Dr Enrico Camporeale, Senior Lecturer in QMUL’s Astronomy Unit, has become the founding editor-in-chief of the new journal Journal of Geophysical Research (JGR): Machine Learning and Computation
The journal, published by the American Geophysical Union (AGU) was launched in November 2023 and has just opened for submissions.
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.”
For more information see the full AGU Press Release.