Abstract—In this work, we propose a simple but effective model to predict the future changes in global temperature based on the greenhouse gases emission rate. Our model provides an empirical formula which connects the global average temperature with the atmospherical concentration of carbon dioxide. Parameters of the model are estimated by evaluating the existing climatic data. Good agreements are observed by comparing the predicted results with the Representative Concentration Pathways (RCPs) data. Moreover, a novel carbon dioxide elimination model that considers the impact of energy and climate governance is reported, and it could serve as a general approach when considering the influences from different climatic factors.
Index Terms—Representative concentration pathways (RCPs) data.
Heming Huang is with Watkinson School in Hartford Connecticut, USA (e-mail: mhuang@watkinson.org).
Xinmeng Li is with the Lake Forest Academy, in Lake Forest, IL, USA (e-mail: xli@students.lfanet.org).
Xiaoyu Tian is with the Mccallie School, 500 Dodds Avenue Chattanooga, USA (e-mail: johnnytian21@mccallie.org).
Andrew Zhang is with School Trinity Pawling School, USA (e-mail: azhang@trinitypawling.org).
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Cite: Heming Huang, Xinmeng Li, Xiaoyu Tian, and Andrew Zhang, "A Simple Model for Quantitative Prediction of Future Climate Change," International Journal of Modeling and Optimization vol. 9, no. 6, pp. 298-302, 2019.
