DOI: 10.1175/JCLI-D-16-0798.1
Scopus记录号: 2-s2.0-85027253133
论文题名: Archetypal analysis: Mining weather and climate extremes
作者: Hannachi A. ; Trendafilov N.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期: 17 起始页码: 6927
结束页码: 6944
语种: 英语
Scopus关键词: Atmospheric thermodynamics
; Constrained optimization
; Meteorology
; Nickel
; Oceanography
; Optimization
; Pattern recognition
; Probability distributions
; Sea level
; Surface waters
; Archetypal analysis
; Asian summer monsoons
; Constrained least squares
; Conventional analysis method
; Optimization algorithms
; Pattern detection
; Sea surface temperature (SST)
; Western boundary currents
; Least squares approximations
英文摘要: Conventional analysis methods in weather and climate science (e.g., EOF analysis) exhibit a number of drawbacks including scaling and mixing. These methods focus mostly on the bulk of the probability distribution of the system in state space and overlook its tail. This paper explores a different method, the archetypal analysis (AA), which focuses precisely on the extremes. AA seeks to approximate the convex hull of the data in state space by finding "corners" that represent "pure" types or archetypes through computing mixture weight matrices. The method is quite new in climate science, although it has been around for about two decades in pattern recognition. It encompasses, in particular, the virtues of EOFs and clustering. The method is presented along with a new manifold-based optimization algorithm that optimizes for the weights simultaneously, unlike the conventional multistep algorithm based on the alternating constrained least squares. The paper discusses the numerical solution and then applies it to the monthly sea surface temperature (SST) from HadISST and to the Asian summer monsoon (ASM) using sea level pressure (SLP) from ERA-40 over the Asian monsoon region. The application to SST reveals, in particular, three archetypes, namely, El Niño, La Niña, and a third pattern representing the western boundary currents. The latter archetype shows a particular trend in the last few decades. The application to the ASM SLP anomalies yields archetypes that are consistent with the ASM regimes found in the literature. Merits and weaknesses of the method along with possible future development are also discussed. © 2017 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49896
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Meteorology, Stockholm University, Stockholm, Sweden; Department of Mathematics and Statistics, The Open University, Milton Keynes, United Kingdom
Recommended Citation:
Hannachi A.,Trendafilov N.. Archetypal analysis: Mining weather and climate extremes[J]. Journal of Climate,2017-01-01,30(17)