Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations

Climate feedbacks over the historical period (1850–2014) have been investigated in large ensembles of historical, hist-ghg, hist-aer, and hist-nat experiments, with 47 members for each experiment. Across the historical ensemble with all forcings, a range in estimated Effective Climate Sensitivity (E...

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Main Authors: Mutton, Harry, Andrews, Timothy, Hermanson, Leon, Seabrook, Melissa, Smith, Doug M, Ringer, Mark Adam, Webb, Mark J
Format: Other/Unknown Material
Language:unknown
Published: Authorea, Inc. 2024
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Online Access:http://dx.doi.org/10.22541/au.171111383.30680177/v1
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spelling crwinnower:10.22541/au.171111383.30680177/v1 2024-06-02T08:14:20+00:00 Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations Mutton, Harry Andrews, Timothy Hermanson, Leon Seabrook, Melissa Smith, Doug M Ringer, Mark Adam Webb, Mark J 2024 http://dx.doi.org/10.22541/au.171111383.30680177/v1 unknown Authorea, Inc. posted-content 2024 crwinnower https://doi.org/10.22541/au.171111383.30680177/v1 2024-05-07T14:19:29Z Climate feedbacks over the historical period (1850–2014) have been investigated in large ensembles of historical, hist-ghg, hist-aer, and hist-nat experiments, with 47 members for each experiment. Across the historical ensemble with all forcings, a range in estimated Effective Climate Sensitivity (EffCS) between approximately 3–6 K is found, a considerable spread stemming solely from initial condition uncertainty. The spread in EffCS is associated with varying Sea Surface Temperature (SST) patterns seen across the ensemble due to their influence on different feedback processes. For example, the level of polar amplification is shown to strongly control the amount of sea ice melt per degree of global warming. This mechanism is responsible for the large spread in shortwave clear-sky feedbacks and is the main contributor to the different forcing efficacies seen across the different forcing agents, although in HadGEM3-GC3.1-LL these differences in forcing efficacy are shown to be small. The spread in other feedbacks is also investigated, with the level of tropical SST warming shown to strongly control the longwave clear-sky feedbacks, and the local surface-air-temperatures and large scale tropospheric temperatures shown to influence cloud feedbacks. The metrics used to understand the spread in feedbacks can also help to explain the disparity between feedbacks seen in the historical experiment simulations and a more accurate modeled estimate of the feedbacks seen in the real world derived from an atmosphere-only experiment prescribed with observed SSTs (termed amip-piForcing). Other/Unknown Material Sea ice The Winnower
institution Open Polar
collection The Winnower
op_collection_id crwinnower
language unknown
description Climate feedbacks over the historical period (1850–2014) have been investigated in large ensembles of historical, hist-ghg, hist-aer, and hist-nat experiments, with 47 members for each experiment. Across the historical ensemble with all forcings, a range in estimated Effective Climate Sensitivity (EffCS) between approximately 3–6 K is found, a considerable spread stemming solely from initial condition uncertainty. The spread in EffCS is associated with varying Sea Surface Temperature (SST) patterns seen across the ensemble due to their influence on different feedback processes. For example, the level of polar amplification is shown to strongly control the amount of sea ice melt per degree of global warming. This mechanism is responsible for the large spread in shortwave clear-sky feedbacks and is the main contributor to the different forcing efficacies seen across the different forcing agents, although in HadGEM3-GC3.1-LL these differences in forcing efficacy are shown to be small. The spread in other feedbacks is also investigated, with the level of tropical SST warming shown to strongly control the longwave clear-sky feedbacks, and the local surface-air-temperatures and large scale tropospheric temperatures shown to influence cloud feedbacks. The metrics used to understand the spread in feedbacks can also help to explain the disparity between feedbacks seen in the historical experiment simulations and a more accurate modeled estimate of the feedbacks seen in the real world derived from an atmosphere-only experiment prescribed with observed SSTs (termed amip-piForcing).
format Other/Unknown Material
author Mutton, Harry
Andrews, Timothy
Hermanson, Leon
Seabrook, Melissa
Smith, Doug M
Ringer, Mark Adam
Webb, Mark J
spellingShingle Mutton, Harry
Andrews, Timothy
Hermanson, Leon
Seabrook, Melissa
Smith, Doug M
Ringer, Mark Adam
Webb, Mark J
Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations
author_facet Mutton, Harry
Andrews, Timothy
Hermanson, Leon
Seabrook, Melissa
Smith, Doug M
Ringer, Mark Adam
Webb, Mark J
author_sort Mutton, Harry
title Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations
title_short Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations
title_full Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations
title_fullStr Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations
title_full_unstemmed Feedbacks, Pattern Effects, and Efficacies in a Large Ensemble of HadGEM3-GC3.1-LL Historical Simulations
title_sort feedbacks, pattern effects, and efficacies in a large ensemble of hadgem3-gc3.1-ll historical simulations
publisher Authorea, Inc.
publishDate 2024
url http://dx.doi.org/10.22541/au.171111383.30680177/v1
genre Sea ice
genre_facet Sea ice
op_doi https://doi.org/10.22541/au.171111383.30680177/v1
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