The art and science of climate model tuning
Bulletin of the American Meteorological Society
American Meteorological Society
© 2017 American Meteorological Society.
Reason for embargo
We survey the rationale and diversity of approaches for tuning, a fundamental aspect of climate modeling which should be more systematically documented and taken into account in multi-model analysis. 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 sub-models. Most sub-models 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.
The authors would like to thank the World Climate Research Program and its Working Group on Coupled Modeling for initiating and helping organize the workshop on model tuning in October 2014 in Garmisch-Partenkirchen, Germany. Work at LLNL was performed under the auspices the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract No. DE-AC52-07NA27344. The National Center for Atmospheric Research is sup- ported by the U.S. National Science Foundation. The contribution of Yun Qian was supported by the U.S. Department of Energy’s Office of Science as part of the Earth System Modeling Program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830
This is the final version of the article. Available from American Meteorological Society via the DOI in this record.
Vol. 98, No. 3
- Mathematics