Fuzzy models: Easier to understand and an easier way to handle uncertainties in climate change research

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

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

Abstract

Greenhouse gas emission scenarios (through 2100) developed by the Intergovernmental Panel on Climate Change when converted to concentrations and atmospheric temperatures through the use of climate models result in a wide range of concentrations and temperatures with a rather simple interpretation: the higher the emissions the higher the concentrations and temperatures. Therefore the uncertainty in the projected temperature due to the uncertainty in the emissions is large. Linguistic rules are obtained through the use of linear emission scenarios and the Magicc model. These rules describe the relations between the concentrations (input) and the temperature increase for the year 2100 (output) and are used to build a fuzzy model. Another model is presented that includes, as a second source of uncertainty in input, the climate sensitivity to explore its effects on the temperature. Models are attractive because their simplicity and capability to integrate the uncertainties to the input and the output.

Original languageEnglish
Title of host publicationSimulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2012, Revised Selected Papers
PublisherSpringer/Verlag
Pages223-237
Number of pages15
Volume256
ISBN (Electronic)9783319035802
DOIs
Publication statusPublished - 2014
EventInternational Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012 - Rome, Italy
Duration: 28 Jul 201231 Jul 2012

Publication series

NameAdvances in Intelligent Systems and Computing
Volume256
ISSN (Print)21945357

Conference

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

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Keywords

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

Cite this

García, C. G., Meneses, O. S., Martínez-López, B., Nebot, À., & Estrada, F. (2014). Fuzzy models: Easier to understand and an easier way to handle uncertainties in climate change research. In Simulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2012, Revised Selected Papers (Vol. 256, pp. 223-237). (Advances in Intelligent Systems and Computing; Vol. 256). Springer/Verlag. https://doi.org/10.1007/978-3-319-03581-9_16