globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-16-0670.1
Scopus记录号: 2-s2.0-85017095579
论文题名:
Characterizing large-scale meteorological patterns and associated temperature and precipitation extremes over the northwestern United States using self-organizing maps
作者: Loikith P.C.; Lintner B.R.; Sweeney A.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期:8
起始页码: 2829
结束页码: 2847
语种: 英语
Scopus关键词: Atmospheric pressure ; Atmospheric temperature ; Climate change ; Climate models ; Climatology ; Conformal mapping ; Atmospheric circulation ; Climate variability ; Extreme events ; North America ; Seasonal variability ; Synoptic climatology ; Self organizing maps
英文摘要: The self-organizing maps (SOMs) approach is demonstrated as a way to identify a range of archetypal large-scale meteorological patterns (LSMPs) over the northwestern United States and connect these patterns with local-scale temperature and precipitation extremes. SOMs are used to construct a set of 12 characteristic LSMPs (nodes) based on daily reanalysis circulation fields spanning the range of observed synoptic-scale variability for the summer and winter seasons for the period 1979-2013. Composites of surface variables are constructed for subsets of days assigned to each node to explore relationships between temperature, precipitation, and the node patterns. The SOMs approach also captures interannual variability in daily weather regime frequency related to El Niño-Southern Oscillation. Temperature and precipitation extremes in high-resolution gridded observations and in situ station data show robust relationships with particular nodes in many cases, supporting the approach as a way to identify LSMPs associated with local extremes. Assigning days from the extreme warm summer of 2015 and wet winter of 2016 to nodes illustrates how SOMs may be used to assess future changes in extremes. These results point to the applicability of SOMs to climate model evaluation and assessment of future projections of local-scale extremes without requiring simulations to reliably resolve extremes at high spatial scales. © 2017 American Meteorological Society.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49722
Appears in Collections:气候变化事实与影响

Files in This Item:

There are no files associated with this item.


作者单位: Department of Geography, Portland State University, Portland, OR, United States; Department of Environmental Sciences, Rutgers, NJ, United States; The State University of New Jersey, New Brunswick, NJ, United States; School of the Environment, Portland State University, Portland, OR, United States

Recommended Citation:
Loikith P.C.,Lintner B.R.,Sweeney A.. Characterizing large-scale meteorological patterns and associated temperature and precipitation extremes over the northwestern United States using self-organizing maps[J]. Journal of Climate,2017-01-01,30(8)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Loikith P.C.]'s Articles
[Lintner B.R.]'s Articles
[Sweeney A.]'s Articles
百度学术
Similar articles in Baidu Scholar
[Loikith P.C.]'s Articles
[Lintner B.R.]'s Articles
[Sweeney A.]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Loikith P.C.]‘s Articles
[Lintner B.R.]‘s Articles
[Sweeney A.]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.