Artificial Intelligence for the Earth Systems

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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Scope

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

Submission Types

  • 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


Chief Editor

Amy McGovern, University of Oklahoma


Editors

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