Previsões Oceânicas no Atlântico Sudoeste (METAREA V) Utilizando

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Raquel Leite Mello ◽  
João Bosco Rodrigues Alvarenga ◽  
Ana Cristina Neves de Freitas ◽  
Clemente Tanajura ◽  
Lucimara Russo ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Research Laboratory ◽  
Ocean Model ◽  
Naval Research Laboratory ◽  
Naval Research ◽  
Ocean Data Assimilation ◽  
Hybrid Coordinate Ocean Model

Neste trabalho foi utilizado o modelo hidrodinâmico HYCOM (HYbrid Coordinate Ocean Model) em duas grades aninhadas. Uma grade para todo o Oceano Atlântico (1/4º) aninhada a outra com para a Metarea V (1/12º). O objetivo é avaliar qual a fonte de dados de ASM (Altura da Superfície do Mar) imposta no modelo é mais adequada para a previsão numérica da área de interesse. Foram realizados três experimentos com diferentes campos de ASM impostos na condição inicial com o esquema de Cooper & Haines (1996) e um experimento controle no qual não foi imposta fonte de ASM externa. De maneira geral, os resultados obtidos através das simulações do HYCOM apresentam-se satisfatórios quando comparados aos dados observacionais de temperatura e salinidade de derivadores Argo. O experimento NRL com ASM total obtido dos resultados do HYCOM+NCODA (Navy Coupled Ocean Data Assimilation) GLOBAL 1/12º obtidos no NRL (Naval Research Laboratory) foi o que melhor representou o perfil médio de temperatura e salinidade observado. No Diagrama de Taylor, este mesmo experimento mostrou maior correlação (0,99), menor erro quadrático médio (0,99ºC) e desvio padrão (8,76ºC) muito próximo dos dados observados (8,67ºC).

scholarly journals OCEAN FORECASTS IN THE SOUTHWESTERN ATLANTIC: IMPACT OF DIFFERENT SOURCES OF SEA SURFACE HEIGHT IN DATA ASSIMILATION

2013 ◽  
Vol 31 (2) ◽  
pp. 243 ◽  
Author(s):  
Raquel Leite Mello ◽  
Ana Cristina Neves de Freitas ◽  
Lucimara Russo ◽  
Jean Felix de Oliveira ◽  
Clemente Augusto Souza Tanajura ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Ocean Model ◽  
Sea Surface ◽  
Naval Research ◽  
Southwest Atlantic ◽  
Argo Data ◽  
Ocean Data Assimilation ◽  
Hybrid Coordinate Ocean Model ◽  
Oceanographic Data ◽  
The One

ABSTRACT. The objective in this paper is to analyze which Sea Surface Height (SSH) source applied to HYCOM (HYbrid Coordinate Ocean Model) is best suited to numerical prediction of the Southwest Atlantic Ocean. To this end two nested grids were used. One grid for the entire Atlantic Ocean (1/4◦) nesting the grid for the Southwest Atlantic (1/12◦) in the one-way mode. Three forecast experiments with different SSH data sources (Naval Research Laboratory – NRL; Archiving, Validation and Interpolation of Oceanographic Data – AVISO and MERCATOR) applied to constrain the initial conditions and a control forecast experiment without SSH constrain were compared. The comparison of forecasted temperature and salinity profiles with Argo data showed good correlation, over 0.98 for temperature and 0.87 for salinity. The NRL experiment – with SSH obtained by HYCOM+NCODA (Navy Coupled Ocean Data Assimilation System) GLOBAL 1/12◦ analysis was the one that best represented the average temperature and salinity profile with respect to the Argo data. Keywords: HYCOM, numerical modeling, ocean prediction, Argo profiler, Taylor diagram. RESUMO. O objetivo deste trabalho é avaliar qual a fonte de dados de ASM (Altura da Superfície do Mar) imposta no modelo HYCOM (HYbrid Coordinate Ocean Model) é mais adequada para a previsão numérica do Oceano Atlântico Sudoeste. Para isto foram utilizadas duas grades aninhadas, uma grade para todo o Oceano Atlântico (1/4◦) aninhada no modo one-way a outra grade para o Atlântico Sudoeste (1/12◦). Foram realizados três experimentos com diferentes campos de ASM (Naval Research Laboratory – NRL; Archiving, Validation and Interpolation of Oceanographic data – AVISO e MERCATOR) impostos na condição inicial e um experimento controle no qual não foi usada fonte de ASM externa. A comparação dos perfis de temperatura e salinidade entre os dados observados e os resultados do modelo apresentou boa correlação, maior que 0,98 para a temperatura e 0,87 para a salinidade. O experimento NRL com ASM total obtido dos resultados do HYCOM+NCODA (Navy Coupled Ocean Data Assimilation) GLOBAL 1/12◦ foi o que melhor representou o perfil médio de temperatura e salinidade observado.  Palavras-chave: HYCOM, modelagem numérica, previsão oceânica, perfiladores Argo, diagrama de Taylor.

