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Quantification of Typhoon-Induced Phytoplankton Blooms Using Satellite Multi-Sensor Data

1
School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
2
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
3
Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518057, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(2), 318; https://doi.org/10.3390/rs10020318
Received: 19 December 2017 / Revised: 13 February 2018 / Accepted: 16 February 2018 / Published: 20 February 2018
(This article belongs to the Special Issue Remote Sensing of Target Detection in Marine Environment)
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Abstract

Using satellite-based multi-sensor observations, this study investigates Chl-a blooms induced by typhoons in the Northwest Pacific (NWP) and the South China Sea (SCS), and quantifies the blooms via wind-induced mixing and Ekman pumping parameters, as well as pre-typhoon mixed-layer depth (MLD). In the NWP, the Chl-a bloom is more correlated with the Ekman pumping than with the other two parameters, with an R2 value of 0.56. In the SCS, the wind-induced mixing and Ekman pumping have comparable correlations with the Chl-a increase, showing R2 values of 0.4~0.6. However, the MLD exhibits a negative correlation with the Chl-a increase. A multi-parameter quantification model of the Chl-a bloom strength achieves better results than the single-parameter regressions, yielding a more significant R2 value of 0.80, and a lower regression rms of 0.18 mg·m−3 in the SCS, and the R2 value in the NWP is also improved compared with the single-parameter regressions. The multi-parameter quantification model of Chl-a blooms is more accurate in the SCS than in the NWP, due to the fact that nutrient profiles in the NWP are uniform from surface to a deep depth (300 m). Thus, the Chl-a blooms are more correlated with the upper ocean dynamical processes in the SCS where a shallower nutricline is found. View Full-Text
Keywords: phytoplankton bloom; typhoon; wind forcing; ekman pumping; mixed-layer depth phytoplankton bloom; typhoon; wind forcing; ekman pumping; mixed-layer depth
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Pan, J.; Huang, L.; Devlin, A.T.; Lin, H. Quantification of Typhoon-Induced Phytoplankton Blooms Using Satellite Multi-Sensor Data. Remote Sens. 2018, 10, 318.

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