Climate Sensitivity on Geological Timescales Controlled by Nonlinear Feedbacks and Ocean Circulation

Farnsworth, Alexander; Lunt, Daniel J.; O'Brien, Charlotte L; Foster, Gavin L.; Inglis, Gordon N.; Markwick, Paul J.; Pancost, Richard D.; Robinson, Stuart A.

doi:10.1029/2019gl083574

Cited by 120 publications

(168 citation statements)

References 54 publications

(97 reference statements)

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“…However, the lower resolution HadCM3L model has been previously used to simulate a range of pre-Quaternary climates (e.g. Lunt et al, 2016;Farnsworth et al, 2019) HadCM3 model simulations The HadCM3 simulations are carried out at ×1, ×2, and ×3 CO 2 concentrations. Several ocean gateways were artificially widened to allow unrestricted throughflow and maximum water depths in parts of the Arctic Ocean were reduced.…”

Section: Hadcm3mentioning

confidence: 99%

DeepMIP: Model intercomparison of early Eocene climatic optimum (EECO) large-scale climate features and comparison with proxy data

Lunt¹,

Bragg²,

Chan³

et al. 2020

Preprint

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Abstract. We present results from an ensemble of seven 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 DeepMIP (www.deepmip.org), and as such all models have been configured with identical paleogeographic and vegetation boundary conditions. The results indicate that these non-CO2 boundary conditions contribute between 3 and 5 °C to Eocene warmth. Compared to results from previous studies, the DeepMIP simulations show reduced spread of global mean surface temperature response across the ensemble, for a given atmospheric CO2 concentration. In a marked departure from the results from previous simulations, at least two of the DeepMIP models (CESM and GFDL) are consistent with proxy indicators of global mean temperature, and atmospheric CO2, and meridional SST gradients. The best agreement with global SST proxies from these models occurs at CO2 concentrations of around 2400 ppmv. At a more regional scale the models lack skill in reproducing the proxy SSTs, in particular in the southwest Pacific, around New Zealand and south Australia, where the modelled anomalies are substantially less than indicated by the proxies. However, in these regions modelled continental surface air temperature anomalies are consistent with surface air temperature proxies, implying an 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 and aerosols.

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Section: Hadcm3mentioning

confidence: 99%

DeepMIP: Model intercomparison of early Eocene climatic optimum (EECO) large-scale climate features and comparison with proxy data

Lunt¹,

Bragg²,

Chan³

et al. 2020

Preprint

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“…Higher-resolution modelling and better representation of climate feedbacks offer some potential improvements in this regard (Huber and Caballero, 2011;Baatsen et al, 2018), and the current Deep-MIP modelling effort might provide further insights into the causes of this common model bias. It should also be noted that these simulations were run with relatively arbitrary pCO 2 levels (although they are of a plausible magnitude; Pearson et al, 2009;Pagani et al, 2011;Foster et al, 2017), and these could be refined to provide a slightly better absolute fit to the data. Orbital variability does not appear to have a major impact on the comparison, as shown by the relatively minor impact on the results in the FOAM simulations and due to the length of the averaged periods of the proxy records.…”

Section: Discrepancies and Uncertainty In The Latitudinal Temperaturementioning

confidence: 99%

Changes in the high-latitude Southern Hemisphere through the Eocene–Oligocene transition: a model–data comparison

et al. 2020

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The global and regional climate changed dramatically with the expansion of the Antarctic Ice Sheet at the Eocene-Oligocene transition (EOT). These large-scale changes are generally linked to declining atmospheric pCO 2 levels and/or changes in Southern Ocean gateways such as the Drake Passage around this time. To better understand the Southern Hemisphere regional climatic changes and the impact of glaciation on the Earth's oceans and atmosphere at the EOT, we compiled a database of 10 ocean and 4 landsurface temperature reconstructions from a range of proxy records and compared this with a series of fully coupled, low-resolution climate model simulations from two models (HadCM3BL and FOAM). Regional patterns in the proxy records of temperature show that cooling across the EOT was less at high latitudes and greater at mid-latitudes. While certain climate model simulations show moderate-good performance at recreating the temperature patterns shown in the data before and after the EOT, in general the model simulations do not capture the absolute latitudinal temperature gradient shown by the data, being too cold, particularly at high latitudes. When taking into account the absolute temperature before and after the EOT, as well as the change in temperature across it, simulations with a closed Drake Passage before and after the EOT or with an opening of the Drake Passage across the EOT perform poorly, whereas simulations with a drop in atmospheric pCO 2 in combination with ice growth generally perform better. This provides further sup-port for previous research that changes in atmospheric pCO 2 are more likely to have been the driver of the EOT climatic changes, as opposed to the opening of the Drake Passage.www.clim-past.net/16/555/2020/