scholarly journals On the Impact of Unmanned Aerial System Observations on Numerical Weather Prediction in the Coastal Zone

2018 ◽  
Vol 146 (2) ◽  
pp. 599-622 ◽  
Author(s):  
David D. Flagg ◽  
James D. Doyle ◽  
Teddy R. Holt ◽  
Daniel P. Tyndall ◽  
Clark M. Amerault ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Research Laboratory ◽  
Weather Prediction ◽  
Ocean Model ◽  
Naval Research ◽  
Unmanned Aerial System ◽  
Numerical Weather ◽  
The Impact

Abstract The Trident Warrior observational field campaign conducted off the U.S. mid-Atlantic coast in July 2013 included the deployment of an unmanned aerial system (UAS) with several payloads on board for atmospheric and oceanic observation. These UAS observations, spanning seven flights over 5 days in the lowest 1550 m above mean sea level, were assimilated into a three-dimensional variational data assimilation (DA) system [the Naval Research Laboratory Atmospheric Variational Data Assimilation System (NAVDAS)] used to generate analyses for a numerical weather prediction model [the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)] with a coupled ocean model [the Naval Research Laboratory Navy Coastal Ocean Model (NCOM)]. The impact of the assimilated UAS observations on short-term atmospheric prediction performance is evaluated and quantified. Observations collected from 50 radiosonde launches during the campaign adjacent to the UAS flight paths serve as model forecast verification. Experiments reveal a substantial reduction of model bias in forecast temperature and moisture profiles consistently throughout the campaign period due to the assimilation of UAS observations. The model error reduction is most substantial in the vicinity of the inversion at the top of the model-estimated boundary layer. Investigations reveal a consistent improvement to prediction of the vertical position, strength, and depth of the boundary layer inversion. The relative impact of UAS observations is explored further with experiments of systematic denial of data streams from the NAVDAS DA system and removal of individual measurement sources on the UAS platform.

Evaluation of Global Ocean Data Assimilation Experiment products on South Florida nested simulations with the Hybrid Coordinate Ocean Model

2008 ◽  
Vol 59 (1) ◽  
pp. 47-66 ◽  
Author(s):  
Vassiliki H. Kourafalou ◽  
Ge Peng ◽  
HeeSook Kang ◽  
Patrick J. Hogan ◽  
Ole-Martin Smedstad ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Ocean Model ◽  
South Florida ◽  
Global Ocean ◽  
Assimilation Experiment ◽  
Ocean Data Assimilation ◽  
Hybrid Coordinate Ocean Model

scholarly journals Argo data assimilation into HYCOM with an EnOI method in the Atlantic Ocean

Ocean Science ◽  
2015 ◽  
Vol 11 (1) ◽  
pp. 195-213 ◽  
Author(s):  
D. Mignac ◽  
C. A. S. Tanajura ◽  
A. N. Santana ◽  
L. N. Lima ◽  
J. Xie
Keyword(s):  
Data Assimilation ◽  
Atlantic Ocean ◽  
Heat Content ◽  
Ocean Model ◽  
Optimal Interpolation ◽  
Argo Data ◽  
Thermohaline Structure ◽  
Vertical Coordinate ◽  
Ocean Data Assimilation ◽  
Hybrid Coordinate Ocean Model

