Artificial Intelligence for the Earth Systems (AIES) will begin accepting submissions for peer review in the fall of 2021. Check back here or submit your name for updates.
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Artificial Intelligence for the Earth Systems (AIES) (Provisional ISSN: 2769-7525) publishes research on the development and application of methods in Artificial Intelligence (AI), Machine Learning (ML), data science, and statistics that is relevant to meteorology, atmospheric science, hydrology, climate science, and ocean sciences. Topics include:
- Development of AI/ML, statistical, and hybrid methods and their application
- Development and application of methods to further the physical understanding of earth system processes from AI/ML models such as explainable and physics-based AI
- The use of AI/ML to emulate components of numerical weather and climate models
- Incorporation of AI/ML into observation and remote sensing platforms
- The use of AI/ML for data assimilation and uncertainty quantification
- Societal applications of AI/ML for AIES disciplines, including ethical and responsible use of AI/ML and educational research on AI/ML
- Articles: Up to 7500 words (approximately 26 double-spaced pages), including the body text, acknowledgments, and appendixes. The word limit does not include the title page, abstract, references, captions, tables, and figures. If a submission exceeds the word limit, the author must provide a justification for the length of the manuscript and request the Chief Editor’s approval of the overage. This request may be uploaded in a document with the "Cover Letter" item type or entered in the comment field in the submission system.
- Reviews: Synthesis of previously published literature that may address successes, failures, and limitations. Requires Review Proposal. For more information, see Review Articles.
- Comment and Reply Exchange: Comments are written in response to a published article and should be submitted within 2 years of the publication date of the original article (although the editor can waive this limit in extenuating circumstances). The author of the original article has the opportunity to write a Reply. These exchanges are published together.
- Corrigenda: The corrigendum article type is available for authors to address errors discovered in already published articles. For more information, see Corrigenda.
Editors and Staff Contacts
Amy McGovern, University of Oklahoma
John T. Allen, Central Michigan University
William F. Campbell, U.S. Naval Research Laboratory
Scott M. Collis, Argonne National Laboratory
David John Gagne II, NCAR
Ruoying He, North Carolina State University
Michael Scheuerer, Norwegian Computing Center, NR
Haruko Murakami Wainwright, Lawrence Berkeley National Laboratory
Peer Review Support Staff
Andrea Herbst-Horner, Assistant to Amy McGovern