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| Titel |
On the consistency of MODIS chlorophyll a products in the northern South China Sea |
| VerfasserIn |
S. L. Shang, Q. Dong, C. M. Hu, G. Lin, Y. H. Li, S. P. Shang |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 11, no. 2 ; Nr. 11, no. 2 (2014-01-22), S.269-280 |
| Datensatznummer |
250117141
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| Publikation (Nr.) |
 copernicus.org/bg-11-269-2014.pdf |
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| Zusammenfassung |
| Chlorophyll a (Chl) concentrations derived from satellite measurements have
been used in oceanographic research, for example to interpret eco-responses
to environmental changes on global and regional scales. However, it is
unclear how existing Chl products compare with each other in terms of
accuracy and consistency in revealing temporal and spatial patterns,
especially in the optically complex marginal seas. In this study, we examined
three MODIS (Moderate Resolution Imaging Spectroradiometer) Chl data products
that have been made available to the community by the US National Aeronautics
and Space Administration (NASA) using community-accepted algorithms and
default parameterization. These included the products derived from the OC3M
(ocean chlorophyll three-band algorithm for MODIS), GSM
(Garver–Siegel–Maritorena model) and GIOP (generalized inherent optical
properties) algorithms. We compared their temporal variations and spatial
distributions in the northern South China Sea. We found that the three
products appeared to capture general features such as unique winter peaks at
the Southeast Asian Time-series Study station (SEATS, 18° N,
116° E) and the Pearl River plume associated blooms in summer. Their
absolute magnitudes, however, may be questionable in the coastal zones.
Additional error statistics using field measured Chl as the truth
demonstrated that the three MODIS Chl products may contain high degree of
uncertainties in the study region. Root mean square error (RMSE) of the
products from OC3M and GSM (on a log scale) was about 0.4 and average
percentage error (ε) was ~ 115% (Chl between
0.05–10.41 mg m−3, n = 114). GIOP with default parameterization led
to higher errors (ε = 329%). An attempt to tune the
algorithms based on a local coastal-water bio-optical data set led to reduced
errors for Chl retrievals, indicating the importance of local tuning of
globally-optimized algorithms. Overall, this study points to the need of
continuous improvements for algorithm development and parameterization for
the coastal zones of the study region, where quantitative interpretation of
the current Chl products requires extra caution. |
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