Net community production in the South China Sea Basin estimated from in situ O2 measurements on an Argo profiling float

Yibin Huang, Bo Yang, Bingzhang Chen, Guoqiang Qiu, Haili Wang, Bangqin Huang

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8 Citations (Scopus)

Abstract

For the first time, the net community production (NCP) was estimated over a complete annual cycle in the basin of the South China Sea (SCS) using in situ oxygen measurements from an Argo profiling float and an oxygen mass balance model. The annual NCP from July 2014 to July 2015 was estimated to be 2.7 mol C m−2 yr−1 (calculated to the deepest winter mixed layer depth of 56 m), with the uncertainties ranging from 0.9 ~ 2.2 mol C m−2 yr−1. NCP estimates followed a monsoonal pattern with higher values in the cold season (November to April) when northeast monsoon prevailed and low values in the warm season (June to September) when this area was dominated by the southwest monsoon. Most of the net heterotrophic events occurred in the warm season. The magnitude and seasonal pattern derived from our results agree with previous export production studies based on discrete measurements. Comparison with satellite-derived NCP revealed that the results derived with NPP from Carbon-based Production Model (CbPM) were closer to the Argo measurements than the results derived with NPP from Vertically Generalized Production Model (VGPM) in magnitude; while the VGPM-based approach did a better job in reproducing the seasonal cycle of NCP in this area. This novel approach provides the possibilities to study the carbon cycle in the SCS with a much higher temporal and spatial resolution, as well as more insights for metabolic state in the oligotrophic subtropical gyres.

Original languageEnglish
Pages (from-to)54-61
Number of pages8
JournalDeep-Sea Research Part I: Oceanographic Research Papers
Volume131
Early online date21 Nov 2017
DOIs
Publication statusPublished - 31 Jan 2018

Keywords

  • Argo float
  • net community production
  • satellite-derived net community production
  • South China Sea Basin
  • temporal variation

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