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Model data for benthic oxygen flux on the East China Sea shelf

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科学数据银行2022-02-21 更新2026-04-23 收录
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The pelagic component (BYESbio24), which was based on a physical-biogeochemical ROMS-CoSiNE model customized for Bohai Sea, Yellow Sea and East China Sea (Zhou et al., 2017; Zhou et al., 2020), was coupled with the benthic component (TOCMAIN; Zhang & Wirtz, 2017; Zhang et al., 2021) to quantify oxygen flux across the sediment-water interface on the East China Sea shelf. Sediment oxygen consumption (SOC) is decomposed into three components: porewater advective flux, molecular diffusive flux and bioturbation diffusive flux. Advective flux is caused by porewater flows in permeable sediments, while diffusive flux is induced by molecular movements and bioturbation in both permeable and impermeable sediments. The uploaded model outputs are in matrix format that is readable by MATLAB. The data are confined within [122 - 127ºE] and [27 - 32ºE]. The mesh grids in terms of longitude and latitude can be found in variables ‘xgrid’ and ‘ygrid’, respectively. Daily-averaged gridded data are presented spanning from 2009 to 2014. Macrobenthos biomass is stored in the variable ‘gbiomass’ in units of gC/m2. Bioturbation coefficient is stored in the variable ‘gbioturb’ in units of cm2/day. Molecular diffusive benthic oxygen flux is stored in the variable ‘gmoldiff’ in units of mmol/m2/day. Bioturbation diffusive benthic oxygen flux is stored in the variable ‘gbiodiff’ in units of mmol/m2/day. Porewater advective benthic oxygen flux is stored in the variable ‘gporeadv’ in units of mmol/m2/day. Total benthic oxygen flux, or the SOC, is stored in the variable ‘gSOC’ in units of mmol/m2/day. Water oxygen consumption (WOC) below the pycnocline is stored in the variable ‘gWOC’ in units of mmol/m2/day. Contribution of SOC to the total local oxygen consumption (SOC + WOC) is stored in the variable ‘gSOCpercent’. References:Zhang, W., & Wirtz, K. (2017). Mutual Dependence Between Sedimentary Organic Carbon and Infaunal Macrobenthos Resolved by Mechanistic Modeling. Journal of Geophysical Research: Biogeosciences, 122(10), 2509-2526. doi: 10.1002/2017JG003909Zhang, W., Neumann, A., Daewel, U., Wirtz, K., van Beusekom, J. E. E., Eisele, A., . . . Schrum, C. (2021). Quantifying importance of macrobenthos for benthic-pelagic coupling in a temperate coastal shelf sea. Journal of Geophysical Research: Oceans, 126, e2020JC016995. doi: 10.1029/2020JC016995.Zhou, F., Chai, F., Huang, D., Xue, H., Chen, J., Xiu, P., . . . Wang, K. (2017). Investigation of hypoxia off the Changjiang Estuary using a coupled model of ROMS-CoSiNE. Progress in Oceanography, 159, 237-254. doi: 10.1016/j.pocean.2017.10.008Zhou, F., Chai, F., Huang, D., Wells, M., Ma, X., Meng, Q., . . . Li, H. (2020). Coupling and Decoupling of High Biomass Phytoplankton Production and Hypoxia in a Highly Dynamic Coastal System: The Changjiang (Yangtze River) Estuary. Frontiers in Marine Science, 7, 259. doi: 10.3389/fmars.2020.00259
提供机构:
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources; Observation and Research Station of Yangtze River Delta Marine Ecosystems, Ministry of Natural Resources; Qicheng Meng; School of Oceanography, Shanghai Jiao Tong University, Shanghai, China; Xiaobo Ni; Peisong Yu; Dingyong Zeng; Wenyan Zhang; Ruibin Ding; Yibo Liao; Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon; Yanbin Tang
创建时间:
2021-10-09
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