Abstract. An ocean data assimilation system to assimilate Argo temperature (T) and salinity (S) profiles into the HYbrid Coordinate Ocean Model (HYCOM) was constructed, implemented and evaluated for the first time in the Atlantic Ocean (78° S to 50° N and 98° W to 20° E). The system is based on the ensemble optimal interpolation (EnOI) algorithm proposed by Xie and Zhu (2010), especially made to deal with the hybrid nature of the HYCOM vertical coordinate system with multiple steps. The Argo T–S profiles were projected to the model vertical space to create pseudo-observed layer thicknesses (Δ pobs), which correspond to the model target densities. The first step was to assimilate Δ pobs considering the sub-state vector composed by the model layer thickness (Δ p) and the baroclinic velocity components. After that, T and S were assimilated separately. Finally, T was diagnosed below the mixed layer to preserve the density of the model isopycnal layers. Five experiments were performed from 1 January 2010 to 31 December 2012: a control run without assimilation, and four assimilation runs considering the different vertical localizations of T, S and Δ p. The assimilation experiments were able to significantly improve the thermohaline structure produced by the control run. They reduced the root mean square deviation (RMSD) of T and S calculated with respect to Argo independent data in 34 and 44%, respectively, in comparison to the control run. In some regions, such as the western North Atlantic, substantial corrections in the 20 °C isotherm depth and the upper ocean heat content towards climatological states were achieved. The runs with a vertical localization of Δ p showed positive impacts in the correction of the thermohaline structure and reduced the RMSD of T (S) from 0.993 °C (0.149 psu) to 0.905 °C (0.138 psu) for the whole domain with respect to the other assimilation runs.

Development of a Mesoscale Ensemble Data Assimilation System at the Naval Research Laboratory

2013 ◽  
Vol 28 (6) ◽  
pp. 1322-1336 ◽  
Author(s):  
Qingyun Zhao ◽  
Fuqing Zhang ◽  
Teddy Holt ◽  
Craig H. Bishop ◽  
Qin Xu
Keyword(s):  
Data Assimilation ◽  
Research Laboratory ◽  
Localization Length ◽  
Naval Research Laboratory ◽  
Naval Research ◽  
Ensemble Size ◽  
The Impact ◽  
Data Assimilation System ◽  
Scale Data ◽  
Assimilation System

Abstract An ensemble Kalman filter (EnKF) has been adopted and implemented at the Naval Research Laboratory (NRL) for mesoscale and storm-scale data assimilation to study the impact of ensemble assimilation of high-resolution observations, including those from Doppler radars, on storm prediction. The system has been improved during its implementation at NRL to further enhance its capability of assimilating various types of meteorological data. A parallel algorithm was also developed to increase the system’s computational efficiency on multiprocessor computers. The EnKF has been integrated into the NRL mesoscale data assimilation system and extensively tested to ensure that the system works appropriately with new observational data stream and forecast systems. An innovative procedure was developed to evaluate the impact of assimilated observations on ensemble analyses with no need to exclude any observations for independent validation (as required by the conventional evaluation based on data-denying experiments). The procedure was employed in this study to examine the impacts of ensemble size and localization on data assimilation and the results reveal a very interesting relationship between the ensemble size and the localization length scale. All the tests conducted in this study demonstrate the capabilities of the EnKF as a research tool for mesoscale and storm-scale data assimilation with potential operational applications.

Progress in Laser Propagation in a Maritime Environment at the Naval Research Laboratory

2005 ◽  
Author(s):  
G. C. Gilbreath ◽  
W. S. Rabinovich ◽  
C. I. Moore ◽  
H. R. Burris ◽  
R. Mahon ◽  
...  
Keyword(s):  
Research Laboratory ◽  
Naval Research Laboratory ◽  
Naval Research ◽  
Laser Propagation ◽  
Maritime Environment
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