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

doi:10.1007/978-3-319-03581-9_16

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

Environmental Economics

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-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 language	English
Title of host publication	Simulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2012, Revised Selected Papers
Publisher	Springer/Verlag
Pages	223-237
Number of pages	15
Volume	256
ISBN (Electronic)	9783319035802
DOIs	https://doi.org/10.1007/978-3-319-03581-9_16
Publication status	Published - 2014
Event	International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012 - Rome, Italy Duration: 28 Jul 2012 → 31 Jul 2012

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	256
ISSN (Print)	21945357

Conference

Conference	International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012
Country/Territory	Italy
City	Rome
Period	28/07/12 → 31/07/12

Keywords

Fuzzy inference models
Global climate change
Greenhouse gases future Scenarios

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-319-03581-9_16

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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

García, Carlos Gay ; Meneses, Oscar Sánchez ; Martínez-López, Benjamín et al. / Fuzzy models : Easier to understand and an easier way to handle uncertainties in climate change research. Simulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2012, Revised Selected Papers. Vol. 256 Springer/Verlag, 2014. pp. 223-237 (Advances in Intelligent Systems and Computing).

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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.",

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booktitle = "Simulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2012, Revised Selected Papers",

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García, CG, Meneses, OS, 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, Advances in Intelligent Systems and Computing, vol. 256, Springer/Verlag, pp. 223-237, International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012, Rome, Italy, 28/07/12. https://doi.org/10.1007/978-3-319-03581-9_16

Fuzzy models: Easier to understand and an easier way to handle uncertainties in climate change research. / García, Carlos Gay; Meneses, Oscar Sánchez; Martínez-López, Benjamín et al.
Simulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2012, Revised Selected Papers. Vol. 256 Springer/Verlag, 2014. p. 223-237 (Advances in Intelligent Systems and Computing; Vol. 256).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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T2 - International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012

AU - García, Carlos Gay

AU - Meneses, Oscar Sánchez

AU - Martínez-López, Benjamín

AU - Nebot, Àngela

AU - Estrada, Francisco

PY - 2014

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N2 - 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.

AB - 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.

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ER -

García CG, Meneses OS, Martínez-López B, Nebot À, Estrada F. 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. Springer/Verlag. 2014. p. 223-237. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-03581-9_16

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

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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