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Volume 9, Issue 3, June 2020, Page: 96-101
Parametric Sensitivity Analysis of a Mathematical Model of the Effect of CO2 on the Climate Change
Bazuaye Frank Etin-Osa, Department of Mathematics and Statistics, University of Port Harcourt, Port Harcourt, Nigeria
Ijomah Maxwell Azubike, Department of Mathematics and Statistics, University of Port Harcourt, Port Harcourt, Nigeria
Received: Oct. 3, 2019;       Accepted: May 26, 2020;       Published: Jun. 8, 2020
DOI: 10.11648/j.acm.20200903.16      View  328      Downloads  98
Mathematical modeling is a very powerful tool for the study and understanding of the climate system. Modern climate models used in different applications are derived from a set of many-dimensional nonlinear differential equations in partial derivatives. The Climate models contain a wide number of model parameters that can describe external forcing that can strongly affect the behavior of the climate. It is imperative to estimate the influence of variations in parameters on climate change. The methods of 1-norm, 2-norm, and infinity-norm were used to quantify different forms of the sensitivity of model parameters. The approach applied in this research involves coding the given system of continuous non-linear first order ordinary differential equation in a Matlab solver, modifying and coding a similar program which is used for a variation of a single parameter one-at-a-time while other model parameters are fixed. Finally, the program is used to calculate the 1-norm, 2-norm, 3-norm and infinity norm of the solution trajectories in the same manner. The study shows that the most sensitivity parameters in the model are the concentration of a suitable absorbent and the rate of inflow of absorbent in the absorption chamber.
Sensitivity Analysis, Mathematical Model, Climate Change
To cite this article
Bazuaye Frank Etin-Osa, Ijomah Maxwell Azubike, Parametric Sensitivity Analysis of a Mathematical Model of the Effect of CO2 on the Climate Change, Applied and Computational Mathematics. Vol. 9, No. 3, 2020, pp. 96-101. doi: 10.11648/j.acm.20200903.16
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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