A non-autonomous framework for climate change and extreme weather events increase in a stochastic energy balance model

TL;DR

This paper introduces a stochastic reaction-diffusion model with three timescales to analyze how climate change influences temperature variability and extreme weather events, showing increases in mean and variance without bifurcation.

Contribution

It presents a novel three-timescale stochastic energy balance model incorporating space heterogeneity to better understand climate change impacts on temperature fluctuations.

Findings

Mean and variance of temperature increase due to climate change

System does not undergo bifurcation despite temperature increases

Model captures the rise in extreme weather event frequency

Abstract

We develop a three-timescale framework for modelling climate change and introduce a space-heterogeneous one-dimensional energy balance model. This model, addressing temperature fluctuations from rising carbon dioxide levels and the super-greenhouse effect in tropical regions, fits within the setting of stochastic reaction-diffusion equations. Our results show how both mean and variance of temperature increase, without the system going through a bifurcation point. This study aims to advance the conceptual understanding of the extreme weather events frequency increase due to climate change.