Global Temperature Fuzzy Model as a Function of Carbon Emissions - A Fuzzy ‘Regression’ from Historical Data

Carlos G. Gay, Bernardo O. Bastien

Abstract

There are several models that correlate global mean temperature with Carbon emissions using statistical analysis; in this study we approach the problem using fuzzy logic analysis and inference systems, which is a pioneer method in climate modelling. The process in which anthropogenic activity affects the atmospheric Carbon and therefore the global mean temperature, has been well studied but there are still a lot of unknown factors that play an important role in the process, e.g. punctual Carbon sequestration processes, economyled emissions’ fluctuations, etcetera. That way the process take no clear path and is when fuzzy logic is ideal to approach the system understanding. In this study a Fuzzy Inference System is developed, which model the problem using historical data from 1959 to present. Our model has good results quite comparable with statistical models and it can be used to project the future global mean temperature. The model was developed using SIMULINK extension from matlab.

References

  1. Shefter, M., Brovkin, V., Cox, P., 2006. Positive Feedback between global warming and atmospheric CO2 concentration inferred from past climate change. Geophysical Journey. V33.
  2. Kauffman R., Kauppi, H., Stock, J., 2006. Emissions, concentrations & temperature: a time series analysis. Climate Change 77:249-278. Springer.
  3. Tans, P., 2014. Atmospheric CO2, Mauna Loa Observatory, NOAA, www.esrl.noaa.gov/gmd/ccgg/ trends.
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Paper Citation


in Harvard Style

Gay C. and Bastien B. (2014). Global Temperature Fuzzy Model as a Function of Carbon Emissions - A Fuzzy ‘Regression’ from Historical Data . In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCEC, (SIMULTECH 2014) ISBN 978-989-758-038-3, pages 818-821. DOI: 10.5220/0005123208180821


in Bibtex Style

@conference{msccec14,
author={Carlos G. Gay and Bernardo O. Bastien},
title={Global Temperature Fuzzy Model as a Function of Carbon Emissions - A Fuzzy ‘Regression’ from Historical Data},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCEC, (SIMULTECH 2014)},
year={2014},
pages={818-821},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005123208180821},
isbn={978-989-758-038-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: MSCCEC, (SIMULTECH 2014)
TI - Global Temperature Fuzzy Model as a Function of Carbon Emissions - A Fuzzy ‘Regression’ from Historical Data
SN - 978-989-758-038-3
AU - Gay C.
AU - Bastien B.
PY - 2014
SP - 818
EP - 821
DO - 10.5220/0005123208180821