Treffer: A sequential algorithm for testing climate regime shifts

Title:
A sequential algorithm for testing climate regime shifts
Authors:
RODIONOV, Sergei N
Source:
Geophysical research letters. 31(9):L09204.1-L09204.4
Publisher Information:
Washington, DC: American Geophysical Union, 2004.
Publication Year:
2004
Physical Description:
print,
Original Material:
INIST-CNRS
Subject Terms:
Astronomy earth cosmic environment, Astronomie et environnement cosmique terrestre, Geophysics, Géophysique, Climatology, meteorology, Climatologie, météorologie, Oceanography, Océanographie, Sciences exactes et technologie, Exact sciences and technology, Terre, ocean, espace, Earth, ocean, space, Algorithme, algorithms, Algoritmo, Anomalie, anomalies, Anomalía, Climat, climate, Clima, Discontinuité, discontinuities, Discontinuidad, Détection, detection, Expérimentation, testing, Performance, Rendimiento, Surveillance, monitoring, Vigilancia, Série temporelle, Time series, Serie temporal, Timing
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington, United States
ISSN:
0094-8276
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=15871011
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Astronomy

External geophysics
Accession Number:
edscal.15871011
Database:
PASCAL Archive

Weitere Informationen

Empirical studies of climate regime shifts typically use confirmatory statistical techniques with an a priori hypothesis about the timing of the shifts. Although there are methods for an automatic detection of discontinuities in a time series, their performance drastically diminishes at the ends of the series. Since all the methods currently available require a substantial amount of data to be accumulated, the regime shifts are usually detected long after they actually occurred. The proposed sequential algorithm allows for early detection of a regime shift and subsequent monitoring of changes in its magnitude over time. The algorithm can handle the incoming data regardless whether they are presented in the form of anomalies or absolute values. It can be easily used for an automatic calculation of regime shifts in large sets of variables.