A new special collection invites papers pertaining to the use of machine learning techniques in all sub-fields of heliophysics.
machine learning & AI
Posted inEditors' Highlights
Machine Learning Looks Anew at Isotope Ratios in Oceanic Basalts
While past attempts to define isotopic endmembers and assign them a geodynamic significance ended in controversy, a machine-learning clustering algorithm offers a solution to this classical problem.
Posted inEditors' Highlights
Deep Learning for Hydrologic Projections Under Climate Change
Extrapolation or not? Big data may help deep learning to go places where it has not been before by transferring learned hydrologic relationships.
Posted inFeatures
How Quantum Computing Can Tackle Climate and Energy Challenges
The day is coming when quantum computers, once the stuff of science fiction, will help scientists solve complex, real-world problems that are proving intractable to classical computing.
Posted inNews
Satellites Get First Full-Year View of Arctic Sea Ice Thickness
The AI-based monitoring method may unlock data that could improve shipping safety and climate predictions.
Posted inNews
Tracking Climate Through Ship Exhaust
International regulations have reduced aerosol pollutants released from ships. Now, researchers want to use ship tracks to better understand the ambiguous effects that cleaner air has on climate.
Posted inEditors' Highlights
Quantifying Changes in Midlatitude Subseasonal Prediction Skill
The differences between future and present subseasonal predictability in the Northern Hemisphere provided by the tropics are evaluated using neural networks.
Posted inEditors' Vox
Monitoring the Health of Our Planet using Earth Observations
A new book explores how Earth science knowledge addresses critical global challenges including sustainable development, disaster risk reduction, and climate change.
Posted inNews
New Landslide Reporting Tool Uses Social Media and AI
The tool extracts landslide information in real time, which could advance landslide research as well as disaster response.
Posted inResearch Spotlights
Machine Learning Could Revolutionize Mineral Exploration
Using a global data set of zircon trace elements, new research demonstrates the power of machine learning algorithms to accurately identify and locate porphyry copper deposits.