Big Data-Driven Climate Change Impact Modelling and Risk Assessment Tool

Environment modification represents one of the most significant existential threats to the modern world, characterised by the increasing frequency of extreme natural disasters. Traditional methods of climate modelling often struggle to process the sheer volume, velocity, and variety of meteorological data generated daily by satellites, IoT sensors, and historical archives. This project proposes the development of a Big Data- Driven Climate Change Impact Modelling and Risk Assessment Tool, a sophisticated software ecosystem designed to ingest, process, and analyse massive datasets to predict climate risks with high granularity. The tool aggregates heterogeneous data sources— including atmospheric pressure readings, oceanic temperature logs, carbon emission statistics, and satellite imagery—to create dynamic, real-time predictive models. These models are capable of forecasting localised climate impacts, such as flood risks in urban areas or drought probabilities in agricultural zones, with a level of precision previously unattainable. Furthermore, the system incorporates a user-friendly visualisation interface that translates complex petabytes of unstructured data into intuitive heat maps, trend graphs, and risk assessment dashboards. This enables stakeholders, ranging from government policy-makers and urban planners to environmental researchers, to make data-driven decisions. Ultimately, this project aims to bridge the gap between raw environmental data and actionable climate intelligence, providing a scalable, robust solution for monitoring and mitigating the impacts of global warming in the 21st century.