Understanding Climate and Extreme Weather Events in the Greater New York Area

Understanding Climate and Extreme Weather Events in the Greater New York Area

Naresh Devineni, The City College of New York – CUNY (Principal Investigator)

James Booth, The City College of New York – CUNY (Co-Investigator)

Abstract

      New York City (NYC) would benefit from more tools and information to help with the City’s response to unexpected flooding, especially from extreme rainfall events. The City’s challenges in responding to flooding events in real-time was brought into sharp focus in 2021 by the devastating results of Tropical Storm Henri and then Hurricane Ida. NYC experiences flooding events from excessive rainfall from storms nearly every year, and sometimes multiple times in the same year. It would benefit, in both financial and human terms, from better predictions for the areas most vulnerable to flooding for any storm event. The City is also concerned about combined sewer overflows because of their effect on water quality and recreational uses. Hence, it seeks to incorporate the best available information about the current and future extreme rainfall events. 

      Understanding the scenarios that properly represent likely storm paths over the City and the associated space-time patterns of rainfall can help improve the operation and performance of hydrologic systems. The traditional design storm-based approach is inadequate for such spatial network simulations. As such, the proposed research seeks to develop a methodology to design extreme rainfall event scenarios considering changing large-scale climate patterns for informing spatial risk in the Greater New York City area. Furthermore, more robust knowledge of correlated extreme events and the resultant simultaneous infrastructure vulnerabilities can support the emergency management division, and will likely create more effective early warning information systems.  

      The research questions that will be addressed are: (a) how space-time distributions of rainfall intensity for extreme rainfall events can best be estimated using multiple sources of rainfall, climate, and storms data; and (b) how these rainfall fields can best be used to assess risks of failure across a network of infrastructure systems. Precipitation estimates from numerical weather and climate models can have significant biases and not resolve the spatial scales relevant for urban flood hazard assessment. However, they resolve the large-scale features of moisture transport associated with the events of concern. In essence, the models capture the larger-scale feature of mesoscale convective systems,

mesoscale convective system (MCS)

A collection of thunderstorms that act as a system. An MCS can spread across an entire state and may appear as a solid line, a broken line, or a cluster of cells that can last more than 12 hours.

Source: NOAA Source

but not the fine details. The project will leverage these aspects of the climate models to develop a physics-informed stochastic approach that improves the specificity and accuracy of precipitation associated with future extreme rainfall events. 

      The PIs at The City College of New York (CCNY) will collaborate with the Department of Energy’s Pacific Northwest National Laboratory (PNNL) scientists. This partnership will combine PNNL scientists’ expertise in mesoscale convective systems and climate modeling with the PIs’ expertise in weather, climate, and hydrologic extremes. The project will facilitate more collaboration between CCNY and PNNL, and is intended to be a catalyst to more extensive research engagement focused on high impact weather and climate issues.