气候变化领域集成服务门户(CCPortal): Best practice strategies for process studies designed to improve climate modeling

CCPortal

DOI	10.1175/BAMS-D-19-0263.1
	Best practice strategies for process studies designed to improve climate modeling
	Sprintall J.; Coles V.J.; Reed K.A.; Butler A.H.; Foltz G.R.; Penny S.G.; Seo H.
发表日期	2020
ISSN	00030007
起始页码	E1842
结束页码	E1850
卷号	101 期号:10
英文摘要	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. ©2020 American Meteorological Society
语种	英语
scopus关键词	Information management; Climate variability; Continual communication; Field campaign; In-situ observations; Physical process; Research models; Scientific data management; Social identity; Climate models
来源期刊	Bulletin of the American Meteorological Society
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/177794
作者单位	Scripps Institution of Oceanography, University of California, San Diego, San diego, CA, United States; Horn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD, United States; School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, NY, United States; NOAA Chemical Sciences Laboratory, Boulder, CO, United States; NOAA, Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, United States; Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, NOAA/Physical Sciences Laboratory, Boulder, CO, United States; Woods Hole Oceanographic Institution, Woods Hole, MA, United States
推荐引用方式 GB/T 7714	Sprintall J.,Coles V.J.,Reed K.A.,et al. Best practice strategies for process studies designed to improve climate modeling[J],2020,101(10).
APA	Sprintall J..,Coles V.J..,Reed K.A..,Butler A.H..,Foltz G.R..,...&Seo H..(2020).Best practice strategies for process studies designed to improve climate modeling.Bulletin of the American Meteorological Society,101(10).
MLA	Sprintall J.,et al."Best practice strategies for process studies designed to improve climate modeling".Bulletin of the American Meteorological Society 101.10(2020).