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Abstract
When simulating past warm climates, such as the early Cretaceous and Paleogene periods, general circulation models (GCMs) underestimate the magnitude of warming in the Arctic. Additionally, model intercomparisons show a large spread in the magnitude of Arctic warming for these warmer-than-modern climates. Several mechanisms have been proposed to explain these disagreements, including the unrealistic representation of polar clouds or underestimated poleward heat transport in the models. This study provides an intercomparison of Arctic cloud and atmospheric heat transport (AHT) responses to strong imposed polar-amplified surface ocean warming across four atmosphere-only GCMs. All models simulate an increase in high clouds throughout the year; the resulting reduction in longwave radiation loss to space acts to support the imposed Arctic warming. The response of low- and midlevel clouds varies considerably across the models, with models responding differently to surface warming and sea ice removal. The AHT is consistently weaker in the imposed warming experiments due to a large reduction in dry static energy transport that offsets a smaller increase in latent heat transport, thereby opposing the imposed surface warming. Our idealized polar amplification experiments require very large increases in implied ocean heat transport (OHT) to maintain steady state. Increased CO2 or tropical temperatures that likely characterized past warm climates reduce the need for such large OHT increases.
Original language | English |
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Pages (from-to) | 5723-5740 |
Number of pages | 18 |
Journal | Journal of Climate |
Volume | 34 |
Issue number | 14 |
DOIs | |
Publication status | Published - 15 Jun 2021 |
Bibliographical note
Funding Information:Acknowledgments. The authors acknowledge the support from the Australian Research Council Centre of Excellence (CE170100023). DD acknowledges the support from the Australian Government Research Training Program Scholarship and appreciates the ACCESS and HadAM3 modelling groups for making their simulations available for this analysis. DD thanks Vishal Dixit, Abhnil Prasad, Zoe Gillett, Jithendra Raju, and all the coauthors for useful discussions during the course of this study. SCS acknowledges ARC Grant FL150100035. KJM acknowledges ARC Grant DP180100048. DJL acknowledges NERC Grant NE/P01903X/1. DJL and GT acknowledge support from ERC Grant 340923 (TGRES, awarded to Rich Pancost). SN and RC acknowledge the support of the Australian Government’s National Environmental Science Programme. Computational resources were provided by the NCI National Facility at the Australian National University, through awards under the Merit Allocation Scheme, the Intersect Allocation Scheme, and the UNSW HPC at NCI Scheme.
Publisher Copyright:
2021 American Meteorological Society
Keywords
- Arctic
- Atmosphere
- Climate sensitivity
- Clouds
- Heat budgets/fluxes
- Paleoclimate
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HPC (High Performance Computing) and HTC (High Throughput Computing) Facilities
Sadaf R Alam (Manager), Steven A Chapman (Manager), Polly E Eccleston (Other), Simon H Atack (Other) & D A G Williams (Manager)
Facility/equipment: Facility