This project presents a data-driven framework for modeling and pricing temperature-based weather derivatives using observational datasets from NOAA’s National Centers for Environmental Information. The analysis focuses on extracting temperature indices from daily station data (i.e., at JFK and LAX airports) to quantify deviations from historical norms. These indices are used to construct payoff structures linked to Heating and Cooling Degree Days.