Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates

The best estimate of equilibrium climate sensitivity (ECS) constrained based on the instrumental record of historical warming becomes coherent with other lines of evidence when the dependence of radiative feedback on the pattern of surface temperature change (pattern effect) is incorporated. Pattern...

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Main Authors: Modak, Angshuman, Mauritsen, Thorsten
Format: Text
Language:English
Published: 2023
Subjects:
Online Access:https://doi.org/10.5194/egusphere-2022-976
https://egusphere.copernicus.org/preprints/2022/egusphere-2022-976/
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spelling ftcopernicus:oai:publications.copernicus.org:egusphere106661 2023-07-30T04:06:47+02:00 Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates Modak, Angshuman Mauritsen, Thorsten 2023-07-11 application/pdf https://doi.org/10.5194/egusphere-2022-976 https://egusphere.copernicus.org/preprints/2022/egusphere-2022-976/ eng eng doi:10.5194/egusphere-2022-976 https://egusphere.copernicus.org/preprints/2022/egusphere-2022-976/ eISSN: Text 2023 ftcopernicus https://doi.org/10.5194/egusphere-2022-976 2023-07-17T16:24:20Z The best estimate of equilibrium climate sensitivity (ECS) constrained based on the instrumental record of historical warming becomes coherent with other lines of evidence when the dependence of radiative feedback on the pattern of surface temperature change (pattern effect) is incorporated. Pattern effect strength is usually estimated with atmosphere-only model simulations forced with observed historical sea-surface temperature (SST) and sea-ice change and constant pre-industrial forcing. However, recent studies indicate that pattern effect estimates depend on the choice of SST boundary condition dataset, due to differences in the measurement sources and the techniques used to merge and construct them. Here, we systematically explore this dataset dependency by applying seven different observed SST datasets to the MPI-ESM1.2-LR model covering 1871–2017. We find that the pattern effect ranges from - 0.01 ± 0.09 <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="64pt" height="10pt" class="svg-formula" dspmath="mathimg" md5hash="777cc679781f35d6dc1f625b1f7bf436"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-7535-2023-ie00001.svg" width="64pt" height="10pt" src="acp-23-7535-2023-ie00001.png"/></svg:svg> to 0.42±0.10 W m −2 K −1 (standard error), whereby the commonly used Atmospheric Model Intercomparison Project II (AMIPII) dataset produces by far the largest estimate. When accounting for the generally weaker pattern effect in MPI-ESM1.2-LR compared to other models, as well as dataset dependency and intermodel spread, we obtain a combined pattern effect estimate of 0.37 W m −2 K −1 [ −0.14 to 0.88 W m −2 K −1 ] (5th–95th percentiles) and a resulting instrumental record ECS estimate of 3.2 K [1.8 to 11.0 K], which as a result of the weaker pattern effect is slightly lower and better constrained than in previous studies. Text Sea ice Copernicus Publications: E-Journals
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description The best estimate of equilibrium climate sensitivity (ECS) constrained based on the instrumental record of historical warming becomes coherent with other lines of evidence when the dependence of radiative feedback on the pattern of surface temperature change (pattern effect) is incorporated. Pattern effect strength is usually estimated with atmosphere-only model simulations forced with observed historical sea-surface temperature (SST) and sea-ice change and constant pre-industrial forcing. However, recent studies indicate that pattern effect estimates depend on the choice of SST boundary condition dataset, due to differences in the measurement sources and the techniques used to merge and construct them. Here, we systematically explore this dataset dependency by applying seven different observed SST datasets to the MPI-ESM1.2-LR model covering 1871–2017. We find that the pattern effect ranges from - 0.01 ± 0.09 <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="64pt" height="10pt" class="svg-formula" dspmath="mathimg" md5hash="777cc679781f35d6dc1f625b1f7bf436"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-7535-2023-ie00001.svg" width="64pt" height="10pt" src="acp-23-7535-2023-ie00001.png"/></svg:svg> to 0.42±0.10 W m −2 K −1 (standard error), whereby the commonly used Atmospheric Model Intercomparison Project II (AMIPII) dataset produces by far the largest estimate. When accounting for the generally weaker pattern effect in MPI-ESM1.2-LR compared to other models, as well as dataset dependency and intermodel spread, we obtain a combined pattern effect estimate of 0.37 W m −2 K −1 [ −0.14 to 0.88 W m −2 K −1 ] (5th–95th percentiles) and a resulting instrumental record ECS estimate of 3.2 K [1.8 to 11.0 K], which as a result of the weaker pattern effect is slightly lower and better constrained than in previous studies.
format Text
author Modak, Angshuman
Mauritsen, Thorsten
spellingShingle Modak, Angshuman
Mauritsen, Thorsten
Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
author_facet Modak, Angshuman
Mauritsen, Thorsten
author_sort Modak, Angshuman
title Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
title_short Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
title_full Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
title_fullStr Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
title_full_unstemmed Better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
title_sort better constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates
publishDate 2023
url https://doi.org/10.5194/egusphere-2022-976
https://egusphere.copernicus.org/preprints/2022/egusphere-2022-976/
genre Sea ice
genre_facet Sea ice
op_source eISSN:
op_relation doi:10.5194/egusphere-2022-976
https://egusphere.copernicus.org/preprints/2022/egusphere-2022-976/
op_doi https://doi.org/10.5194/egusphere-2022-976
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