Perspectives from the Global Ocean Data Assimilation Experiment

2006 ◽  
pp. 1-17 ◽  
Author(s):  
Neville Smith
Keyword(s):  
Data Assimilation ◽  
Global Ocean ◽  
Assimilation Experiment ◽  
Ocean Data Assimilation

scholarly journals GODAE: The Global Ocean Data Assimilation Experiment

Oceanography ◽  
2009 ◽  
Vol 22 (3) ◽  
pp. 14-21 ◽  
Author(s):  
Michael Bell ◽  
Michel Lefèbvre ◽  
Pierre-Yves Le Traon ◽  
Neville Smith ◽  
Kirsten Wilmer-Becker
Keyword(s):  
Data Assimilation ◽  
Global Ocean ◽  
Assimilation Experiment ◽  
Ocean Data Assimilation

scholarly journals DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR OPERATIONAL OCEANOGRAPHY AND OCEAN FORECASTING

2013 ◽  
Vol 31 (2) ◽  
pp. 210 ◽  
Author(s):  
Jose Antonio Moreira Lima ◽  
Renato Parkinson Martins ◽  
Clemente Augusto Souza Tanajura ◽  
Afonso De Moraes Paiva ◽  
Mauro Cirano Cirano ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Atlantic Ocean ◽  
Large Scale ◽  
Integrated Approach ◽  
Global Ocean ◽  
Assimilation Experiment ◽  
In Situ Data ◽  
Ocean Data Assimilation ◽  
Observation Network ◽  
Ocean Forecasting

ABSTRACT. This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network (REMO) for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in situ data such as the South Atlantic Ocean. An integrated approach is proposed here in which the large-scale circulation in the Atlantic Ocean is modeled in a first step, and gradually downscaled into higher resolution regional models. This approach is able to resolve important processes such as the Brazil Current and associated meso-scale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView), in which REMO takes part.Keywords: ocean models, ocean measurements, data assimilation. RESUMO. Este artigo apresenta o planejamento, implementação e alguns resultados da Rede de Modelagem e Observação Oceanográfica, com acrônimo REMO, para águas territoriais brasileiras. A previsão de condições oceânicas tem sido um importante tópico de pesquisa científica ao longo da última década, devido a estudos relacionados com mudanças climáticas assim como interesse por previsões sinóticas de curto prazo de variáveis tais como correntes marinhas e temperatura da água. É um desafio realizar o projeto de um sistema de previsão para uma região oceânica com baixa disponibilidade de medições, como o Oceano Atlântico Sul. Uma proposta de desenvolvimento integrado é apresentada neste trabalho, onde um modelo de circulação oceânica de todo Oceano Atlântico foi implementado como passo inicial, e gradualmente foram aninhados modelos regionais com maior resolução espacial. Este artigo apresenta a estratégia de desenvolvimento destes modelos oceânicos utilizando o conhecimento científico disponibilizado por pesquisadores de uma rede de instituições brasileiras, com eventual colaboração de pesquisadores internacionais. Esta iniciativa brasileira possui pontos comuns com um projeto de cooperação científica internacional, denominado Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView), da qual a REMO faz parte.Palavras-chave: oceanografia operacional, modelagem oceânica, sensoriamento remoto, medições oceanográficas, assimilação de dados.

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 The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project

2007 ◽  
Vol 88 (8) ◽  
pp. 1197-1214 ◽  
Author(s):  
C. Donlon ◽  
I. Robinson ◽  
K. S. Casey ◽  
J. Vazquez-Cuervo ◽  
E. Armstrong ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Pilot Project ◽  
Sea Surface ◽  
Global Ocean ◽  
Assimilation Experiment ◽  
Ocean Data Assimilation ◽  
Data Products

A new generation of integrated sea surface temperature (SST) data products are being provided by the Global Ocean Data Assimilation Experiment (GODAE) High-Resolution SST Pilot Project (GHRSST-PP). These combine in near-real time various SST data products from several different satellite sensors and in situ observations and maintain the fine spatial and temporal resolution needed by SST inputs to operational models. The practical realization of such an approach is complicated by the characteristic differences that exist between measurements of SST obtained from subsurface in-water sensors, and satellite microwave and satellite infrared radiometer systems. Furthermore, diurnal variability of SST within a 24-h period, manifested as both warm-layer and cool-skin deviations, introduces additional uncertainty for direct intercomparison between data sources and the implementation of data-merging strategies. The GHRSST-PP has developed and now operates an internationally distributed system that provides operational feeds of regional and global coverage high-resolution SST data products (better than 10 km and ~6 h). A suite of online satellite SST diagnostic systems are also available within the project. All GHRSST-PP products have a standard format, include uncertainty estimates for each measurement, and are served to the international user community free of charge through a variety of data transport mechanisms and access points. They are being used for a number of operational applications. The approach will also be extended back to 1981 by a dedicated reanalysis project. This paper provides a summary overview of the GHRSST-PP structure, activities, and data products. For a complete discussion, and access to data products and services see the information online at www.ghrsst-pp.org.

