An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3
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Published:2021-08-17
Issue:8
Volume:14
Page:5107-5124
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Phipps Steven J.ORCID, Roberts Jason L., King Matt A.ORCID
Abstract
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 any simple 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.
Funder
Australian Research Council
Publisher
Copernicus GmbH
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