146031 - An iterative process for efficient optimisation of parameters in geoscientific models.pdf (3.74 MB)
Download fileAn iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3
journal contribution
posted on 2023-05-21, 01:40 authored by Phipps, SJ, Roberts, JL, Matt KingMatt KingPhysical 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.
Funding
CSIRO-Commonwealth Scientific & Industrial Research Organisation
History
Publication title
Geoscientific Model DevelopmentVolume
14Issue
8Pagination
5107-5124ISSN
1991-959XDepartment/School
School of Geography, Planning and Spatial SciencesPublisher
Copernicus GmbHPlace of publication
GermanyRights statement
© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License (https://creativecommons.org/licenses/by/4.0/)Repository Status
- Open