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Phytoplankton size class in the East China Sea derived from MODIS satellite data.
Phytoplankton size class in the East China Sea derived from MODIS satellite data.
- Source :
- Biogeosciences Discussions; 2018, p1-37, 37p
- Publication Year :
- 2018
-
Abstract
- The distribution of the phytoplankton size class (PSC) and the variations in the size classes are key to understanding ocean biogeochemical processes and ecosystem. Remote sensing of the PSC in the East China Sea (ECS) remains a challenge, although many PSC algorithms have been developed. Here based on a local dataset from the ECS, a regional model was tuned to infer the PSC from the spectral features of normalized phytoplankton absorption (α<subscript>ph</subscript>) using a principal component analysis approach. Before applying the refined model to the real MODIS (Moderate Resolution Imaging Spectroradiometer) data, reconstructing satellite R<subscript>rs</subscript> at 412 and 443 nm becomes critical through modeling them from R<subscript>rs</subscript> between 469 and 555 nm using multiple regression analyses. Satellite-derived PSC values compare well with those derived from pigment composition, which demonstrates the potential of satellite ocean color data to estimate PSC distributions in the ECS from space. The refined model was applied to α<subscript>ph</subscript> derived from R<subscript>rs</subscript> observations collected by MODIS over the ECS from 2003 to 2016. Seasonal images show that the PSC distribution was heterogeneous in both temporal and spatial scales. Seasonal variations of the PSC in the ECS were probably affected by a combination of the water column stability, upwelling, sea surface temperature, and the Kuroshio Current. Additionally, human activity and riverine discharge may also influence the PSC distributions in the ECS, especially in coastal regions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18106277
- Database :
- Complementary Index
- Journal :
- Biogeosciences Discussions
- Publication Type :
- Academic Journal
- Accession number :
- 128259014
- Full Text :
- https://doi.org/10.5194/bg-2017-508