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Introduction to Ocean Data Assimilation
2011Data assimilation is the process of hindcasting, now-casting, and forecasting using information from both observations and ocean dynamics. Modern ocean forecasting systems rely on data assimilation to estimate initial and boundary data, to interpolate and smooth sparse or noisy observations, and to evaluate observing systems and dynamical models. Every
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Data Assimilation in Ocean Prediction
1999Abstract : Remotely sensed satellite observations provide ocean altimetry data at high temporal and spatial resolutions to an unprecedented accuracy of approximately 5 cms. Availability of data of such high quality and wide coverage makes it possible to address a variety of scientific questions related to physical oceanography including, for example ...
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Global ocean data assimilation system
1996Abstract A global oceanic four-dimensional data assimilation system has been developed for use in initializing coupled ocean-atmosphere general circulation models and also to study interannual variability. The data inserted into a high resolution global ocean model consists only of conventional sea surface temperature observations and vertical ...
A. Rosati, R. Gudgel, K. Miyakoda
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Assimilation of Data into Ocean Models
1989Because of the size of the ocean we do not have, nor are we ever likely to have, good synoptic data on the ocean circulation. However, data from relatively isolated instruments within the ocean are usually available and these are now being joined by data from satellite mounted instruments which give routine surveillance of the ocean surface.
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2001
Abstract : Development of data assimilation, not only for data analysis, but as a rigorous framework for the test-ing of numerical models of ocean circulation to be used in hindcasting, forecasting and array assess-ment.
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Abstract : Development of data assimilation, not only for data analysis, but as a rigorous framework for the test-ing of numerical models of ocean circulation to be used in hindcasting, forecasting and array assess-ment.
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Ocean Data Assimilation: A Coastal Application
2009The Navy Coupled Ocean Data Assimilation (NCODA) system is applied to a period during the Autonomous Ocean Sampling Network II (AOSN II) field campaign conducted in the Monterey Bay area in August 2003. The multivariate analysis of NCODA is cycled with the Navy Coastal Ocean Model (NCOM) in a sequential, incremental, update cycle.
Xiaodong Hong +3 more
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HYCOM Consortium for Data-assimilative Ocean Modeling
2001Abstract : The long-term goal is to make HYCOM (HYbrid Coordinate Ocean Model) a state of the art community ocean model with data assimilation capability that can (1) be used in a wide range of ocean-related research, (2) be used in a next generation eddy-resolving global ocean prediction system and (3) be coupled to a variety of other models ...
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Assimilation of Drifter Data in a Circulation Model of the Indian Ocean
IEEE Geoscience and Remote Sensing Letters, 2012Assimilation of drifter data in a circulation model of the Indian Ocean has been explored in the study. Assimilation has been effected using the approach of nudging. The impact of such assimilation has been quantified by comparing the sea level anomalies simulated in runs with and without assimilation against independent observations derived by ...
Manisha Santoki +4 more
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Variational Data Assimilation for the Global Ocean
2013A fully three dimensional, multivariate, variational ocean data assimilation system has been developed that produces simultaneous analyses of temperature, salinity, geopotential and vector velocity. The analysis is run in real-time and is being evaluated as the data assimilation component of the Hybrid Coordinate Ocean Model (HYCOM) forecast system at ...
James A. Cummings, Ole Martin Smedstad
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A multivariate balance operator for variational ocean data assimilation
Quarterly Journal of the Royal Meteorological Society, 2005AbstractIt is common in meteorological applications of variational assimilation to specify the error covariances of the model background state implicitly via a transformation from model space where variables are highly correlated to a control space where variables can be considered to be approximately uncorrelated.
Weaver, Anthony T. +4 more
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