GOES Imager Shows Diurnal Changes of a Trichodesmium erythraeum Bloom on the West Florida Shelf

Chuanmin Hu, Lian Feng

Research output: Contribution to journalArticlepeer-review

Abstract

The advantages of geostationary observations of sediment plumes and phytoplankton blooms have been reported for coastal waters in the southern North Sea and west Pacific. So far, similar observations have not been possible for the Gulf of Mexico where blooms of Trichodesmium erythraeum often occur. Here, using data collected by the Geostationary Operational Environmental Satellite (GOES) Imager, we document diurnal changes of a Trichodesmium bloom first identified by the Moderate Resolution Imaging Spectroradiometer (MODIS). Despite the low-signal-to-noise ratio ( ~ 46 : 1 for typical ocean radiance), the 550-750-nm band revealed clear patterns of Trichodesmium mats floating on the ocean surface and their temporal changes between 14:15 and 22:30 GMT on May 22, 2004. Normalization of the delineated bloom against the ocean background provided an effective atmospheric correction that enabled quantification of the changes in bloom size (i.e., area) and bloom intensity over the course of a day. The area coverage increased by about eightfold from midmorning (14-15 GMT) to reach its maximum around 18:30 GMT, whereas the mean intensity of the bloom area increased by ~ 22% from midmorning to 17:30 GMT. In the afternoon, while the bloom area remained relatively stable on the water surface, bloom intensity sharply decreased. These temporal patterns may be caused by physical aggregation and/or vertical migration of the Trichodesmium cells, and they agree well with the diurnal changes of a harmful algal bloom of the dinoflagellate Prorocentrum donghaiense in the East China Sea observed by the Geostationary Ocean Color Imager.

Original languageAmerican English
JournalIEEE Geoscience and Remote Sensing Letters
Volume11
DOIs
StatePublished - Aug 1 2014

Keywords

  • Oceans
  • Satellites
  • Sea measurements
  • Remote sensing
  • MODIS
  • Image color analysis
  • Signal to noise ratio

Disciplines

  • Life Sciences

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