Different kinds of severe weather, including multiple kinds at once, have different impacts on the grid in different places.
disaster preparedness
Posted inEditors' Highlights
Using Satellite Data for More Effective Disaster Response
Satellite data play a crucial role in disaster assessment and response. Meeting expanding demand requires not only accelerated data processing but increased collaboration with responders.
Posted inNews
Improving Earthquake Early Warning Access for the Deaf Community
Earthquake early warning systems are rarely accessible to people who are deaf or hard of hearing. A group of scientists is working to change that.
Posted inNews
Alaska’s Mount Veniaminof Volcano Is Stealthy—Here’s Why
New research explains why Mount Veniaminof erupts without the usual warming signs.
Posted inNews
Water Testing Builds Trust in Science as Maui Communities Recover
Following fires that ravaged the island in 2023, researchers educated residents about how wildfires affect water quality, and gathered data to determine how wildfire impacts change over time.
Posted inNews
Seismometers Track Atmospheric Shock Waves from Incoming Space Debris
A Chinese spacecraft that burned up high over Los Angeles created a sonic trail detected by ground-based sensors.
Posted inNews
Torrents of Sediment-Laden Water Worsened Disastrous Libyan Floods
Drought followed by torrential rain can unleash deadly floods in arid regions, like those that affected Libya in 2023.
Posted inResearch Spotlights
Machine Learning Could Improve Extreme Weather Warnings
A deep learning technique could reduce the error in 10-day weather forecasts by more than 90%, allowing communities to better prepare for extreme events such as heat waves.
Posted inNews
Rancho Palos Verdes Landslides Have Residents Seeking Science
Residents of Rancho Palos Verdes are looking to the scientific community for help in understanding the slow-moving landslides that are destroying their community.
Posted inOpinions
Cultivating Trust in AI for Disaster Management
Artificial intelligence applied in disaster management must be reliable, accurate, and, above all, transparent. But what does transparency in AI mean, why do we need it, and how is it achieved?