RESEARCH · RESEARCH · #619
TACLS: Scripps’ new satellite + machine-learning tool to help detect flash floods
Researchers at the Scripps Institution of Oceanography (UC San Diego) developed the Transient Artifact and Continuous Learning System (TACLS), software that combines satellite data and machine learning to help National Weather Service forecast offices spot areas at risk of flash flooding sooner and support warning decisions. The project is presented as a new decision-support tool intended to improve lead time and accuracy of flash-flood alerts rather than a completed, nationwide operational system.
KEY POINTS
- Researchers at the Scripps Institution of Oceanography (UC San Diego) developed the Transient Artifact and Continuous Learning System (TACLS), software that combines satellite data and machine learning to help National Weather Service forecast offices spot areas at risk of flash flooding sooner and support warning decisions.
- The project is presented as a new decision-support tool intended to improve lead time and accuracy of flash-flood alerts rather than a completed, nationwide operational system.
- Early, machine-learning–augmented detection of flash-flood conditions could give forecasters more lead time to issue life-saving warnings and improve situational awareness at NWS offices.
WHY IT MATTERS
Early, machine-learning–augmented detection of flash-flood conditions could give forecasters more lead time to issue life-saving warnings and improve situational awareness at NWS offices.