New research is challenging established assumptions about how clouds form and interact with Earth’s surface. One result may be better weather forecasts.
machine learning & AI
Deep Learning Facilitates Earthquake Early Warning
A deep learning model trained with real-time satellite data significantly reduces the time to predict the ground motion of big earthquakes.
Machine Learning for Geochemists Who Don’t Want to Code
Geochemistry π is an easy-to-use step-by-step interface to carry out common machine learning tasks on geochemical data, including regression, clustering, classification, and dimension-reduction.
How Did We Miss 20% of Greenland’s Ice Loss?
The ice loss was hidden in places existing monitoring methods can’t reach, such as hard-to-map fjords. Machine learning helped scientist revise mass loss estimates and uncover patterns in glacial retreat.
Using Machine Learning to Reconstruct Cloud-Obscured Dust Plumes
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.
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.
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.
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.
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.