIE ensembles by deriving a subjective tuning of the model with a 50- member ensemble of 1000-year simulations. The simulated climate is presented considering (i) global fields of seasonal surface air temperature, precipitation, wind, solar and thermal radiation, with comparisons to reanalysis data; (ii) vegetation carbon, soil moisture and aridity index; and (iii) sea surface temperature, salinity and ocean circulation. Considering its resolution, PLASIM–GENIE reproduces the main features of the climate system well and demonstrates usefulness for a wide range of applications

Coupled climate–carbon cycle simulation of the Last Glacial Maximum atmospheric CO2 decrease using a large ensemble of modern plausible parameter sets

During the Last Glacial Maximum (LGM), atmospheric CO2 was around 90 ppmv lower than during the pre-industrial period. The reasons for this decrease are most often elucidated through factorial experiments testing the impact of individual mechanisms. Due to uncertainty in our understanding of the real system, however, the different models used to conduct the experiments inevitably take on different parameter values and different structures. In this paper, the objective is therefore to take an uncertainty-based approach to investigating the LGM CO2 drop by simulating it with a large ensemble of parameter sets, designed to allow for a wide range of large-scale feedback response strengths. Our aim is not to definitely explain the causes of the CO2 drop but rather explore the range of possible responses. We find that the LGM CO2 decrease tends to predominantly be associated with decreasing sea surface temperatures (SSTs), increasing sea ice area, a weakening of the Atlantic Meridional Overturning Circulation (AMOC), a strengthening of the Antarctic Bottom Water (AABW) cell in the Atlantic Ocean, a decreasing ocean biological productivity, an increasing CaCO3 weathering flux and an increasing deep-sea CaCO3 burial flux. The majority of our simulations also predict an increase in terrestrial carbon, coupled with a decrease in ocean and increase in lithospheric carbon. We attribute the increase in terrestrial carbon to a slower soil respiration rate, as well as the preservation rather than destruction of carbon by the LGM ice sheets. An initial comparison of these dominant changes with observations and paleoproxies other than carbon isotope and oxygen data (not evaluated directly in this study) suggests broad agreement. However, we advise more detailed comparisons in the future, and also note that, conceptually at least, our results can only be reconciled with carbon isotope and oxygen data if additional processes not included in our model are brought into play

PALEO-PGEM v1.0: a statistical emulator of Pliocene–Pleistocene climate

We describe the development of the “Paleoclimate PLASIM-GENIE (Planet Simulator–Grid-Enabled Integrated Earth system model) emulator” PALEO-PGEM and its application to derive a downscaled high-resolution spatio-temporal description of the climate of the last 5×106 years. The 5×106-year time frame is interesting for a range of paleo-environmental questions, not least because it encompasses the evolution of humans. However, the choice of time frame was primarily pragmatic; tectonic changes can be neglected to first order, so that it is reasonable to consider climate forcing restricted to the Earth's orbital configuration, ice-sheet state, and the concentration of atmosphere CO2. The approach uses the Gaussian process emulation of the singular value decomposition of ensembles of the intermediate-complexity atmosphere–ocean GCM (general circulation model) PLASIM-GENIE. Spatial fields of bioclimatic variables of surface air temperature (warmest and coolest seasons) and precipitation (wettest and driest seasons) are emulated at 1000-year intervals, driven by time series of scalar boundary-condition forcing (CO2, orbit, and ice volume) and assuming the climate is in quasi-equilibrium. Paleoclimate anomalies at climate model resolution are interpolated onto the observed modern climatology to produce a high-resolution spatio-temporal paleoclimate reconstruction of the Pliocene–Pleistocene

Modeling the ecology and evolution of biodiversity: Biogeographical cradles, museums, and graves

