Deep-water chlorophyll concentration global time series fluctuation

T. Holden; D. Sunil; E. Cheung; D. Cotten; D. Klarberg; G. Tremberger Jr.; T. Nasar; J. Taylor; P. Marchese; T. Cheung

doi:10.1117/12.825807

19 August 2009 Deep-water chlorophyll concentration global time series fluctuation

T. Holden, D. Sunil, E. Cheung, D. Cotten, D. Klarberg, G. Tremberger Jr., T. Nasar, J. Taylor, P. Marchese, T. Cheung

Proceedings Volume 7459, Ocean Remote Sensing: Methods and Applications; 74590O (2009) https://doi.org/10.1117/12.825807
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

The deep water chlorophyll concentration fluctuation from 2003 to 2007 has been studied using fractal analysis. The SeaWiFS global daily mean chlorophyll concentration time series were used. The Higuchi fractal algorithm was used to calculate fractal dimension, which is given by the slope of an associated length versus the lag. Short range fluctuation investigation using a six point slope gives fractal dimensions from 1.80 to 1.85, suggesting the presence of correlation, which was confirmed by computer simulations. The gradual increase of fractal dimension to 1.9 in about 15 lag-days suggests that a long-range de-correlation mechanism favoring random fluctuation is present. The 2007 times series shows a relatively low overall fractal dimension and exhibits a peculiar multi-fractal behavior. This phenomenon and the observed low accumulated cyclone energy in 2007 support the interpretation that cyclone energy can promote deep-water chlorophyll concentration fluctuation. A regression of fractal dimension at 10 lag-days versus the log of cyclone energy gives an R² value of 0.75 (N = 5)., which suggests the presence of additional or related de-correlation mechanisms.

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T. Holden, D. Sunil, E. Cheung, D. Cotten, D. Klarberg, G. Tremberger Jr., T. Nasar, J. Taylor, P. Marchese, and T. Cheung "Deep-water chlorophyll concentration global time series fluctuation", Proc. SPIE 7459, Ocean Remote Sensing: Methods and Applications, 74590O (19 August 2009); https://doi.org/10.1117/12.825807

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KEYWORDS

Fractal analysis

Calibration

Satellites

Wind energy

Climatology

Computer simulations

Autoregressive models

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