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“…The transfer function is generated from a pair of Eocene climate model simulations, carried out at two CO2 concentrations. The first simulations are the same 2x CO2 and 4x CO2 HadCM3L Eocene simulations from Farnsworth et al (2019). The second simulations are the x 4CO2 and 8x CO2 CCSM3 simulations of Huber and Caballero (2011), also discussed in Lunt et al (2012).…”

Section: Dsurf-2mentioning

confidence: 99%

“…The Fifth IPCC Assessment Report stated that GMST was 9°C to 14°C higher than for pre-industrial conditions during the early Eocene (~52 to 50 Ma) (Masson- Delmotte et al, 2014). Subsequent studies indicate a wider range of estimates, from 9 to 23°C warmer than pre-industrial (Cramwinckel et al, 2018;Farnsworth et al, 2019;Hansen et al, 2013;Zhu et al, 2019;Caballero and Huber, 2013) ( Figure 1). It is an open question whether this range arises from inconsistencies between the methods used to estimate GMST, such as selection of proxy datasets, treatment of uncertainty, and/ analysis of different time intervals.…”

Section: Introductionmentioning

confidence: 97%

“…Sea surface temperature (SST) and land air temperature (LAT) proxies indicate that the latest Paleocene and early Eocene were characterised by global mean surface temperatures (GMST) much warmer than those of today (Cramwinckel et al, 2018;Farnsworth et al, 2019;Hansen et al, 2013;Zhu et al, 2019;Caballero and Huber, 2013). Having a robust quantitative estimate of the magnitude of warming relative to modern is useful for two primary reasons: (1) it allows us to contextualise future climate change predictions by comparing the magnitude of future anthropogenic warming with the magnitude of past natural warming; (2) combined with CO2 proxy data, it allows us to estimate climate sensitivity, a key metric for understanding how the climate system responds to CO2 forcing.…”

Section: Introductionmentioning

confidence: 99%

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Global mean surface temperature and climate sensitivity of the EECO, PETM and latest Paleocene

Inglis¹,

Bragg²,

Burls³

et al. 2019

Preprint

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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 during the geological record. GMST estimates from 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. Here, we develop a multi-method experimental framework to calculate GMST during three target intervals: 1) the latest Paleocene (~57 Ma), 2) the Paleocene-Eocene Thermal Maximum (56 Ma) and 3) the early Eocene Climatic Optimum (EECO; 49.4 to 53.3 Ma). Using six independent methodologies, we find that average GMST estimates during the latest Paleocene and PETM are 11.7°C (± 0.6°C) and 18.7°C (± 0.8°C) higher than pre-industrial, respectively. GMST estimates from the EECO are 13.3°C (±0.5°C) warmer than pre-industrial and comparable to previous IPCC AR5 estimates (12.7°C higher than pre-industrial). Leveraging the extremely large ‘signal’ associated with these extreme warm climates, we combine estimates of GMST and CO2 from the latest Paleocene, PETM and EECO to calculate a gross estimate of the average climate sensitivity between the early Paleogene and today. This yields gross climate sensitivity estimates for the latest Paleocene, PETM and EECO which range between 2.8 to 4.8°C (66% confidence). These largely fall within the range predicted by the IPCC (1.5 to 4.5°C per doubling CO2), but appear incompatible with low values (between 1.5 and 2.8°C per doubling CO2).

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Climate Sensitivity on Geological Timescales Controlled by Nonlinear Feedbacks and Ocean Circulation

Cited by 120 publications

References 54 publications

DeepMIP: Model intercomparison of early Eocene climatic optimum (EECO) large-scale climate features and comparison with proxy data

DeepMIP: Model intercomparison of early Eocene climatic optimum (EECO) large-scale climate features and comparison with proxy data

Changes in the high-latitude Southern Hemisphere through the Eocene–Oligocene transition: a model–data comparison

Global mean surface temperature and climate sensitivity of the EECO, PETM and latest Paleocene

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