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dc.contributor.authorSprintall, Janet  Concept link
dc.contributor.authorColes, Victoria J.  Concept link
dc.contributor.authorReed, Kevin A.  Concept link
dc.contributor.authorButler, Amy H.  Concept link
dc.contributor.authorFoltz, Gregory R.  Concept link
dc.contributor.authorPenny, Stephen G.  Concept link
dc.contributor.authorSeo, Hyodae  Concept link
dc.date.accessioned2021-02-19T21:27:02Z
dc.date.issued2020-10-01
dc.identifier.citationSprintall, 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.en_US
dc.identifier.urihttps://hdl.handle.net/1912/26724
dc.descriptionAuthor 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.en_US
dc.description.abstractProcess 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.en_US
dc.description.sponsorshipWe gratefully acknowledge U.S. CLIVAR for supporting the PSMI panel, as well as all the principal investigators that contributed to our PSMI panel webinars. JS was inspired by participation in the process studies funded by NASA NNH18ZDA001N-OSFC and NOAA NA17OAR4310257; GF was supported by base funds to NOAA/AOML’s Physical Oceanography Division; and HS was supported by NOAA NA19OAR4310376 and NA17OAR4310255.en_US
dc.publisherAmerican Meteorological Societyen_US
dc.relation.urihttps://doi.org/10.1175/BAMS-D-19-0263.1
dc.titleBest practice strategies for process studies designed to improve climate modelingen_US
dc.typeArticleen_US
dc.description.embargo2021-04-01en_US
dc.identifier.doi10.1175/BAMS-D-19-0263.1
dc.embargo.liftdate2021-04-01


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