Articles | Volume 17, issue 4
Research article
26 Aug 2021
Research article |  | 26 Aug 2021

Can assimilation of satellite observations improve subsurface biological properties in a numerical model? A case study for the Gulf of Mexico

Bin Wang, Katja Fennel, and Liuqian Yu

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Cited articles

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Biogeochemical-Argo Planning Group: The scientific rationale, design and implementation plan for a Biogeochemical-Argo float array, Report,, 2016. a
Chai, F., Johnson, K. S., Claustre, H., Xing, X., Wang, Y., Boss, E., Riser, S., Fennel, K., Schofield, O., and Sutton, A.: Monitoring ocean biogeochemistry with autonomous platforms, Nat. Rev. Earth Environ., 1, 315–326,, 2020. a
Chassignet, E., Hurlburt, H., Smedstad, O., Barron, C., Ko, D., Rhodes, R., Shriver, J., Wallcraft, A., and Arnone, R.: Assessment of Data Assimilative Ocean Models in the Gulf of Mexico Using Ocean Color, Geophys. Monogr. Ser., 161, 87–100,, 2005. a, b
Short summary
We demonstrate that even sparse BGC-Argo profiles can substantially improve biogeochemical prediction via a priori model tuning. By assimilating satellite surface chlorophyll and physical observations, subsurface distributions of physical properties and nutrients were improved immediately. The improvement of subsurface chlorophyll was modest initially but was greatly enhanced after adjusting the parameterization for light attenuation through further a priori tuning.