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Investigation of the island-induced ocean vortex train of the Kuroshio Current using satellite imagery
- Source :
- Remote Sensing of Environment. 193:54-64
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- In this study, we used satellite imagery to conduct a statistical study of the ocean vortex train induced by the Kuroshio Current on the leeward side of Green Island, Taiwan. The spatial scale and characteristics of the ocean vortex train were analyzed using image datasets from five different high-resolution satellites, including optical imagery from the Satellite Pour l'Observation de la Terre and the Formosat-2 satellites and synthetic aperture radar imagery from the European Remote Sensing Satellite, Advanced Land Observing Satellite, and Sentinel-1. Satellite altimetry data and a moored acoustic Doppler current profiler (ADCP) were used to calculate the velocity of the Kuroshio Current. The ADCP data suggest that the velocity increases on the western side of the vortex train when it is formed on the leeward side of Green Island. Data from the moderate-resolution imaging spectroradiometer (MODIS) showed that the sea surface temperature of the recirculation water was over 2 °C colder and the chlorophyll-a concentration was two times higher than that of the surrounding waters. These phenomena suggested upwelling, mixing processes, and an island-mass effect. Wind forcing had a pronounced effect on the characteristics of the vortex train. High-resolution satellite images indicate that the averaged aspect ratio of the vortex train is 2.09 and the dimensionless width is 2.02 under southerly winds, compared to 1.91 and 2.76, respectively, under northerly winds.
- Subjects :
- 010504 meteorology & atmospheric sciences
Meteorology
010505 oceanography
Soil Science
Geology
01 natural sciences
Vortex
European Remote-Sensing Satellite
Sea surface temperature
Spectroradiometer
Acoustic Doppler current profiler
Climatology
Upwelling
Satellite imagery
Satellite
Computers in Earth Sciences
0105 earth and related environmental sciences
Remote sensing
Subjects
Details
- ISSN :
- 00344257
- Volume :
- 193
- Database :
- OpenAIRE
- Journal :
- Remote Sensing of Environment
- Accession number :
- edsair.doi...........0f42612dc1ccc77d461b5799dd325540