AGU Launches Journal of Geophysical Research: Machine Learning and Computation


Today, we are excited to announce the launch of a new open access journal, the Journal of Geophysical Research: Machine Learning and Computation.

JGR: Machine Learning and Computation is dedicated to research that explores data-driven and computational methodologies based on statistical analysis, machine learning, artificial intelligence and mathematical models, with the aim of advancing knowledge in the Earth and space sciences. In particular, this journal will accept papers proposing novel results in the broad fields of solar and space physics, geophysical fluids and planetary environments, Earth surface and interiors, and biogeosciences.

“In the last five years alone, we’ve seen research utilizing machine learning and artificial intelligence grow rapidly across AGU journals and meetings, and for good reason,” said Lisa J. Graumlich, president of AGU. “Earth and space scientists have access to more data than ever. These cutting-edge techniques are invaluable in helping scientists use this data to uncover new insights about our planet and improve crucial scientific predictions, including alerting communities to natural hazards and climate-related risks.”

The decision to launch JGR: Machine Learning and Computation follows a growing body of research in the field, evidenced by dedicated special collections and meetings. In 2022, more than 500 manuscripts submitted across AGU journals and more than 1700 abstracts submitted to AGU22 contained the index terms “machine learning” or “artificial intelligence.” The journal was proposed by members of AGU’s Nonlinear Geophysics Section and received vocal approval in discussions with the AGU Council and editors of AGU journals.

“There came a point when special collections were not enough,” said Enrico Camporeale, founding editor-in-chief of JGR: Machine Learning and Computation and research scientist at the University of Colorado Boulder. “JGR: Machine Learning and Computation fills a crucial gap for researchers utilizing machine learning or artificial intelligence in the Earth and space sciences. With this journal, we now have a dedicated platform for rigorous peer review of our research.”

JGR: Machine Learning and Computation is the 12th of 24 AGU journals to be fully open access. Open access journals remove the paywall that would require readers to have a paid subscription, thereby increasing equitable access to the latest advances among researchers and the public alike. AGU also offers various funding support for authors publishing in its fully open access journals, including full waivers. All accepted papers will be published regardless of the author’s ability to pay publication fees. AGU is a proud leader in open science, advancing the effort through publications, meetings, data leadership, community science, policy engagement and career development.

“The growth of machine learning goes hand-in-hand with the push to take more journals open access,” said Matthew Giampoala, AGU’s vice president of publications. “Both of these practices accelerate the speed of scientific discovery and inspire researchers to collaborate more broadly with their peers.”

AGU is currently seeking dynamic, well-organized scientists with high editorial standards to join the JGR: Machine Learning and Computation editorial board as editors and associate editors. Individuals interested in being considered should send a curriculum vitae with a letter of interest outlining qualifications for the position and interest in the journal to [email protected].

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  1. Xueshang Feng

    It is timely to launch such a journal. In space weather, data science, prediction method and ven my own field of numerical space weather modeling welcomes sych a journal devoted to ML. Recently, our research topic applies DL techniques combined with numerical space weather models to show the potentiality of ML.

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