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Cited by 89Climate variability and modelsMeteorological Phenomena and SimulationsAtmospheric aerosols and clouds

Tuning the MPI‐ESM1.2 Global Climate Model to Improve the Match With Instrumental Record Warming by Lowering Its Climate Sensitivity

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Mauritsen, Thorsten, Roeckner, Erich·2020·Journal of Advances in Modeling Earth Systems
DOI 10.1029/2019ms002037PMC PMC7375142
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Abstract

A climate model's ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons it cannot be considered a purely empirical result of the modeling efforts because the desired result is known in advance and so is a potential target of tuning. Here we report how the latest edition of the Max Planck Institute for Meteorology Earth System Models (MPI‐ESM1.2) atmospheric component (ECHAM6.3) had its sensitivity systematically tuned in order to improve the modeled match with the instrumental record. In practice, this was done by targeting an equilibrium climate sensitivity of about 3 K, slightly lower than in the previous model generation (MPI‐ESM), which warmed more than observed, and in particular by addressing a climate sensitivity of about 7 K in an intermediate version of the model. In the process we identified several controls on cloud feedback, some of which confirm recently proposed hypotheses. We find the model exhibits excellent fidelity with the observed centennial global warming. We further find that an alternative approach with high climate sensitivity compensated by strong aerosol cooling instead would yield colder than observed results in the second half of the twentieth century.

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  • Some modeling teams provide simulations that target a given value of ECS to the CMIP database, calling into question any method that uses CMIP as a starting point for spanning ECS uncertainty.

    “Some modeling teams even provide simulations that target a given value of the ECS to the CMIP database (42) (calling into question any method that uses CMIP as a starting point for spanning ECS uncertainty).”

    From Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections (2023) · cites this paper as [42]

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Authors
Mauritsen, T., & Roeckner, E.
Affiliations
  • Stockholm University (SE)
  • Max Planck Institute for Meteorology (DE)
Corresponding author
Mauritsen, Thorsten
ORCID
Mauritsen, Thorsten
Venue
Journal of Advances in Modeling Earth Systems
Publisher
American Geophysical Union (AGU)
Published
2020-05
Volume
12
Issue
5
Pages
e2019MS002037-e2019MS002037
ISSN
1942-2466 (ISSN-L)
DOI
10.1029/2019ms002037
PMC
PMC7375142
OpenAlex
W3018941750
Cited by
89
References
42
Citations by year
2026: 10 · 2025: 8 · 2024: 12 · 2023: 8 · 2022: 14 · 2021: 22 · 2020: 2 · 2019: 2 · 2018: 3 · 2017: 2 · 2016: 5 · 2015: 1
FWCI
4.28
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Advances in Modeling Earth Systems (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
Funders
Seventh Framework Programme (770765, 820829)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
Keywords
MPI-ESM1.2, climate sensitivity, model calibration, instrumental temperature records, cloud feedback, aerosol cooling, equilibrium climate sensitivity, global warming

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