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  • 1
    Electronic Resource
    Electronic Resource
    Wave mechanism of the seasonal variability of the largescale current field in the northern Tropical Atlantic (1991)
    Springer
    Physical oceanography 2 (1991), S. 329-340 
    Details
    ISSN: 0928-5105
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract A spatial-temporal analysis of the density field in the large-scale hydrological observation areas in the Tropical Atlantic is carried out. The spectral maximum corresponding to the first baroclinic mode of the planetary Rossby wave is discriminated and studied. It is shown that the seasonal transformation of the large-scale circulation of the current field is connected with the propagation of this wave. A simple quasi-geostrophic model is suggested which describes the seasonal variability of the North Equatorial Countercurrent. The results obtained by this model are compared with the hydrological survey data.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02197766
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    Paper (German National Licenses)
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  • 2
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    The local ensemble transform Kalman filter and the running-in-place algorithm applied to a global ocean general circulation model (2013)
    Copernicus
    Details
    Publication Date: 2013-11-26
    Description: The most widely used methods of data assimilation in large-scale oceanography, such as the Simple Ocean Data Assimilation (SODA) algorithm, specify the background error covariances and thus are unable to refine the weights in the assimilation as the circulation changes. In contrast, the more computationally expensive Ensemble Kalman Filters (EnKF) such as the Local Ensemble Transform Kalman Filter (LETKF) use an ensemble of model forecasts to predict changes in the background error covariances and thus should produce more accurate analyses. The EnKFs are based on the approximation that ensemble members reflect a Gaussian probability distribution that is transformed linearly during the forecast and analysis cycle. In the presence of nonlinearity, EnKFs can gain from replacing each analysis increment by a sequence of smaller increments obtained by recursively applying the forecast model and data assimilation procedure over a single analysis cycle. This has led to the development of the "running in place" (RIP) algorithm by Kalnay and Yang (2010) and Yang et al. (2012a,b) in which the weights computed at the end of each analysis cycle are used recursively to refine the ensemble at the beginning of the analysis cycle. To date, no studies have been carried out with RIP in a global domain with real observations. This paper provides a comparison of the aforementioned assimilation methods in a set of experiments spanning seven years (1997–2003) using identical forecast models, initial conditions, and observation data. While the emphasis is on understanding the similarities and differences between the assimilation methods, comparisons are also made to independent ocean station temperature, salinity, and velocity time series, as well as ocean transports, providing information about the absolute error of each. Comparisons to independent observations are similar for the assimilation methods but the observation-minus-background temperature differences are distinctly lower for LETKF and RIP. The results support the potential for LETKF to improve the quality of ocean analyses on the space and timescales of interest for seasonal prediction and for RIP to accelerate the spin up of the system.
    Print ISSN: 1023-5809
    Electronic ISSN: 1607-7946
    Topics: Geosciences , Physics
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
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    Wave mechanism of the seasonal variability of the largescale current field in the northern Tropical Atlantic (1991)
    Springer
    Details
    Publication Date: 1991-09-01
    Print ISSN: 0928-5105
    Electronic ISSN: 1573-160X
    Topics: Geosciences , Physics
    Published by Springer
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    PAPER CURRENT
  • 4
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    The Ocean Reanalyses Intercom parison Project (ORA - IP) (2015)
    Details
    Publication Date: 2022-06-20
    Description: Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.
    Description: This work has been partially funded by the European Commission funded projects MyOcean, MyOcean2 and COMBINE; by the GEMINA project-funded bythe Italian Ministry for Environment; by the NERC-funded VALOR project; by the NERC-funded NCEO program; by the Research Program on Climate Change adaptation of the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government; by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101); by NASA’s Modeling Analysis and Prediction Program under WBS 802678.02.17.01.25 and by the NASA Physical Oceanography Program; by the NOAA's Climate Observation Division (COD); by the LEFE/GMMC French national program.
    Description: Published
    Description: s80-s97
    Description: 4A. Clima e Oceani
    Description: JCR Journal
    Description: open
    Keywords: Global ocean–sea-ice modelling ; Ocean model comparisons ; DATA ASSIMILATION SCHEME ; multi-analysis ensemble ; Ocean climate ; 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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    PAPER (OA)
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