Satellite-observed dust plumes from North Africa are frequently obscured by clouds, but a new study uses machine learning to reconstruct dust patterns, demonstrating a new way to validate dust forecasts.
machine learning & AI
Posted inEditors' Vox
OneHealth, Climate Change, and Infectious Microbes
AGU and ASM welcome submissions to a joint special collection focusing on the impacts of climate change and microbes on human well-being.
Posted inEditors' Highlights
Deep Learning Tackles Deep Uncertainty
A new method based on artificial intelligence could help accelerate projections of polar ice melt and future sea level rise.
Posted inEditors' Vox
JGR: Machine Learning and Computation is Open for Submissions
The founding Editor-in-Chief discusses how AGU’s newest journal will capture critical advancements of the techniques moving scientific discovery forward.
Posted inResearch Spotlights
Mapping Mars: Deep Learning Could Help Identify Jezero Crater Landing Site
Researchers used new techniques to more precisely estimate ground elevations on Mars, producing a refined resolution map for rover landings.
Posted inEditors' Highlights
Machine Learning Identifies Source Volcanoes of Ash Deposits
Tracing ash layers from explosive eruptions back to their source volcanoes is needed to evaluate hazards to population and aviation, a problem addressed by a new machine learning classification method.
Posted inNews
Rivers Are Warming Up and Losing Oxygen
Researchers used deep learning to fill in the gaps of “patchy” water quality data, revealing decades-long trends toward warmer and less oxygenated rivers that could have worrisome consequences.
Posted inEditors' Vox
Advancing AI and Machine Learning Beyond Predictive Capabilities
A new cross-journal special collection invites contributions that unlock the next frontier in hydrology and Earth sciences through artificial intelligence and machine learning.