FACTS: Fuzzy assessment and control for temperature stabilization: Regulating global carbon emissions with a fuzzy approach to climate projections

This work presents a new approach for assessing the climate system and for stabilizing the temperature and other climate parameters. FACTS, as we call it, is a fuzzy inference system that overview certain climate state, and is able to generate the CO2 emissions reduction needed to implement in order to stabilize the temperature. FACTS was constructed using a neural network optimization process along with data generated by a classical emissions pathfinder. Then, it was embedded in MAGICC6, a simple climate model that was forced by the four Representative Concentration Pathways until and ultimately stabilized by the proposed methodology.