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An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3
Citation
Phipps, SJ and Roberts, JL and King, MA, An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3, Geoscientific Model Development, 14, (8) pp. 5107-5124. ISSN 1991-959X (2021) [Refereed Article]
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Copyright 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/)
DOI: doi:10.5194/gmd-14-5107-2021
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.
Item Details
Item Type: | Refereed Article |
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Keywords: | model optimisation, ice sheet model |
Research Division: | Earth Sciences |
Research Group: | Physical geography and environmental geoscience |
Research Field: | Glaciology |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in the earth sciences |
UTAS Author: | Phipps, SJ (Dr Steven Phipps) |
UTAS Author: | King, MA (Professor Matt King) |
ID Code: | 146031 |
Year Published: | 2021 |
Deposited By: | Geography and Spatial Science |
Deposited On: | 2021-08-18 |
Last Modified: | 2021-09-03 |
Downloads: | 10 View Download Statistics |
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