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Title: The Art and Science of Climate Model Tuning

Abstract

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. Here, we discuss how tuning methodologies may affect fundamental results of climate models, suchmore » as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [6];  [8];  [9];  [2];  [1];  [2];  [10];  [11]
  1. Lab. de Meteorologie Dynamique, Paris (France)
  2. Max Planck Institute for Meteorology, Hamburg (Germany)
  3. National Center for Atmospheric Research, Boulder, CO (United States)
  4. National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Lab., Princeton, NJ (United States)
  5. Princeton Univ., Princeton, NJ (United States)
  6. Beijing Normal Univ., Beijing (China)
  7. Eidgenossische Technische Hochschule, Zurich (Switzerland)
  8. Deutscher Wetterdienst, Offenbach (Germany)
  9. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  10. Univ. of Tokyo, Tokyo (Japan)
  11. Univ. of Exeter, Exeter (United Kingdom)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1366951
Report Number(s):
LLNL-JRNL-680477
Journal ID: ISSN 0003-0007
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Bulletin of the American Meteorological Society
Additional Journal Information:
Journal Volume: 98; Journal Issue: 3; Journal ID: ISSN 0003-0007
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

Hourdin, Frederic, Mauritsen, Thorsten, Gettelman, Andrew, Golaz, Jean -Christophe, Balaji, Venkatramani, Duan, Qingyun, Folini, Doris, Ji, Duoying, Klocke, Daniel, Qian, Yun, Rauser, Florian, Rio, Catherine, Tomassini, Lorenzo, Watanabe, Masahiro, and Williamson, Daniel. The Art and Science of Climate Model Tuning. United States: N. p., 2017. Web. doi:10.1175/BAMS-D-15-00135.1.
Hourdin, Frederic, Mauritsen, Thorsten, Gettelman, Andrew, Golaz, Jean -Christophe, Balaji, Venkatramani, Duan, Qingyun, Folini, Doris, Ji, Duoying, Klocke, Daniel, Qian, Yun, Rauser, Florian, Rio, Catherine, Tomassini, Lorenzo, Watanabe, Masahiro, & Williamson, Daniel. The Art and Science of Climate Model Tuning. United States. doi:10.1175/BAMS-D-15-00135.1.
Hourdin, Frederic, Mauritsen, Thorsten, Gettelman, Andrew, Golaz, Jean -Christophe, Balaji, Venkatramani, Duan, Qingyun, Folini, Doris, Ji, Duoying, Klocke, Daniel, Qian, Yun, Rauser, Florian, Rio, Catherine, Tomassini, Lorenzo, Watanabe, Masahiro, and Williamson, Daniel. Fri . "The Art and Science of Climate Model Tuning". United States. doi:10.1175/BAMS-D-15-00135.1. https://www.osti.gov/servlets/purl/1366951.
@article{osti_1366951,
title = {The Art and Science of Climate Model Tuning},
author = {Hourdin, Frederic and Mauritsen, Thorsten and Gettelman, Andrew and Golaz, Jean -Christophe and Balaji, Venkatramani and Duan, Qingyun and Folini, Doris and Ji, Duoying and Klocke, Daniel and Qian, Yun and Rauser, Florian and Rio, Catherine and Tomassini, Lorenzo and Watanabe, Masahiro and Williamson, Daniel},
abstractNote = {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. Here, 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.},
doi = {10.1175/BAMS-D-15-00135.1},
journal = {Bulletin of the American Meteorological Society},
number = 3,
volume = 98,
place = {United States},
year = {Fri Mar 31 00:00:00 EDT 2017},
month = {Fri Mar 31 00:00:00 EDT 2017}
}

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