An EMD and PCA hybrid approach for separating noise from signal, and signal in climate change detection

International Journal of Climatology

Volumn 32, Issue 4, 2012, Pages 624-634

  Lee, Taesam ^a   Ouarda, T B M J ^b,c  

^a Gyeongsang National University   (South Korea)

^b KHALIFA UNIVERSITY   (United Arab Emirates)

^c CENTRE EAU TERRE ENVIRONNEMENT   (Canada)

Author keywords

Background noise; Climate change detection; Empirical mode decomposition; Global surface temperature anomaly

Indexed keywords

BACKGROUND NOISE; CLIMATE CHANGE DETECTION; CLIMATE SIGNALS; DATA SETS; EMPIRICAL MODE DECOMPOSITION; FORCINGS; GLOBAL SURFACE TEMPERATURE; HIGH FREQUENCY COMPONENTS; HIGH FREQUENCY HF; HYBRID APPROACH; LOW-FREQUENCY COMPONENTS; OCEANIC CIRCULATIONS; RANDOM COMPONENTS; RANDOM NOISE; SIGNALTONOISE RATIO (SNR); SOLAR ACTIVITY; STATISTICAL DETECTION; SYNTHETIC APPLICATION;

ATMOSPHERIC TEMPERATURE; SIGNAL DETECTION; SOLAR ENERGY; SURFACE PROPERTIES;

CLIMATE CHANGE;

CLIMATE CHANGE; CLIMATE FORCING; CLIMATE MODELING; DECOMPOSITION ANALYSIS; DETECTION METHOD; EMPIRICAL ANALYSIS; SIGNAL PROCESSING; SIGNAL-TO-NOISE RATIO; SURFACE TEMPERATURE; TEMPERATURE ANOMALY;

EID: 84858295509     PISSN: 08998418     EISSN: 10970088     Source Type: Journal    
DOI: 10.1002/joc.2299     Document Type: Article

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