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Climate of the Past An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/cp-2020-86
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-2020-86
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Jul 2020

17 Jul 2020

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This preprint is currently under review for the journal CP.

LGM climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity

Jiang Zhu1 and Christopher J. Poulsen2 Jiang Zhu and Christopher J. Poulsen
  • 1Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO 80305, USA
  • 2Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48109, USA

Abstract. Equilibrium climate sensitivity (ECS) has been directly estimated using reconstructions of past climates that are different than today’s. A challenge to this approach is that temperature proxies integrate over the timescales of the fast feedback processes (e.g. changes in water vapor, snow, and clouds) that are captured in ECS as well as the slower feedback processes (e.g. changes in ice sheets and ocean circulation) that are not. A way around this issue is to treat the slow feedbacks as climate forcings and independently account for their impact on global temperature. Here we conduct a suite of Last Glacial Maximum (LGM) simulations using the Community Earth System Model version 1.2 (CESM1.2) to quantify the forcing and efficacy of land ice sheets (LIS) and greenhouse gases (GHG) in order to estimate ECS. Our forcing and efficacy quantification adopts the effective radiative forcing (ERF) and adjustment framework and provides a complete accounting for the radiative, topographic, and dynamical impacts of LIS on surface temperatures. ERF and efficacy of LGM LIS are −3.2 W m−2 and 1.1, respectively. The larger-than-unity efficacy is caused by the relatively larger temperature changes over land and the Northern Hemisphere subtropical oceans than those in response to a doubling of atmospheric CO2. The subtropical SST response is linked to LIS-induced wind changes and feedbacks in ocean-atmosphere coupling and clouds. ERF and efficacy of LGM GHG are −2.8 W m−2 and 0.9, respectively. The lower efficacy is primarily attributed to a smaller cloud feedback at colder temperatures. Our simulations further demonstrate that the direct ECS calculation using the forcing, efficacy, and temperature response in CESM1.2 overestimates the true value in the model by 25 % due to the neglect of slow ocean dynamical feedback. This is supported by the greater cooling (6.8 °C) in a fully coupled LGM simulation than that (5.3 °C) in a slab ocean model simulation with ocean dynamics disabled. The majority (67 %) of the ocean dynamical feedback is attributed to dynamical changes in the Southern Ocean, where interactions between ocean stratification, heat transport, and sea-ice cover are found to amplify the LGM cooling. Our study demonstrates the value of climate models in the quantification of climate forcings and the ocean dynamical feedback, which is necessary for an accurate direct ECS estimation.

Jiang Zhu and Christopher J. Poulsen

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Jiang Zhu and Christopher J. Poulsen

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Latest update: 05 Aug 2020
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Short summary
Climate sensitivity has been directly calculated from paleoclimate data. This approach relies on good understandings of climate forcings and interactions within the Earth system. We conduct Last Glacial Maximum simulations using a climate model to quantify the forcing and efficacy of ice sheets and greenhouse gases and to directly estimate climate sensitivity in the model. Results suggest that the direct calculation overestimates the truth by 25 % due to the neglect of ocean dynamical feedback.
Climate sensitivity has been directly calculated from paleoclimate data. This approach relies on...
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