• About
  • Special Reports
  • Topics
    • Climate
    • Earth Science
    • Oceans
    • Space & Planets
    • Health & Ecosystems
    • Culture & Policy
    • Education & Careers
    • Opinions
  • Projects
    • Postcards From the Field
    • ENGAGE
    • Editors’ Highlights
    • Editors’ Vox
    • Eos en Español
    • Eos 简体中文版
    • Print Archive: 2015–2025
  • Policy Tracker
  • Blogs
    • Research & Developments
    • The Landslide Blog
  • Newsletter
  • Submit to Eos
  • AGU.org
  • Career Center
  • Join AGU
  • Give to AGU
  • About
  • Special Reports
  • Topics
    • Climate
    • Earth Science
    • Oceans
    • Space & Planets
    • Health & Ecosystems
    • Culture & Policy
    • Education & Careers
    • Opinions
  • Projects
    • Postcards From the Field
    • ENGAGE
    • Editors’ Highlights
    • Editors’ Vox
    • Eos en Español
    • Eos 简体中文版
    • Print Archive: 2015–2025
  • Policy Tracker
  • Blogs
    • Research & Developments
    • The Landslide Blog
  • Newsletter
  • Submit to Eos
Skip to content
  • AGU.org
  • Career Center
  • Join AGU
  • Give to AGU
Eos

Eos

Science News by AGU

Support Eos
Sign Up for Newsletter
  • About
  • Special Reports
  • Topics
    • Climate
    • Earth Science
    • Oceans
    • Space & Planets
    • Health & Ecosystems
    • Culture & Policy
    • Education & Careers
    • Opinions
  • Projects
    • Postcards From the Field
    • ENGAGE
    • Editors’ Highlights
    • Editors’ Vox
    • Eos en Español
    • Eos 简体中文版
    • Print Archive: 2015–2025
  • Policy Tracker
  • Blogs
    • Research & Developments
    • The Landslide Blog
  • Newsletter
  • Submit to Eos

machine learning & AI

Three photographs showing nodes being staged, transported by truck, and charged/harvested in racks.
Posted inEditors' Vox

The Big Data Revolution Unlocks New Opportunities for Seismology

by Stephen J. Arrowsmith, Daniel T. Trugman, Karianne Bergen and Beatrice Magnani 9 June 202214 June 2022

The field of seismology is entering a new era where our understanding of earthquakes and the solid earth is increasingly driven by new Big Data experiments and algorithms.

Graph showing contribution of each large-scale atmospheric variable on the y-axis to predicted total convective area.
Posted inEditors' Highlights

Using Artificial Intelligence to Study Convection

by Minghua Zhang 8 June 202223 January 2023

Machine learning techniques are used to examine relationships between the large-scale state of the atmosphere, the convection total area, and the degree of organization in northern Australia.

Illustration of the AI algorithm estimating large earthquakes’ magnitudes on the basis of prompt elastogravity signals (PEGS) traveling at the speed of light, much faster than seismic (P and S) waves.
Posted inNews

Monitoring Earthquakes at the Speed of Light

by Mohammed El-Said 2 June 20222 June 2022

New research uses gravity and a machine learning model to instantaneously estimate the magnitude and location of large earthquakes.

A representation of the “plumbing system” underneath a volcano, with multiple reservoirs at different depths in the crust where magma may be stored.
Posted inEditors' Highlights

Machine Learning Helps See into a Volcano’s Depths

by Paul Asimow 27 April 202215 November 2022

How big might future volcanic eruptions be? Crystals carry information to answer this and machine learning methods can visualize and interpret this multidimensional data.

Illustrations showing the uses of fractures in the subsurface.
Posted inEditors' Vox

Understanding and Utilizing the Fractured Earth

by Hari Viswanathan and Jeffrey Hyman 26 April 20222 August 2022

The prediction of flow and transport in fractured rock is one of the great challenges in the Earth and energy sciences with far-reaching economic and environmental impacts.

Scientists using ground-penetrating radar equipment
Posted inResearch Spotlights

Testing a Machine Learning Approach to Geophysical Inversion

by Morgan Rehnberg 1 April 20221 April 2022

Variational autoencoders can be leveraged to provide an effective method of inversion that is both accurate and computationally efficient.

Maps of time-mean precipitation pattern error for 40-day simulations with three configurations of a global atmospheric model with a coarse 200-km grid.
Posted inEditors' Highlights

Corrective Machine Learning for Improving Climate Models

by Jiwen Fan 15 March 20225 January 2023

A machine-learned correction enables an efficient coarse-grid global atmosphere model to better track the weather and time-mean precipitation of an expensive fine-grid ‘digital twin’ reference model.

A pile of fiber-optic cable sits on a street in New York City with workers in the background.
Posted inFeatures

Distributed Sensing and Machine Learning Hone Seismic Listening

by Whitney Trainor-Guitton, Eileen R. Martin, Verónica Rodríguez Tribaldos, Nicole Taverna and Vincent Dumont 4 March 202214 May 2024

Fiber-optic cables can provide a wealth of detailed data on subsurface vibrations from a wide range of sources. Machine learning offers a means to make sense of it all.

Parka-clad volunteers collecting a meteorite that fell in Antarctica
Posted inENGAGE, News

Machine Learning Pinpoints Meteorite-Rich Areas in Antarctica

Katherine Kornei, Science Writer by Katherine Kornei 1 March 202227 March 2023

A new algorithm suggests that only a small fraction of meteorites present on the White Continent’s surface have been recovered to date.

A gravel pit near Antofagasta, Chile, with an overlay of waveforms from the Iquique aftershock sequence
Posted inResearch Spotlights

Comparing Machine Learning Models for Earthquake Detection

Kate Wheeling, freelance science writer by Kate Wheeling 24 February 202224 February 2022

A new study evaluated the performance of emerging deep learning models for earthquake detection, phase identification, and phase picking.

Posts pagination

Newer posts 1 … 13 14 15 16 17 … 23 Older posts
Over a dark blue-green square appear the words Special Report: The State of the Science 1 Year On.

Features from AGU Publications

Research Spotlights

Extreme Heat May Drive Asthma Risk in Baltimore, Especially at Night

12 August 202612 August 2026
Editors' Highlights

Drought Extremes are Intensifying More Rapidly Than in the Past

18 August 2026
Editors' Vox

Introducing Research Letters in Paleoceanography and Paleoclimatology

12 August 202610 August 2026
Eos logo at left; AGU logo at right

About Eos
ENGAGE
Awards
Contact

Advertise
Submit
Career Center
Sitemap

© 2026 American Geophysical Union. All rights reserved Powered by Newspack