Hyper-Local Weather Forecasting System Could be a Boon to New York

Cornell University has begun work developing a hyperlocal weather forecasting system for New York state’s rural communities. 

They've partnered with community stakeholders to design and implement a forecasting system aimed at improving winter-storm emergency response and coordination around natural disasters.

It’s a part of a competition hosted by the National Science Foundation, or NSF. For the competition, NSF has administered grant funding to Community Driven research projects.

Cornell is in Phase 1 of the NSF competition. They’ve received $50 thousand for this project. If they are selected for Phase 2, their funding will jump to a $1 million.

Max Zhang is leading Cornell's weather forecasting project. He’s a professor in Cornell’s Sibley School of Mechanical and Aerospace Engineering. 

He said the project is going to begin by setting up monitors along the local road system to give officials an accurate sense of what conditions are across Tompkins County’s remote areas. It will grow from there, but the mantra of local forecasting is data.

Zhang said, "With better data, more granular data, and better services, right? So they can make that decision in a more real time response to the conditions."

Zhang stresses the importance a real-time response can have. He said, "How we can maintain roads and our transportation system in the winter storm, or other extreme weather conditions, is often a life and death question, right?"

Climate change is, of course, a motivation to work on this project. Zhang said, as winter storms and natural disasters increase in their intensity, some will be more affected than others.

"Yeah. It's definitely an equity issue. We want to focus on the rural area. I think that we believe the rural community is affected by extreme weather disproportionate fashion."

By creating this tool, this system could alleviate some of the pressures on the limited budgets of towns in upstate New York, and better prepare them for challenges to come.