This paper examines the spillover effects of weather events on inflation via commodity prices, utilizing a bottom-up approach enhanced by forward-looking Monte Carlo simulations. The SERENA methodology, developed for this study, facilitates the integration of geospatial climate models into economic analysis. By leveraging Representative Concentration Pathways (RCP) scenarios and data from the Atmosphere-Ocean General Circulation Models (AOGCMs), we assess how climate-induced fluctuations in commodity prices affect inflation. The inclusion of Monte Carlo simulations captures the dynamic and uncertain nature of weather patterns, enabling robust forecasts under varying climate scenarios. Our findings indicate significant spillover effects, with extreme weather driving commodity price shocks of up to 100% by 2040. These price shocks, in turn, exert upward pressure on inflation, with a 1% rise in commodity prices leading to an average 2% increase in US CPI inflation. These results provide valuable insights for policymakers and investors aiming to understand the economic and financial impacts of climate change.
