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    Best practice strategies for process studies designed to improve climate modeling

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    Article (1.418Mb)
    Date
    2020-10-01
    Author
    Sprintall, Janet  Concept link
    Coles, Victoria J.  Concept link
    Reed, Kevin A.  Concept link
    Butler, Amy H.  Concept link
    Foltz, Gregory R.  Concept link
    Penny, Stephen G.  Concept link
    Seo, Hyodae  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/26724
    As published
    https://doi.org/10.1175/BAMS-D-19-0263.1
    DOI
    10.1175/BAMS-D-19-0263.1
    Abstract
    Process studies are designed to improve our understanding of poorly described physical processes that are central to the behavior of the climate system. They typically include coordinated efforts of intensive field campaigns in the atmosphere and/or ocean to collect a carefully planned set of in situ observations. Ideally the observational portion of a process study is paired with numerical modeling efforts that lead to better representation of a poorly simulated or previously neglected physical process in operational and research models. This article provides a framework of best practices to help guide scientists in carrying out more productive, collaborative, and successful process studies. Topics include the planning and implementation of a process study and the associated web of logistical challenges; the development of focused science goals and testable hypotheses; and the importance of assembling an integrated and compatible team with a diversity of social identity, gender, career stage, and scientific background. Guidelines are also provided for scientific data management, dissemination, and stewardship. Above all, developing trust and continual communication within the science team during the field campaign and analysis phase are key for process studies. We consider a successful process study as one that ultimately will improve our quantitative understanding of the mechanisms responsible for climate variability and enhance our ability to represent them in climate models.
    Description
    Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(10), (2020): E1842-E1850, doi:10.1175/BAMS-D-19-0263.1.
    Publisher Embargo:
    The publisher requires that this item be embargoed until 2021-04-01. Please check back after 2021-04-01.
    Collections
    • Physical Oceanography (PO)
    Suggested Citation
    Sprintall, J., Coles, V. J., Reed, K. A., Butler, A. H., Foltz, G. R., Penny, S. G., & Seo, H. (2020). Best practice strategies for process studies designed to improve climate modeling. Bulletin of the American Meteorological Society, 101(10), E1842-E1850. doi:10.1175/BAMS-D-19-0263.1. Sprintall, J., Coles, V. J., Reed, K. A., Butler, A. H., Foltz, G. R., Penny, S. G., & Seo, H. (2020). Best practice strategies for process studies designed to improve climate modeling. Bulletin of the American Meteorological Society, 101(10), E1842-E1850.
     
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