On Bayesian Spatio-Temporal Modeling of Oceanographic Climate Characteristics
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Bhattacharjee, Madhuchhanda, and Snigdhansu Chatterjee. “On Bayesian Spatio-Temporal Modeling of Oceanographic Climate Characteristics.” In Current Trends in Bayesian Methodology with Applications. Chapman and Hall/CRC, 2015. https://www.taylorfrancis.com/chapters/edit/10.1201/b18502-12/bayesian-spatio-temporal-modeling-oceanographic-climate-characteristics-madhuchhanda-bhattacharjee-snigdhansu-chatterjee
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It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
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Abstract
Recent change in the planet’s climate conditions is a matter of great concern, owing to its potential devastating effects for all life forms. A thorough study of climate variables should inform us about possible patterns of the climate of this planet, which further goes on to inform and guide policy decisions relating to adaptation and mitigation strategies to counter climate change, better management of resources, risk management, and for a better quality of life for all. Many of these aspects relate to extremes as well as typical values of climate variables. Consequently, it is of interest to obtain the joint distribution of the several climate variables. Owing to the complex dependence patterns possible in such joint distributions, a Bayesian modeling of the data is needed. Moreover, using Bayesian methodologies in the climate field also allows for systematic, coherent and simple treatment of Physics-driven known relations and constraints, combining multiple sources of data of varying size, dimensions and precision.