We propose to integrate the City of Chicago’s unique urban data resources with advanced assessments of extreme weather conditions, distributed high-resolution air and water sensing, and atmospheric and hydrologic models of extreme weather impacts to inform multi-level systems analyses balancing economic, environmental, efficiency, risk, and social objectives. To advance urban systems science for critical vulnerabilities, we propose to focus on two particularly high impact multi-component hazards: (1) high-intensity storms that cause flooding and damage infrastructure, and (2) stagnant atmospheric conditions conducive to harmful heat waves and deleterious air quality. Projections of increasing, and in some cases unprecedented, extreme weather event intensity and frequency pose acute and daunting challenges for urban infrastructure managers and emergency responders. Given the hyper-local scale of convective precipitation and flooding impacts, a new approach is needed at the frontier linking meteorology and hydrology. Similarly, extreme air stagnation events associated with heat and pollutant accumulation pose a substantial public health challenge in urban environments due to the amplifying effects of heat islands and abundant pollution sources. Flooding and heat/air quality impacts in urban settings are highly non-uniform as they depend on social and built infrastructure, as well as the attendant meteorological conditions. We propose to integrate recent advances in high-resolution weather simulations and real-time assimilation of both weather radar and distributed environmental sensing to assess and predict hazardous conditions with neighborhood-scale resolution. Localized data will be used to inform and validate predictions which will be (a) integrated with urban hydrologic models to assess stormwater infrastructure performance and flooding at neighborhood-scales. and (b) used to identify heat and pollutant accumulation “hotspots” as well as test the remediation potential of hard and soft infrastructure design solutions. Integrating these environmental predictions and infrastructure performance models with demographic data, community impact assessments, and economic damage assessments will advance understanding of the manner in which weather variability, urban infrastructure, and social organization coalesce into urban vulnerability. Integrated simulation, data assimilation, and prediction methods will provide a means to evaluate alternative strategies for increased resilience to extreme weather. Based on assessment of factors that ameliorate local impacts of extreme weather in cities, our team of scientists and engineers will assess alternative infrastructures to increase resilience, including options such as integration of nature-based solutions (green infrastructure) in cities, and adaptive management based on increased ability to predict hazardous weather conditions at city-to-neighborhood scales.
|Effective start/end date||9/15/18 → 8/31/22|
- National Science Foundation (CBET-1848683)
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.