Simple fuzzy logic models to estimate the global temperature change due to GHG emissions

Carlos Gay-García, Oscar Sánchez Meneses, Benjamín Martínez-López, Àngela Nebot, Francisco Estrada

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Future scenarios (through 2100) developed by the Intergovernmental Panel on Climate Change (IPCC) indicate a wide range of concentrations of greenhouse gases (GHG) and aerosols, and the corresponding range of temperatures. These data, allow inferring that higher temperature increases are directly related to higher emission levels of GHG and to the increase in their atmospheric concentrations. It is evident that lower temperature increases are related to smaller amounts of emissions and, to lower GHG concentrations. In this work, simple linguistic rules are extracted from results obtained through the use of simple linear scenarios of emissions of GHG in the Magicc model. These rules describe the relations between the GHG, their concentrations, the radiative forcing associated with these concentrations, and the corresponding temperature changes. These rules are used to build a fuzzy model, which uses concentration values of GHG as input variables and gives, as output, the temperature increase projected for year 2100. A second fuzzy model is presented on the temperature increases obtained from the same model but including a second source of uncertainty: climate sensitivity. Both models are very attractive because their simplicity and capability to integrate the uncertainties to the input (emissions, sensitivity) and the output (temperature).

Original languageEnglish
Title of host publicationSIMULTECH 2012 - Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications
Pages518-526
Number of pages9
Publication statusPublished - 2012
Event2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012 - Rome, Italy
Duration: 28 Jul 201231 Jul 2012

Conference

Conference2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012
CountryItaly
CityRome
Period28/07/1231/07/12

Keywords

  • Fuzzy inference models
  • Global climate change
  • Greenhouse gases future scenarios

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