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- Title
Global Sensitivity Analysis of Parameters in the ENSO model Based on Sobol’ Method.
- Authors
Xiaoqun Cao; ShiPeng Su; HongZe Leng; BaiNian Liu
- Abstract
In this work, a global sensitivity analysis (GSA) is performed on physical parameters and initial values of a nonlinear El Niño Southern Oscillation (ENSO) model, to determine the influential parameters at different prediction times. The anomaly of sea surface temperature (SST) at each prediction time is viewed as the response quantity of interest in the sensitivity analysis by Sobol’ method. And the Latin Hypercube Sampling technique is applied to all input parameters. Then, the first-order sensitivity indexes (FSI) and total sensitivity indexes (TSI) of physical parameters and initial values are calculated, respectively. The results of numerical simulations show that the proposed method is very effective and feasible for sensitivity analysis of nonlinear ENSO model. It is concluded that the sensitive parameters and relative ranking vary considerably at different prediction times. In the beginning period, initial values of the model have a great influence on the SST anomaly forecast, while for the long-term prediction, physical coefficients become main sensitive parameters, and the initial values have little effect on the output variable. In addition, the interaction between input parameters in the model increases with forecast time, which is indicated by that the difference between the TSI and FSI of each parameter becomes larger.
- Subjects
GLOBAL analysis (Mathematics); SENSITIVITY analysis; EL Nino; LATIN hypercube sampling; OCEAN temperature; SOUTHERN oscillation
- Publication
Journal of Coastal Research, 2020, Vol 99, p340
- ISSN
0749-0208
- Publication type
Article
- DOI
10.2112/SI99-047.1