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machine learning & AI

Figure showing simulation from the study.
Posted inEditors' Highlights

Equation Discovery for Subgrid-Scale Closures

by Tapio Schneider 24 July 202424 July 2024

Machine learning can discover closure equations for fluid simulations. A new study finds that common algorithms rediscover known, unstable closures, which can be stabilized with higher-order terms.

A vast forested landscape in Chhattisgarh, India.
Posted inNews

New Model Can Better Predict Areas Vulnerable to Forest Fires in India

by Pragathi Ravi 24 July 202424 July 2024

Researchers incorporated local atmospheric parameters and terrain data to more accurately estimate the probability of fire in a specific area.

Photo of Dr. Jaclyn Clement Kinney
Posted inEditors' Vox

Introducing the New Editor-in-Chief of the ESS Open Archive

by Jaclyn Clement Kinney 22 July 202422 July 2024

Learn about the person taking the helm of the Earth and Space Science Open Archive and their vision for the coming years.

Diagram from the paper.
Posted inEditors' Highlights

Physics + Machine Learning Provide a Better Map of Ocean Measurements

by Stephen M. Griffies and Oliver Watt-Meyer 15 July 202411 July 2024

A new study offers a compelling example where the merger of dynamical modeling, machine learning, and ocean measurements enhances oceanographic understanding, monitoring, and mapping.

Figure showing weather forecasts.
Posted inEditors' Highlights

Machine Learning Masters Weather Prediction

by Hannah Christensen 10 July 20241 July 2024

Community datasets and evaluation standards are needed to further advance machine learning for weather prediction.

Maps from the study
Posted inEditors' Highlights

Autocalibration of the E3SM Atmosphere Model Improves Model Fidelity

by Jiwen Fan 9 May 20247 May 2024

A surrogate model was trained to predict E3SM atmosphere model spatial fields as a function of uncertain physical parameters and used to optimize the parameters for present-day climate.

Remote sensing image of the Pan-Third Pole region
Posted inEditors' Vox

Harmonizing Theory and Data with Land Data Assimilation

by Xin Li and Feng Liu 7 May 20249 May 2024

Land data assimilation advances scientific understanding and serves as an engineering tool for land surface process studies, reflecting the trend of harmonizing theory and data in the big data era.

Four graphs from the paper
Posted inEditors' Highlights

Learning Data Assimilation Without the Help of the Gaussian Assumption

by Stefan Kollet 15 April 202411 April 2024

Major Earth system processes are non-linear and non-Gaussian, and so should be our data assimilation approaches.

Figure from the paper.
Posted inEditors' Highlights

Machine Learning Accelerates the Simulation of Dynamical Fields

by Jiwen Fan 20 March 202418 March 2024

Fourier neural operator solvers accurately emulate particle-resolved direct numerical simulations and significantly reduce the computational time by two orders of magnitude.

Photo of Alexandre Schubnel with a cover of JGR: Solid Earth.
Posted inEditors' Vox

Introducing the new Editor-in-Chief of JGR: Solid Earth

by Alexandre Schubnel 28 February 202428 February 2024

Learn about the person taking the helm of JGR: Solid Earth and his vision for the coming years.

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