AGU Advances launches its Early Career Editorial Fellow program, welcoming three early career scientists to the editorial board.
AGU Advances
Posted inResearch Spotlights
Want to Predict Wildfire Severity? Look to the State of Vegetation
A new study connects satellite data on vegetation condition, topography, and weather conditions to examine the predicted versus actual burn severity of the 2025 Los Angeles wildfires.
Posted inEditors' Highlights
Managed Agriculture Hinders Predictability of Critical Zone Features
Intensively managed agricultural sites show behavioral shifts of the critical zone system and subsystems thus impacting predictability.
Posted inEditors' Highlights
Toward Marine Cloud Brightening at Scale: A Science Agenda
Marine Cloud Brightening (MCB) is a Solar Radiation Management (SRM) solution to cool the planet by changing the albedo of low-altitude marine clouds to increase reflected shortwave radiation.
Posted inEditors' Highlights
More Braided Rivers from Increasing Flow Variability
Global analysis of satellite data and river flow records show that higher flow intermittency after climate change may lead to an increasing number of threads in braided rivers, thus impacting ecosystems.
Posted inResearch Spotlights
What Makes Mars’s Magnetotail Flap?
Spacecraft reveal a key driver of up-and-down motions of thin, current-carrying plasma sheets on the nightside of Mars.
Posted inEditors' Highlights
Amazon River Breezes Mimic Pollution in Clouds
Natural river breezes create clouds over the Amazon that mimic the signs of pollution, complicating climate impact assessments.
Posted inEditors' Highlights
Timing of Geomagnetic Storms Shapes Their Impact
The impact of geomagnetic storms, which can disrupt satellites, GPS, and power grids, is shown to depend on their onset timing.
Posted inResearch Spotlights
Glaciers May Flow into the Ocean More Quickly Than We Think
New research found that adjusting a key model variable may give more accurate predictions of glacial retreat.
Posted inEditors' Highlights
Machine Learning Could Enhance Earth System Modeling
Based on tests of a machine learning-based (ML) hybrid model, combining ML with established physics-based frameworks represents a promising path toward developing ML-based Earth system models.