Stochastic Modeling of Climate Change Impact: Assessing Regional Temperature Increases Under Global Warming

Richard Murdoch Montgomery

doi:10.20944/preprints202406.0055.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 2 June 2024 / Approved: 3 June 2024 / Online: 3 June 2024 (09:40:16 CEST)

In this study, we develop a stochastic partial differential equation (SPDE) model to assess the regional severity of temperature increases due to global warming. The model incorporates various stochastic processes to account for uncertainties such as solar explosions, economic upheavals, rising emissions, and irreversible changes in the climate system. Our base temperature model, influenced by latitude, is enhanced by these random factors to simulate realistic and diverse outcomes of climate change. Numerical simulations on a global grid provide a heatmap representing potential temperature increase severity across different regions. The results highlight the significant impact on tropical and polar regions, demonstrating the utility of SPDE models in understanding and predicting the complex dynamics of climate change. This approach offers valuable insights for policymakers and researchers aiming to develop adaptive strategies for mitigating the adverse effects of global warming.

climate change; global warming; stochastic simulation; complex dynamics

Environmental and Earth Sciences, Environmental Science

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Stochastic Modeling of Climate Change Impact: Assessing Regional Temperature Increases Under Global Warming

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