%0 Journal Article
%@nexthigherunit 8JMKD3MGPCW/3ER446E
%@nexthigherunit 8JMKD3MGPCW/3F35TRS
%3 lima_investigation.pdf
%4 sid.inpe.br/mtc-m21c/2019/02.28.10.47
%8 Jan.
%9 journal article
%@issn 2169-9275
%A Lima, Leonardo Nascimento,
%A Pezzi, Luciano Ponzi,
%A Penny, Stephen G.,
%A Tanajura, Clemente A. S.,
%@secondarytype PRE PI
%B Journal of Geophysical Research: Oceans
%D 2019
%N 1
%P 432-452
%T An investigation of ocean model uncertainties through ensemble forecast experiments in the Southwest Atlantic Ocean
%V 124
%X cean general circulation models even with realistic behavior still incorporate large uncertainties from external forcing. This study involves the realization of ensemble experiments using a regional model configured for the Southwest Atlantic Ocean to investigate uncertainties derived from the external forcing such as the atmosphere and bathymetry. The investigation is based on perturbing atmospheric surface fluxes and bathymetry through a series of ensemble experiments. The results showed a strong influence of the South Atlantic Convergence Zone on the underlying ocean, 7days after initialization. In this ocean region, precipitation and radiation flux perturbations notably impacted the sea surface salinity and sea surface temperature, by producing values of ensemble spread that exceeded 0.08 and 0.2 degrees C, respectively. Wind perturbations extended the impact on currents at surface, with the spread exceeding 0.1m/s. The ocean responded faster to the bathymetric perturbations especially in shallow waters, where the dynamics are largely dominated by barotropic processes. Ensemble spread was the largest within the thermocline layer and in ocean frontal regions after a few months, but by this time, the impact on the modeled ocean obtained from either atmospheric or bathymetric perturbations was quite similar, with the internal dynamics dominating over time. In the vertical, the sea surface temperature exhibited high correlation with the subsurface temperature of the shallowest model levels within the mixed layer. Horizontal error correlations exhibited strong flow dependence at specific points on the Brazil and Malvinas Currents. This analysis will be the basis for future experiments using ensemble-based data assimilation in the Southwest Atlantic Ocean. Plain Language Summary The numerical models are powerful tools to provide knowledge about the ocean state concerning currents eddies, meanders, and other ocean dynamic and thermodynamic processes on a range of temporal and spatial scales. An accurate numerical model makes possible to get a tridimensional ocean representation with some confidence during time. Even though the ocean numerical models have been incorporating improvements, mainly due to a growing evolution of the computational resources, they are still somewhat limited and bring uncertainties on their simulations due many reasons that are related to the applied physical parameterization, atmospheric forcing, bathymetry, and some other issues. It is crucial to investigate and to know these uncertainties. This study goes further on the uncertainty investigations in order to create the basis (prior step) for an ensemble-based data assimilation system for the Southwest Atlantic Ocean. Our results indicated that uncertainty in wind forcing plays a major role in the determination of uncertainty in the ocean state. Compared to atmospheric forcing, the uncertainty in bathymetry produced a larger impact on the ocean representation, especially in shallow waters, though this may be in part due to excited waves at the initial time.
%@area MET
%@electronicmailaddress leonasclima@gmail.com
%@electronicmailaddress luciano.pezzi@inpe.br
%@documentstage not transferred
%@group MET-MET-SESPG-INPE-MCTIC-GOV-BR
%@group DIDSR-CGOBT-INPE-MCTIC-GOV-BR
%@dissemination WEBSCI; PORTALCAPES; AGU; SCOPUS.
%@orcid 0000-0003-3208-5857
%@orcid 0000-0001-6016-4320
%@orcid 0000-0002-5223-8307
%@orcid 0000-0002-3490-4302
%@usergroup simone
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHM8
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation University of Maryland
%@affiliation Universidade Federal da Bahia (UFBA)
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@doi 10.1029/2018JC013919
%2 sid.inpe.br/mtc-m21c/2019/02.28.10.47.51