The SERENA methodology introduced in this paper integrates geospatial climatemodel data on crop production into an economic modeling environment. We examine the spillover effects of extreme weather events on commodity prices and inflation using a novel bottom-up framework. Drawing on Representative Concentration Pathway (RCP) scenarios and atmosphere-ocean general circulation models (AOGCMs), we simulate climate-induced supply shocks and trace their transmission to commodity markets and broader inflation dynamics. Monte Carlo simulations are embedded to capture the uncertain and evolving nature of weather-related risk, resulting in forecasts across alternative climate pathways. Our results indicate that extreme weather events can trigger commodity price shocks that exceed 100% by 2040 in certain scenarios, with significant transmission to consumer prices: On average, a 1% commodity price increase leads to a 2% increase in CPI inflation. These results underscore the need for the construction of new climate-informed economic modeling tools capable of translating physical climate risk into actionable signals for the financial and policy sectors.