Individual processes shaping geographical patterns of biodiversity are increasingly understood, but their complex interactions on broad spatial and temporal scales remain beyond the reach of analytical models and traditional experiments. To meet this challenge, we built a spatially explicit, mechanistic simulation model implementing adaptation, range shifts, fragmentation, speciation, dispersal, competition, and extinction, driven by modeled climates of the past 800,000 years in South America. Experimental topographic smoothing confirmed the impact of climate heterogeneity on diversification. The simulations identified regions and episodes of speciation (cradles), persistence (museums), and extinction (graves). Although the simulations had no target pattern and were not parameterized with empirical data, emerging richness maps closely resembled contemporary maps for major taxa, confirming powerful roles for evolution and diversification driven by topography and climate

The Relative Importance of Phytoplankton Light Absorption and Ecosystem Complexity in an Earth System Model

We investigate the relative importance of ecosystem complexity and phytoplankton light absorption for climate studies. While the complexity of Earth System models (ESMs) with respect to marine biota has increased over the past years, the relative importance of biological processes in driving climate-relevant mechanisms such as the biological carbon pump and phytoplankton light absorption is still unknown. The climate effects of these mechanisms have been studied separately, but not together. To shed light on the role of biologically mediated feedbacks, we performed different model experiments with the EcoGENIE ESM. The model experiments have been conducted with and without phytoplankton light absorption and with two or 12 plankton functional types. For a robust comparison, all simulations are tuned to have the same primary production. Our model experiments show that phytoplankton light absorption changes ocean physics and biogeochemistry. Higher sea surface temperature decreases the solubility of CO2 which in turn increases the atmospheric CO2 concentration, and finally the atmospheric temperature rises by 0.45°C. An increase in ecosystem complexity increases the export production of particulate organic carbon but decreases the amount of dissolved organic matter. These changes in the marine carbon cycling, however, hardly reduces the atmospheric CO2 concentrations and slightly decreases the atmospheric temperature by 0.034°C. Overall we show that phytoplankton light absorption has a higher impact on the carbon cycle and on the climate system than a more detailed representation of the marine biota

Climate pathways behind phytoplankton-induced atmospheric warming

We investigate the ways in which marine biologically mediated heating increases the surface atmospheric temperature. While the effects of phytoplankton light absorption on the ocean have gained attention over the past years, the impact of this biogeophysical mechanism on the atmosphere is still unclear. Phytoplankton light absorption warms the surface of the ocean, which in turn affects the air–sea heat and CO2 exchanges. However, the contribution of air–sea heat versus CO2 fluxes in the phytoplankton-induced atmospheric warming has not been yet determined. Different so-called climate pathways are involved. We distinguish heat exchange, CO2 exchange, dissolved CO2, solubility of CO2 and sea-ice-covered area. To shed more light on this subject, we employ the EcoGEnIE Earth system model that includes a new light penetration scheme and isolate the effects of individual fluxes. Our results indicate that phytoplankton-induced changes in air–sea CO2 exchange warm the atmosphere by 0.71 ∘C due to higher greenhouse gas concentrations. The phytoplankton-induced changes in air–sea heat exchange cool the atmosphere by 0.02 ∘C due to a larger amount of outgoing longwave radiation. Overall, the enhanced air–sea CO2 exchange due to phytoplankton light absorption is the main driver in the biologically induced atmospheric heating

Tectonic and climatic drivers of Asian monsoon evolution.

Asian Monsoon rainfall supports the livelihood of billions of people, yet the relative importance of different drivers remains an issue of great debate. Here, we present 30 million-year model-based reconstructions of Indian summer monsoon and South East Asian monsoon rainfall at millennial resolution. We show that precession is the dominant direct driver of orbital variability, although variability on obliquity timescales is driven through the ice sheets. Orographic development dominated the evolution of the South East Asian monsoon, but Indian summer monsoon evolution involved a complex mix of contributions from orography (39%), precession (25%), atmospheric CO2 (21%), ice-sheet state (5%) and ocean gateways (5%). Prior to 15 Ma, the Indian summer monsoon was broadly stable, albeit with substantial orbital variability. From 15 Ma to 5 Ma, strengthening was driven by a combination of orography and glaciation, while closure of the Panama gateway provided the prerequisite for the modern Indian summer monsoon state through a strengthened Atlantic meridional overturning circulation