Scientists are challenging conventional notions of how dust particles are aligned; “everything we’ve so far hypothesized about the impact of dust on the atmosphere might be misplaced.”
remote sensing
Posted inEditors' Highlights
Streamer Corona Discharges in Thunderstorms Detected from Space
Concurrent detection from space and the ground of blue optical flashes from streamer corona discharges at altitudes between 8.5 and 14 kilometers and radio waves.
Posted inEditors' Highlights
Lightning Discharge Type Linked to Terrestrial Gamma‐Ray Flashes
For the first time, the connection between energetic in cloud pulse and terrestrial gamma‐ray flashes is confirmed in the Gamma-Ray Observation of Winter Thunderclouds experiment in Japan.
Posted inNews
Wildfires Trigger Long-Term Permafrost Thawing
Researchers used satellite data to trace ground subsidence in a permafrost-rich region in eastern Siberia following a wildfire.
Posted inNews
Drones Help Bridge the Gaps in Assessing Global Change
New instruments in the research tool kit bolster scientific understanding of the ecology of a greening Arctic.
Posted inResearch Spotlights
Remote Sensing of Algal Blooms Can Improve Health and Save Money
Using satellites to detect cyanobacterial algal blooms can foster faster decision-making that reduces harm to public health as well as associated costs.
Posted inAGU News
Bringing Satellite Observations Down to Earth
This month’s issue of Eos shows how scientists can sometimes get a better look at something by stepping far—much, much farther—away.
Posted inResearch Spotlights
How Forest Degradation Affects Carbon and Water Cycles
Forest degradation may be as widespread as deforestation in the Amazon, but its impact on energy, carbon, and water fluxes is less well understood.
Posted inEditors' Highlights
Can We Observe How Cloud Clustering Affects the Radiation Budget?
Satellite observational analysis confirms that lower-atmospheric stability and cloud clustering are major factors modulating the tropical radiation budget that had been suggested by modeling studies.
Posted inEditors' Highlights
Machine Learning Predicts Subsidence from Groundwater Pumping
Machine learning and data on aquifer type, sediment thickness, and proxies for irrigation water use has been used to produce the most comprehensive map of land subsidence in the western U.S. to date.