The Art and Science of Climate Model Tuning
Open accessAbstract
The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. We discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.
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Objective methods such as history matching cannot replace the expertise and subjectivity inherent to the tuning process.
“This underlines that objective methods such as history matching cannot and should not replace the expertise and subjectivity inherent to the tuning process (23).”
From Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections (2023) · cites this paper as [23]
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- Authors
- Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan, Q., Folini, D., Ji, D., Klocke, D., Qian, Y., Rauser, F., Rio, C., Tomassini, L., Watanabe, M., & Williamson, D.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Max Planck Institute for Meteorology (DE)
- NSF National Center for Atmospheric Research (US)
- NOAA Geophysical Fluid Dynamics Laboratory (US)
- Princeton University (US)
- Beijing Normal University (CN)
- ETH Zurich (CH)
- Deutscher Wetterdienst (DE)
- Pacific Northwest National Laboratory (US)
- The University of Tokyo (JP)
- University of Exeter (GB)
- ORCID
- Venue
- Bulletin of the American Meteorological Society
- Publisher
- American Meteorological Society
- Published
- 2017-03-01
- Volume
- 98
- Issue
- 3
- Pages
- 589-602
- ISSN
- 0003-0007 (ISSN-L)
- 1520-0477
- OpenAlex
- W2495412896
- Cited by
- 611
- References
- 4
- Citations by year
- 2026: 30 · 2025: 62 · 2024: 62 · 2023: 78 · 2022: 90 · 2021: 78 · 2020: 80 · 2019: 49 · 2018: 51 · 2017: 26 · 2016: 4
- FWCI
- 32.13
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Bulletin of the American Meteorological Society (publishedVersion)
- Open Research Exeter (University of Exeter) (publishedVersion)
- NOAA Institutional Repository (submittedVersion, other-oa)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- Figshare (submittedVersion)
- Funders
- National Science Foundation (DE-AC52-07-NA27344, DEAC05–76RL01830, 76RL01830)
- U.S. Department of Energy (DE-AC05–76RL01830, DEAC5207NA27344, AC52‐07NA27344, 76RL01830, AC05-76RL01830, DE-AC05?, Contract DE-AC05-76RL01830)
- Battelle (AC05-76RL01830, DE- AC05-76RL01830, DE-AC05, DE-AC52-07NA27344)
- National Center for Atmospheric Research
- Agence Nationale de la Recherche (ANR-10-LABX-0018)
- Office of Science (DE-AC52-07NA27344, DE‐AC05‐76 RL01830)
- Engineering and Physical Sciences Research Council (EP/K019112/1)
- Japan Society for the Promotion of Science (26247079)
- Lawrence Livermore National Laboratory (DE‐AC5207NA27344, DE-AC05-76RL01830, AC52-07NA27344)
- Pacific Northwest National Laboratory (DEAC0576RL01830, 76RL01830, DE-AC52-07NA27344)
- 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 › Climate Change and Geoengineering
- Keywords
- climate model tuning, parameter estimation, parameter uncertainty, climate sensitivity, model optimization, climate change projections, model validation against observations
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