Preprints
https://doi.org/10.5194/gmd-2020-382
https://doi.org/10.5194/gmd-2020-382

Submitted as: development and technical paper 30 Nov 2020

Submitted as: development and technical paper | 30 Nov 2020

Review status: this preprint is currently under review for the journal GMD.

An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3

Steven J. Phipps1,2, Jason L. Roberts3, and Matt A. King2 Steven J. Phipps et al.
  • 1Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
  • 2School of Technology, Environments and Design, University of Tasmania, Hobart, Tasmania, Australia
  • 3Australian Antarctic Division, Kingston, Tasmania, Australia

Abstract. Physical processes within geoscientific models are sometimes described by simplified schemes known as parameterisations. The values of the parameters within these schemes can be poorly constrained by theory or observation. Uncertainty in the parameter values translates into uncertainty in the outputs of the models. Proper quantification of the uncertainty in model predictions therefore requires a systematic approach for sampling parameter space. In this study, we develop a simple and efficient approach to identify regions of multi-dimensional parameter space that are consistent with observations. Using the Parallel Ice Sheet Model to simulate the present-day state of the Antarctic Ice Sheet, we find that co-dependencies between parameters preclude the identification of a single optimal set of parameter values. Approaches such as large ensemble modelling are therefore required in order to generate model predictions that incorporate proper quantification of the uncertainty arising from the parameterisation of physical processes.

Steven J. Phipps et al.

Data sets

An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3 Steven J. Phipps, Jason L. Roberts, and Matt A. King https://doi.org/10.5281/zenodo.4275053

Model code and software

An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3 Steven J. Phipps, Jason L. Roberts, and Matt A. King https://doi.org/10.5281/zenodo.4275053

Steven J. Phipps et al.

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Short summary
Simplified schemes, known as parameterisations, are sometimes used to describe physical processes within numerical models. However, the values of the parameters are uncertain. This introduces uncertainty into the model outputs. We develop a simple approach to identify plausible ranges for model parameters. Using a model of the Antarctic Ice Sheet, we find that the value of one parameter can depend on the values of others. We conclude that a single optimal set of parameter values does not exist.