Verification of seiching processes in a large and deep lake (Trichonis, Greece)

A computational analysis of the periods and structure of surface seiches of Lake Trichonis in Greece and its experimental verification from three simultaneous water gauge recordings, mounted along the shores in Myrtia, Panetolio and Trichonio is given. The first five theoretical modes are calculated with a finite difference code of tidal equations, which yield the eigenperiodes, co-range and co-tidal lines that are graphically displayed and discussed in detail.Experimental verifications are from recordings taken during spring. Visual observations of the record permit identification of the five lowest order modes, including inter station phase shift. Power spectral analysis of two time series and interstation phase difference and coherence spectra allow the identification of the same five modes. Agreement between the theoretically predicted and the experimentally determined periods was excellent for most of the calculated modes.

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Short-Term Covariability of Chlorophyll and Temperature in the St. Lawrence Estuary

Journal of the Fisheries Research Board of Canada ◽

10.1139/f79-081 ◽

1979 ◽

Vol 36 (5) ◽

pp. 568-573 ◽

Cited By ~ 16

Author(s):

S. Demers ◽

P. E. Lafleur ◽

L. Legendre ◽

C. L. Trump

Keyword(s):

Time Series ◽

Spectral Analysis ◽

Chlorophyll A ◽

Physiological State ◽

Power Spectral Analysis ◽

Tidal Energy ◽

Lawrence Estuary ◽

Power Spectral ◽

Chlorophyll Distribution ◽

St Lawrence Estuary

Time series of chlorophyll a fluorescence and temperature taken at a depth of 1 m were recorded at 4-min intervals for 136.5 h, at an anchor station located in the Middle Estuary of the St. Lawrence. The sampling program was carried out during the transition from neap tides to spring tides. Power spectral analysis was applied to the series and variance spectra were estimated. Coherency spectra between fluorescence and temperature were also computed. Results indicate that chlorophyll distribution was controlled by physical processes during neap tides. Conversely, lesser amounts of chlorophyll a per cell and lesser primary production rates were noted during spring tides. A flattening of the chlorophyll spectrum was observed for this part of the study. This result was interpreted in terms of the poor physiological state of the phytoplankton population that was sampled during the second part of the study, a different density structure being present due to the change in tidal energy. Key words: time series, chlorophyll, temperature, spectral analysis, St. Lawrence Estuary

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Autoregressive (AR) based power spectral analysis of heart rate time series signal (HRTS signal)

TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region ◽

10.1109/tencon.2003.1273146 ◽

2004 ◽

Cited By ~ 1

Author(s):

V.P.S. Naidu ◽

M.R.S. Reddy

Keyword(s):

Heart Rate ◽

Time Series ◽

Spectral Analysis ◽

Power Spectral Analysis ◽

Power Spectral

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Power Spectral Analysis of Cosmic Ray Time Series Data over a Wide Rigidity Range.

Journal of geomagnetism and geoelectricity ◽

10.5636/jgg.47.1093 ◽

1995 ◽

Vol 47 (11) ◽

pp. 1093-1096

Author(s):

Shinichi Yasue ◽

Kazuoki Munakata ◽

Yoichi Tomi ◽

Satoru Mori ◽

Zenjiro Fujii ◽

...

Keyword(s):

Time Series ◽

Spectral Analysis ◽

Time Series Data ◽

Power Spectral Analysis ◽

Cosmic Ray ◽

Series Data ◽

Power Spectral

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Time-variant power spectral analysis of heart-rate time series by autoregressive moving average (ARMA) method

Sadhana ◽

10.1007/bf02703813 ◽

2003 ◽

Vol 28 (6) ◽

pp. 1027-1035

Author(s):

V P S Naidu ◽

M R S Reddy

Keyword(s):

Heart Rate ◽

Time Series ◽

Spectral Analysis ◽

Moving Average ◽

Power Spectral Analysis ◽

Autoregressive Moving Average ◽

Power Spectral

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CROSS‐SPECTRAL ANALYSIS USING MAXIMUM ENTROPY

Geophysics ◽

10.1190/1.1440433 ◽

1974 ◽

Vol 39 (3) ◽

pp. 353-354 ◽

Cited By ~ 15

Author(s):

Tad Ulrych ◽

Oliver Jensen

Keyword(s):

Time Series ◽

Spectral Analysis ◽

Maximum Entropy ◽

Maximum Entropy Method ◽

Power Spectral Analysis ◽

Entropy Method ◽

Considerable Success ◽

Power Spectral ◽

Bivariate Time Series

A great deal of interest has been shown in the maximum entropy method (MEM) of power spectral analysis originally suggested by Burg (1967, 1968). The application of MEM to problems of geophysical and astronomical interest has met with considerable success (Ulrych, 1972; Ulrych et al., 1973; Smylie et al., 1973; Currie, 1973a, b; and Jensen and Ulrych, 1973). We have recently received a number of enquiries concerning the possibility of computing maximum entropy crosspower spectra. The purpose of this note is to present a method of determining the MEM crosspower spectrum from a knowledge of the MEM autopower spectra of the bivariate time series.

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