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Version 1

Data on the South China Sea and Xisha Islands (Chl-a, SST, Trajectories of tropical cyclones, fire points, bcaod and PAR).

Published:31 May 2024|Version 1|DOI:10.17632/zmzbpgfy59.1
Contributors:
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Description

Based on relevant data obtained from various types of remote sensing (Chl-a, SST, Trajectories of tropical cyclones, fire points, bcaod and PAR). The data has been used in the "Wildfire particulates enhance phytoplankton growth and alter communities in the South China Sea under wind-driven upwelling" article cited and analyzed. The data comes from multiple databases (Japan meteorological Agency, GlobColour, The NOAA's Physical Sciences Laboratory (PSL), Boulder, Colorado, USA, The CAMS Global Atmospheric Composition Predictions dataset, Fire Information for Resource Management System and NASA Prediction Of Worldwide Energy Resources).

Steps to reproduce

The required data can be downloaded from the given websites and institutions, and all data is registered for free access to data.

Institutions

Guangxi University

Categories

Biological Oceanography, Tropical Cyclone, Chlorophyll a

Funding

National Natural Science Foundation of China

42076157

National Natural Science Foundation of China

42090041

National Natural Science Foundation of China

42030502

Related Links

Licence

Creative Commons Attribution 4.0 International

Version 2

Data on the South China Sea (Chl-a, SST, Trajectories of tropical cyclones, fire points, bcaod and PAR).

Published:25 July 2024|Version 2|DOI:10.17632/zmzbpgfy59.2
Contributors:
,
,
,
,
,
,
,

Description

Based on relevant data obtained from various types of remote sensing (Chl-a, SST, Trajectories of tropical cyclones, fire points, bcaod and PAR). The data has been used in the "Wildfire particulates enhance phytoplankton growth and alter communities in the South China Sea under wind-driven upwelling" article cited and analyzed. The data comes from multiple databases (Japan meteorological Agency, GlobColour, The NOAA's Physical Sciences Laboratory (PSL), Boulder, Colorado, USA, The CAMS Global Atmospheric Composition Predictions dataset, Fire Information for Resource Management System and NASA Prediction Of Worldwide Energy Resources).

Steps to reproduce

The required data can be downloaded from the given websites and institutions, and all data is registered for free access to data.

Institutions

Guangxi University

Categories

Biological Oceanography, Tropical Cyclone, Chlorophyll a

Funding

National Natural Science Foundation of China

42090041

National Natural Science Foundation of China

42076157

National Natural Science Foundation of China

42030502

Related Links

Licence

Creative Commons Attribution 4.0 International