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Observing system experiments over the Atlantic Ocean with the REMO ocean data assimilation system (RODAS) into HYCOM

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The Oceanographic Modeling and Observation Network (REMO) focuses on scientific and technological development of operational oceanography in Brazil considering both numerical forecasting and observational systems. A key component of the forecasting system is the recently constructed REMO Ocean Data Assimilation System (RODAS) into the HYbrid Coordinate Ocean Model (HYCOM). Here, RODAS is presented for the first time with its full capability. RODAS employs a multivariate ensemble optimal interpolation scheme that is able to assimilate Argo temperature (T) and salinity (S) profiles, sea surface temperature (SST) analyses, and satellite along-track or gridded sea-level anomaly (SLA) data. RODAS is presented together with a series of Observing System Experiments (OSEs), in which components of the Global Ocean Observing System (GOOS) were systematically withheld from 3-year assimilation runs over the Atlantic Ocean. Using the same initial condition from a full assimilation run, OSEs were performed from 1 January 2010 to 31 December 2012 withholding (i) only Argo data; (ii) only UK MetOffice OSTIA SST analyses; (iii) only satellite along-track altimetry data; and (iv) all observation types. These runs were also compared with the full assimilation run and the model free run to evaluate the impact of different observations into the model state. The results show that each observation type brings complementary information into the analyses. Assimilation of SST is needed to better constrain the mixed layer temperature, while assimilation of SLA mainly improves the representation of circulation by adding mesoscale-like features, such as those found in the Gulf Stream and the Brazil-Malvinas Confluence. In the subsurface, only Argo observations are able to constrain the thermohaline state. When Argo data are withheld, the quality of S is seriously compromised and becomes worse than the free run in the upper ocean. Additionally, the run withholding all observation types shows that the model state in the surface almost reaches the free run state by the end of the third year. However, below 300 m, the memory of the Argo data assimilation is longer and the quality of T and S is only degraded by 35% in comparison with the full assimilation run.

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Funding

This work was financially supported by PETROBRAS and the Brazilian oil regulatory agency ANP (Agência Nacional de Petróleo, Gás Natural e Biocombustíveis), within the special participation research project Oceanographic Modeling and Observation Network (REMO). Part of the infrastructure to develop this work was offered by the Brazilian Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the research grant 446528/2014-5.

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Authors and Affiliations

  1. Departamento de Física da Terra e do Meio Ambiente, Instituto de Física, Universidade Federal da Bahia (UFBA), Salvador, Brazil

    Clemente A. S. Tanajura

  2. Oceanographic Modeling and Observation Network (REMO), Geophysics and Geology Research Center, Federal University of Bahia (CPGG/UFBA), Salvador, Brazil

    Clemente A. S. Tanajura, Davi Mignac, Alex N. de Santana, Filipe B. Costa, Leonardo N. Lima & Konstantin P. Belyaev

  3. Ocean Modeling and Data Assimilation Division, Euro-Mediterranean Center on Climate Change (CMCC), Bologna, Italy

    Leonardo N. Lima

  4. Shirshov Institute of Oceanology, Russian Academy of Sciences (SIORAS), Moscow, Russia

    Konstantin P. Belyaev

  5. Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), Beijing, China

    Jiang Zhu

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  1. Clemente A. S. Tanajura
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  2. Davi Mignac
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  3. Alex N. de Santana
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  4. Filipe B. Costa
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  5. Leonardo N. Lima
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  6. Konstantin P. Belyaev
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  7. Jiang Zhu
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Correspondence to Clemente A. S. Tanajura.

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Responsible Editor: Tal Ezer

This article is part of the Topical Collection on the 10th International Workshop on Modeling the Ocean (IWMO), Santos, Brazil, 25-28 June 2018

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Tanajura, C.A.S., Mignac, D., de Santana, A.N. et al. Observing system experiments over the Atlantic Ocean with the REMO ocean data assimilation system (RODAS) into HYCOM. Ocean Dynamics 70, 115–138 (2020). https://doi.org/10.1007/s10236-019-01309-8

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