Frontiers in Marine Science (Jun 2023)

Oceanic and ecological response to native Typhoons Cempaka and Lupit (2021) along the northern South China Sea continental shelf: comparison and evaluation of global and regional Operational Oceanography Forecasting Systems

  • Shaojing Guo,
  • Xueming Zhu,
  • Xuanliang Ji,
  • Hui Wang,
  • Hui Wang,
  • Shouwen Zhang,
  • Hua Jiang,
  • Dan Wang,
  • Dan Wang

DOI
https://doi.org/10.3389/fmars.2023.1175263
Journal volume & issue
Vol. 10

Abstract

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The Global Operational Oceanography Forecasting System from the Mercator Ocean (MO) and the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv2) were compared and evaluated using in situ and satellite observations, with a focus on the oceanic and ecological response to two consecutive native typhoons, Cempaka and Lupit, that occurred in July–August 2021. Results revealed a better simulation of the chlorophyll a (Chla) structure by SCSOFSv2 and a better simulation of the temperature profile by MO in the Pearl River Estuary. In addition, SCSOFSv2 sea surface temperature (SST) and MO Chla variations corresponded well with observations along the northern SCS shelf. Simulated maximum SST cooling was larger and 2–3 days earlier than those observations. Maximum Chla was stronger and led the climatological average by 2 days after the typhoon passage. Typhoon-induced vertical variations of Chla and NO3 indicated that different Chla bloom processes from coastal waters to the continental shelf. Discharge brought extra nutrients to stimulate Chla bloom in coastal waters, and model results revealed that its impact could extend to the continental shelf 50–150 km from the coastline. However, bottom nutrients were uplifted to contribute to Chla enhancement in the upper and middle layers of the shelf. Nutrients transported from the open sea along the continental slope with the bottom cold water could trigger Chla enhancement in the Taiwan Bank. This study suggests considering strong tides and waves as well as regional dynamics to improve model skills in the future.

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