About Urban-PREDICT
Introduction
Urban areas worldwide are increasingly vulnerable to weather-related hazards due to global climate change and rapid urbanization. This affects people living in diverse urban conditions and with different levels of vulnerability. These hazards include extreme heat, storm surges, heavy precipitation and flooding, wildfires, and deteriorating air quality. The Urban-PREDICT project, as part of the World Weather Research Program (WWRP) Implementation Plan (IP) 2024–2027, and Advancing Weather Research to Reduce Risk to Societies (AWAR3E) principles, aims to advance urban multi-hazard prediction and Early Warning Systems (EWS). By developing and integrating ultra-high-resolution weather hazard forecasting at application-appropriate spatial scales (ranging from tens to thousands of meters), Artificial Intelligence (AI), and place-specific, culturally relevant data, the project enhances preparedness and response in diverse urban settings.
Goal
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.
Background
Urban areas around the world are facing an unprecedented rise in weather-related hazards as climate change and rapid urbanization intensify the risks. Those hazards include extreme heat, heavy precipitation and flooding, wildfire, and deteriorating air quality. At the same time 70% of the world’s population will be living in cities by 2050, exacerbating both their risks and the number of people potentially exposed. Increasing evidence highlights the effects of wildfire smoke on air quality (AQ) and human health. With more than half the global population living in cities projected to rise significantly, the urgency for effective early warning systems has never been greater. In 2023, the UN Secretary General launched the cross-UN initiative “Early Warnings for All” (EW4All) to ensure that everyone on Earth is protected from hazardous weather, water, or climate events through life-saving early warning systems (EWS) by the end of 2027. EWSs are a proven, efficient, and cost-effective way to save lives and infrastructure and support climate resilience and long-term sustainability. This UN initiative underscores the global commitment to ensuring that every urban community, particularly those most vulnerable, receives timely and actionable weather alerts to mitigate these emerging risks.
Project Structure: Four Working Packages
Accessibility and Relevance of Information
Explore context-specific early warnings and data availability, actionability, and cultural relevance.
Prediction and EWS Across Spatial Scales
Assess the impact of varying spatio-temporal resolutions on hazard prediction accuracy and EWS effectiveness.
Advanced Urban Modelling and Prediction Capabilities
Develop and leverage emerging data sources, numerical weather prediction models and AI to enhance urban multi-hazard forecasting from nowcasting to seasonal timescales.
Prediction and EWS Across Spatial Scales
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.
WP1
Knowledge synthesis and guidance on better accessibility and culturally relevant urban datasets and information to support actionable EWS for place-specific preparedness and response.
WP3
Enhanced understanding of the role of diverse and emerging models and urban data in hazard prediction and improved ultra-high-resolution urban hazard prediction and EWS capabilities.
WP2
Improved knowledge and recommendations for benchmarking on the role of spatial scale in providing effective multi-hazard early warnings.
WP4
Improved preparedness of policymakers, communities, and practitioners in urban areas to respond to weather-related risks using data and information that are place-specific and result from a dialogue of knowledges.
Expected Outcomes
Impacts
The project will foster and build a dynamic international community of researchers in urban prediction, enhancing global collaboration, knowledge exchange, and capacity-building for urban multi-hazard prediction and early warning systems. Communities in urban areas will have reduced adverse impacts from weather-related multi-hazard risks as a result of better preparedness and enhanced minute-to-season multi-hazard prediction and EWS, clear risk communication campaigns, and actionable plans.