QuadTune version 1: a regional tuner for global atmospheric models

Abstract. When a new, better-formulated physical parameterization is introduced into a global atmospheric model, aspects of the global model solutions are sometimes degraded. Then, in order to use the new global model to address science questions, there is an incentive to restore its accuracy. Oftentimes this restoration is achieved by tuning of model parameter values. Unfortunately, the retuning process is expensive because characterizing the parameter dependence requires numerous time-consuming global simulations. To reduce the cost of tuning, this manuscript introduces a “poor man's” model tuner, “QuadTune”. QuadTune carves the globe into regions and approximates the model parameter dependence through the use of an uncorrelated quadratic emulator (i.e., response surface). The simplicity of the emulator reduces the required number of global model simulations and aids explainability of tuner behavior. Tuning removes parametric error but leaves behind model structural error. Structural error manifests itself as regional residual biases, such as stubborn biases and tuning trade-offs. To visualize these residual biases, QuadTune's software includes a set of diagnostic plots. This paper illustrates the use of the plots for characterizing residual biases with an example tuning problem.

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Publication Details

Journal
Geoscientific model development
Published
2025-12-09
DOI
https://doi.org/10.5194/gmd-18-9767-2025
Primary Topic
Meteorological Phenomena and Simulations
Type
article
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article

QuadTune version 1: a regional tuner for global atmospheric models

Benjamin A. Stephens, Yun Qian, Shaocheng Xie, Vincent E. Larson et al.
Geoscientific model development
Meteorological Phenomena and Simulations
article

QuadTune version 1: a regional tuner for global atmospheric models

Benjamin A. Stephens, Yun Qian, Shaocheng Xie, Vincent E. Larson, Colin M. Zarzycki, Gerhard Dikta, Zhun Guo
article en

Abstract

Abstract. When a new, better-formulated physical parameterization is introduced into a global atmospheric model, aspects of the global model solutions are sometimes degraded. Then, in order to use the new global model to address science questions, there is an incentive to restore its accuracy. Oftentimes this restoration is achieved by tuning of model parameter values. Unfortunately, the retuning process is expensive because characterizing the parameter dependence requires numerous time-consuming global simulations. To reduce the cost of tuning, this manuscript introduces a “poor man's” model tuner, “QuadTune”. QuadTune carves the globe into regions and approximates the model parameter dependence through the use of an uncorrelated quadratic emulator (i.e., response surface). The simplicity of the emulator reduces the required number of global model simulations and aids explainability of tuner behavior. Tuning removes parametric error but leaves behind model structural error. Structural error manifests itself as regional residual biases, such as stubborn biases and tuning trade-offs. To visualize these residual biases, QuadTune's software includes a set of diagnostic plots. This paper illustrates the use of the plots for characterizing residual biases with an example tuning problem.

Geoscientific model developmentVol. 18(23)
NSF National Center for Atmospheric Research (US), Lawrence Livermore National Laboratory (US), Pennsylvania State University (US), Pacific Northwest National Laboratory (US), Institute of Atmospheric Physics (CN), University of Wisconsin–Milwaukee (US), FH Aachen (DE)
Openalex Percentile: Top 57%
Meteorological Phenomena and Simulations
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