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Variability in near‐surface particulate absorption spectra: What can a satellite ocean color imager see?
Author(s) -
Garver Sara A.,
Siegel David A.,
B. Greg Mitchell
Publication year - 1994
Publication title -
limnology and oceanography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.7
H-Index - 197
eISSN - 1939-5590
pISSN - 0024-3590
DOI - 10.4319/lo.1994.39.6.1349
Subject(s) - ocean color , empirical orthogonal functions , particulates , phytoplankton , environmental science , chlorophyll a , absorption (acoustics) , satellite , atmospheric sciences , biomass (ecology) , chemistry , oceanography , climatology , geology , optics , physics , nutrient , organic chemistry , astronomy , biochemistry
An extensive database of ∼400 in situ particulate absorption spectra [ a p (λ)] is analyzed to assess the potential of using ocean color imagers to examine variability in the structure of the near‐surface ocean planktonic ecosystem. This application of a p (λ) data is appropriate, as particulate absorption variations are the dominant source of ocean color variation and are attributable to changes in the phytoplankton community structure. Empirical orthogonal function (EOF) analyses are used to estimate the contribution of each statistical mode to the total variance. The EOF analyses showed that >99% of the variance found in the a p (λ) data set can be simply attributed to the total amount of particulate material. When this source of variability is removed, two significant modes of variability can be identified which comprise 79 and 18% of the normalized variance. These modes are interpreted as representing the relative contribution of chlorophyll‐containing biomass and detrital materials, verifying the use of two‐component phytoplankton‐detritus models to partition a p (λ). Only a small amount of the total a p (λ) variability (<0.5% of the total) can be attributed to absorption features caused by accessory pigment groups. Thus, variability in a p (λ) is almost entirely associated with the quantity of the absorbing materials rather than their spectral quality (or normalized spectral shape). These results suggest that remotely sensed ocean color spectra will reflect only three statistically significant components: the total amount of particulate material, the relative amounts of chlorophyll‐containing biomass, and detrital materials. For most typical conditions it is unlikely that robust global algorithms for determining particular phytoplankton groups can be developed from remotely sensed ocean color spectra.