scholarly journals Impact of Multiple Altimeter Data and Mean Dynamic Topography in a Global Analysis and Forecasting System

2019 ◽  
Vol 36 (7) ◽  
pp. 1255-1266 ◽  
Author(s):  
Mathieu Hamon ◽  
Eric Greiner ◽  
Pierre-Yves Le Traon ◽  
Elisabeth Remy
Keyword(s):  
Data Assimilation ◽  
Sea Surface ◽  
Global Ocean ◽  
Altimeter Data ◽  
Dynamic Topography ◽  
Mean Dynamic Topography ◽  
Ocean Data Assimilation ◽  
The Mean ◽  
Data Assimilation System ◽  
Assimilation System

AbstractSatellite altimetry is one of the main sources of information used to constrain global ocean analysis and forecasting systems. In addition to in situ vertical temperature and salinity profiles and sea surface temperature (SST) data, sea level anomalies (SLA) from multiple altimeters are assimilated through the knowledge of a surface reference, the mean dynamic topography (MDT). The quality of analyses and forecasts mainly depends on the availability of SLA observations and on the accuracy of the MDT. A series of observing system evaluations (OSEs) were conducted to assess the relative importance of the number of assimilated altimeters and the accuracy of the MDT in a Mercator Ocean global 1/4° ocean data assimilation system. Dedicated tools were used to quantify impacts on analyzed and forecast sea surface height and temperature/salinity in deeper layers. The study shows that a constellation of four altimeters associated with a precise MDT is required to adequately describe and predict upper-ocean circulation in a global 1/4° ocean data assimilation system. Compared to a one-altimeter configuration, a four-altimeter configuration reduces the mean forecast error by about 30%, but the reduction can reach more than 80% in western boundary current (WBC) regions. The use of the most recent MDT updates improves the accuracy of analyses and forecasts to the same extent as assimilating a fourth altimeter.

scholarly journals A Hybrid Global Ocean Data Assimilation System at NCEP

2015 ◽  
Vol 143 (11) ◽  
pp. 4660-4677 ◽  
Author(s):  
Stephen G. Penny ◽  
David W. Behringer ◽  
James A. Carton ◽  
Eugenia Kalnay
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Global Ocean ◽  
Climate Forecast ◽  
Forecast System ◽  
Climate Forecast System ◽  
Ocean Data Assimilation ◽  
Data Assimilation System ◽  
Ncep Climate Forecast System ◽  
Assimilation System

Abstract Seasonal forecasting with a coupled model requires accurate initial conditions for the ocean. A hybrid data assimilation has been implemented within the National Centers for Environmental Prediction (NCEP) Global Ocean Data Assimilation System (GODAS) as a future replacement of the operational three-dimensional variational data assimilation (3DVar) method. This Hybrid-GODAS provides improved representation of model uncertainties by using a combination of dynamic and static background error covariances, and by using an ensemble forced by different realizations of atmospheric surface conditions. An observing system simulation experiment (OSSE) is presented spanning January 1991 to January 1999, with a bias imposed on the surface forcing conditions to emulate an imperfect model. The OSSE compares the 3DVar used by the NCEP Climate Forecast System (CFSv2) with the new hybrid, using simulated in situ ocean observations corresponding to those used for the NCEP Climate Forecast System Reanalysis (CFSR). The Hybrid-GODAS reduces errors for all prognostic model variables over the majority of the experiment duration, both globally and regionally. Compared to an ensemble Kalman filter (EnKF) used alone, the hybrid further reduces errors in the tropical Pacific. The hybrid eliminates growth in biases of temperature and salinity present in the EnKF and 3DVar, respectively. A preliminary reanalysis using real data shows that reductions in errors and biases are qualitatively similar to the results from the OSSE. The Hybrid-GODAS is currently being implemented as the ocean component in a prototype next-generation CFSv3, and will be used in studies by the Climate Prediction Center to evaluate impacts on ENSO prediction.

Impact of an upgraded model in the NCEP Global Ocean Data Assimilation System: The tropical Indian Ocean

2016 ◽  
Vol 121 (11) ◽  
pp. 8039-8062 ◽  
Author(s):  
Hasibur Rahaman ◽  
David W. Behringer ◽  
Stephen G. Penny ◽  
M. Ravichandran
Keyword(s):  
Indian Ocean ◽  
Data Assimilation ◽  
Tropical Indian Ocean ◽  
Global Ocean ◽  
Ocean Data Assimilation ◽  
Data Assimilation System ◽  
Assimilation System
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