Effects of typhoon and upwelling on Chlorophyll-a distribution in the northeastern coast of Hainan during Summer

Abstract

Typhoons or upwelling are thought to promote higher phytoplankton chlorophyll-a (Chl-a) concentration in many previous studies. However, the combined effects of typhoons and upwelling have been less studied in the South China Sea. Based on satellite remote sensing data, we investigated potential contributions of temperature-characterizing upwelling and typhoon events to Chl-a changes in the Hainan northeast area. Results showed that the Chl-a concentration was 0.80 mg m-3 at the coastal upwelling index (CUI) of 1.7°C in the summer of 2020 when there were no typhoons crossing the area. The CUI (1.01°C) of typhoon-influenced period in 2019 was 0.21°C higher than that of typhoon-free period in 2019. And the Chl-a also increased from 0.70 mg m-3 to 0.99 mg m-3. In comparison, during the typhoon-free period, with the higher CUI, there was the higher concentration of Chl-a. In addition, the typhoon affected Chl-a concentration is significantly higher than that in the other two typhoon-free periods of 2019 and 2020. Though the typhoon has a limited effect on the upwelling intensity, the Chl-a concentration is much higher than when the upwelling acts alone. This is due to the combined effect of typhoon (vertical mixing and runoff) and upwelling. The above results indicate that upwelling dominated the changes in Chl-a concentration in the Hainan northeast upwelling area during the typhoon-free period. In contrast, strong vertical mixing and runoff dominated the changes of Chl-a concentration during the typhoon-influenced period in the above area.

Fig 1. Study area.

(a) A map of the South China Sea and (b) deep map of the coastal area of Hainan. Trapezoid in (b) is Hainan Northeast Upwelling (HNEU) area. The color bar is depth with coastal area of Hainan. The high-precision shoreline base-map data used in the map is derived from Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG), which is the U.S. Government material and is not subject to copyright protection within the United States.

Fig 2

Temperature and wind fields in July. Monthly climatology of (a) sea surface temperature (SST) and (c) wind speed (WS) averaged in July from 1998 to 2019, and (b) the summer (July) mean SST and (d) WS in 2020. The high-precision shoreline base-map data used in the map is derived from Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG), which is the U.S. Government material and is not subject to copyright protection within the United States.

Fig 3. Distribution of Chl-a concentration in July.

Monthly climatology of (a) chlorophyll-a (Chl-a) concentration averaged in July from 1998 to 2019 and (b) the summer (July) mean Chl-a concentration in 2020. The red dotted lines are the left and right partition lines of the HNEU area. The high-precision shoreline base-map data used in the map is derived from Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG), which is the U.S. Government material and is not subject to copyright protection within the United States.

Fig 4. Upwelling intensity comparison and Chl-a concentration difference plots.

Monthly average Coastal Upwelling Index (CUI) in (a) 2019 and (b) 2020, and (c) monthly average Chl-a concentration difference between 2019 and 2020 (Chl-a concentrations in 2019 minus Chl-a concentration in 2020) in the HNEU area in summer. The high-precision shoreline base-map data used in the map is derived from Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG), which is the U.S. Government material and is not subject to copyright protection within the United States.

Fig 5. Comparison of CUI and Chl-a concentration.

Comparative histogram of weekly average CUI and Chl-a concentration. Light blue columns are during typhoon crossing and one week after typhoon crossing in the summer of 2019. Dark blue columns are during the second to fourth week after typhoon crossing in the summer of 2019. Purple columns are 2020 corresponding to 2019 time period.

Fig 6. Correlation coefficients between CUI and Chl-a concentration.

(a) For the typhoon-influenced period in 2019. (b) For the typhoon-free time period in 2019, and (c) for the corresponding time period in 2020. The spatial average data from 3 periods was used here, based on an area of (0.04° × 0.04°) in the study region.

Fig 7. WS on the day of typhoon crossing.

Red line is path of typhoon MUN in the study area in the summer of 2019. The high-precision shoreline base-map data used in the map is derived from Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG), which is the U.S. Government material and is not subject to copyright protection within the United States.

Fig 8. Map of possible mechanisms affecting the ecological environment of the HNEU area.

(a) During the typhoon-influenced period and (b) during typhoon-free period.