ClimateIQ is an AI driven, multi-hazard risk and vulnerability tool leveraging Machine Learning, Big Data, and multiple climate hazard model environments to reveal high resolution hotspots of overlapping climate risks in cities and urbanized regions.
The aim of the tool is to help city planners and communities prioritize local adaptations to climate hazards, using advanced climate models and machine learning to identify the areas most at risk.
Our Approach:
ClimateIQ is based on an innovative, integrated multi-hazard modeling environment, which generates predictions for high resolution urban heat and extreme flood hazard exposure information. ClimateIQ uses advanced physics-based models to simulate climate hazard exposure. Machine learning models learn to reproduce the outputs of the physics-based models, speeding up climate hazard simulation time. To make hazard information available to users, ClimateIQ partners with Climasens to provide a user-friendly dashboard and APIs for easy integration into existing workflows.
Team:
The ClimateIQ team brings extensive experience in climate risk modeling, AI applications, data analysis and visualization, as well as working with diverse stakeholders in cities. Led by Dr. Timon McPhearson, Director of the Urban Systems Lab (USL) at the New School in New York City, the core team includes faculty and researchers at The New School, along with partners at Climasens, Stockholm Resilience Centre (SRC), Beijer Institute of Ecological Economics, Cary Institute of Ecosystem Studies and George Mason University. Support provided in part by Google.org Impact Challenge on Climate Innovation.
