EGU2020-17939
https://doi.org/10.5194/egusphere-egu2020-17939
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Scaling Analysis of the Algal Blooms

Yongxiang Huang1,2,3, Yang Gao1,2, Qianguo Xing4, Francois Schmitt2, and Jianyu Hu1,3
Yongxiang Huang et al.
  • 1State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361102 China
  • 2CNRS, Univ. Lille, Univ. Littoral Cote d’Opale, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, F 62930 Wimereux, France
  • 3Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
  • 4Yantai Institute of Coastal Zone Research Chinese Academy of Sciences, Yantai, Shandong 264003, China

Algal blooms, also known as ‘red tide’, are extremely harmful to the marine ecosystem since they infuse toxins into seawater and stifle oxygen in the water columns. Visually, they demonstrate rich patterns in spatial due to the interaction between the ocean current and the wind. Using the satelliate remote sensing data provided by the Chinese satellite Gaofeng 1, we first derive a normalized difference vegetation index (NDVI), which can be used to separate efficiently different types of cases, e.g., no algae bloom (NAB), macro algae bloom (MAB), and phytoplankton algae bloom (PAB), etc. The classical structure-function analysis is performed. Our preliminary results confirm the existence of the power-law behavior on the spatial scale range from 100 m to 400 m for the case of MAB. The corresponding scaling exponents are close to the ones of the classical passive scalar in three-dimension hydrodynamic turbulence. It suggests that the MAB could be treated as a passive scalar, which leads to not only a better understanding of the dynamics of algal blooms, but also a challenge of the modelling.

How to cite: Huang, Y., Gao, Y., Xing, Q., Schmitt, F., and Hu, J.: Scaling Analysis of the Algal Blooms, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17939, https://doi.org/10.5194/egusphere-egu2020-17939, 2020.

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