%0 Journal Article
%4 sid.inpe.br/plutao/2014/12.01.12.15.34
%2 sid.inpe.br/plutao/2014/12.01.12.15.35
%@doi 10.3878/j.issn.1674-2834.14.0011
%@issn 1674-2834
%F lattes: 7758920363746942 4 TanajuraSaMiLiBeXi:2014:GeDePr
%T The REMO ocean data assimilation system into HYCOM (RODAS_H): general description and preliminary results
%D 2014
%9 journal article
%A Tanajura, Clemente Augusto Souza,
%A Santana, Alex Novaes,
%A Mignac, Davi,
%A Lima, Leonardo Nascimento,
%A Belyaev, Konstantin Pavlovich,
%A Xie, Ji-ping,
%@affiliation
%@affiliation
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%B Atmospheric and Oceanic Science Letters
%V 7
%N 5
%P 464-470
%K ocean data assimilation, Ensemble Optimal Interpolation, observing system experiment, HYCOM, Atlantic Ocean.
%X The first version of the Brazilian Oceanographic Modeling and Observation Network (REMO) ocean data assimilation system into the Hybrid Coordinate Ocean Model (HYCOM) (RODAS_H) has recently been constructed for research and operational purposes. The system is based on a multivariate Ensemble Optimal Interpolation (EnOI) scheme and considers the high frequency variability of the model error co-variance matrix. The EnOI can assimilate sea surface temperature (SST), satellite along-track and gridded sea level anomalies (SLA), and vertical profiles of temperature (T) and salinity (S) from Argo. The first observing system experiment was carried out over the Atlantic Ocean (78°S50°N, 100°W20°E) with HYCOM forced with atmospheric reanalysis from 1 January to 30 June 2010. Five integrations were performed, including the control run without assimilation. In the other four, different observations were assimilated: SST only (A_SST); Argo T-S profiles only (A_Argo); along-track SLA only (A_SLA); and all data employed in the previous runs (A_All). The A_SST, A_Argo, and A_SLA runs were very effective in improving the representation of the assimilated variables, but they had relatively little impact on the variables that were not assimilated. In particular, only the assimilation of S was able to reduce the deviation of S with respect to observations. Overall, the A_All run produced a good analysis by reducing the deviation of SST, T, and S with respect to the control run by 39%, 18%, and 30%, respectively, and by increasing the correlation of SLA by 81%.
%@language en
%3 The REMO Ocean Data Assimilation System into HYCOM %28RODAS_H%29%3A General Description and Preliminary Results.pdf
%U http://159.226.119.58/aosl/article/2014/1674-2834-7-5-464.html