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
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 256)


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.


Fuzzy Inference Models Greenhouse Gases Future Scenarios Global Climate Change 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Carlos Gay García
    • 1
  • Oscar Sánchez Meneses
    • 1
  • Benjamín Martínez-López
    • 1
  • Àngela Nebot
    • 2
  • Francisco Estrada
    • 1
  1. 1.Centro de Ciencias de la AtmósferaUniversidad Nacional Autónoma de MéxicoMexico. D.F.Mexico
  2. 2.Grupo de Investigación Soft ComputingUniversitat Politécnica de CatalunyaBarcelonaSpain

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