Democratizing climate action & enhancing climate literacy: An AI-assisted geospatial analysis of historical trends and future projections for urban resilience using Kolkata as a case study

This paper presents a generative-AI–assisted, open-source framework designed to democratize access to complex climate data and strengthen public climate literacy, using Kolkata as a case study. By leveraging generative AI to synthesize code for Google Earth Engine and R, the authors show how non-experts can analyze historical climate trends and explore future projections without advanced programming skills. The analysis reveals significant urban warming driven by rapid land-use change, intensifying night-time heat stress and increasing the risk of extreme rainfall, while projections suggest up to ~3 °C warming and a sharply rising probability of late-monsoon extreme rainfall by 2030. Overall, the study argues that translating technical climate data into citizen-centric narratives is essential for shifting cities from reactive disaster response toward anticipatory, community-informed climate action and disaster risk reduction.