Predictions, Risk assessments, Early warnings, Data integration, Inclusive governance, Community awareness, and Transformative actions
Urban-PREDICT seeks to reduce weather-related risks by combining advanced weather prediction models with community and place-specific insights, including decision-making structures and processes. This will lead to more effective early warning systems and risk management strategies tailored to urban populations.
Explore context-specific early warnings and data availability, actionability, and cultural relevance.
Assess the impact of varying spatio-temporal resolutions on hazard prediction accuracy and EWS effectiveness.
Develop and leverage emerging data sources, numerical weather prediction models and AI to enhance urban multi-hazard forecasting from nowcasting to seasonal timescales.
Leverage knowledge and capacity to enable stakeholders (including scientists, policymakers, emergency management, and communities) to co-develop the tools and insights necessary for resilient urban EWS planning.
Cities are hotspots for climate-related risks. Dense infrastructure, high population,…
Artificial Intelligence is changing the way we understand and predict…
Urban areas are becoming increasingly vulnerable to unpredictable weather patterns.…