Flash floods can strike without warning — this new technology could change that
UCSD, NASA, and NWS scientists built TACLS, a satellite and machine learning system providing earlier flash flood warnings, initially in California.
The Transient Artifact and Continuous Learning System (TACLS) combines satellite data, GNSS ground sensors, and machine learning to identify areas at risk of transitioning from rain to dangerous flash floods sooner than current NWS tools like rain gauges and radars. It was developed by Scripps Institution of Oceanography at UC San Diego with NWS forecasters and NASA, funded by NASA's Earth Science Technology Office through its Advanced Information Systems Technology program. TACLS currently covers only California but will be made available to all 122 NWS weather forecast offices. The motivation follows deadly flash floods such as the June 9 Lanesville, Indiana event with over 8 inches of rain in hours.
- TACLS uses GNSS satellite and ground sensor data with machine learning for flood prediction
- Developed by UCSD Scripps, NWS, and NASA; NASA-funded project
- Currently covers California; rollout planned to all 122 NWS offices
- Aims to give earlier flash flood warnings than existing gauges and radars
- Vendors
- NASA
- Products
- TACLS
- Countries
- United States
From the original article
8 min read at theverge.com
On the morning of June 9th, Laura Lin was working from her home in Lanesville, a rural southern Indiana town about 15 miles from the Kentucky border. She was on a Zoom call, unaware that the heavy rain outside was beginning to flood her yard. "I look over to where the barn is over there, and I see pieces of my wood floating, and I was like, 'What?'
By Megan Wollerton · theverge.com
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