ARGO data assimilation into the ocean dynamics model with high spatial resolution using Ensemble Optimal Interpolation (EnOI)

Kaurkin, Maxim; Ibrayev, R. A.; Belyaev, Konstantin

doi:10.1134/s0001437016060059

Cited by 18 publications

(13 citation statements)

References 19 publications

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“…These data were used to calculate by the Monte-Carlo method the vector С as an ensemble average of the difference between two parameters in two successive model calculations divided by the time pitch and the model error covariance matrix Q. It was established in previous investigations [14] that it is sufficient for data assimilation to have an ensemble of about 50 values for each ocean characteristic (temperature, salinity, horizontal and vertical velocities, ocean level, etc.). Therefore, the annual averages for the conventional 1900-1950 were used as the ensemble's components.…”

Section: Model Experimentsmentioning

confidence: 99%

“…It should be noted that a great contribution to the development of this theory and its application was made by Soviet (Russian) researchers under the leadership of the Academician A. S. Sarkisyan [13]. As for the recent publications in this domain, we should note [14]. On the whole, this research field is actively and successfully developed in Russia and abroad.…”

Section: Introductionmentioning

confidence: 96%

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Estimation of the Meridional Heat and Mass Transport in the South Atlantic by Using the Joint Atmosphere and Ocean Circulation Model with Data Assimilation and Visualization Facilities

Belyaev¹,

Кулешов²,

Tuchkova³

2019

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The joint ocean-Earth-atmosphere model of the Max Planck Institute for Meteorology with application of original data assimilation methods are used to estimate the meridional heat and mass flows. The CTD-sections of temperature and salinity across the Atlantic Ocean for 1991-1995 obtained in the course of the WOCE (The World Ocean Circulation Experiment) international experiment are used as observation data. The sections contain about 650 stations; each of them provides from 100 to 3000 measurements from the sea surface to the bottom. In our study both the control estimates for the velocities of currents and those with assimilation of the data of these experiments are obtained. Using visualization facilities, we have shown how data assimilation changes the model characteristics, including velocities of currents and temperature fields at different sea levels. The graphs demonstrate the influence of the change in the initial field after data assimilation on the results of the model calculations after 6 and 11 months of integration for both the observed model characteristics and those which are not observed directly. The Generalized Kalman Filter (GKF) method which coincides in a particular case with the classical Ensemble Kalman Filter (EnKF) is used as the data assimilation method. The results of calculations of the heat and mass flows are analyzed and compared with those of control calculations with no data assimilation. The calculations were performed on the supercomputers-Mistral‖ in DKRZ (Deutsches Klimarechenzentrum,

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Section: Model Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Estimation of the Meridional Heat and Mass Transport in the South Atlantic by Using the Joint Atmosphere and Ocean Circulation Model with Data Assimilation and Visualization Facilities

Belyaev¹,

Кулешов²,

Tuchkova³

2019

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“…The method of adaptive statistics, which allows to consider the changes in the dispersion of forecast errors in time and space, is more advanced among the approaches presented in [4,5]. Unlike the methods for assimilation of the ocean (sea) hydrophysical parameter measurements in the model based on Kalman ensemble filters [6][7][8] and variational assimilation of observational data [9][10][11], the adaptive statistics method does not require the application of powerful computing systems.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2018

PhO

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Retrospective analysis of the Black Sea hydrophysical fields (1993-2014) is carried out including assimilation of the three-dimensional fields of the temperature and salinity pseudo measurements reconstructed before in the model on the horizons within the layer 63-500 m by the adaptive statistics method. To compare root-mean-square deviations of the temperature and salinity fields from the observations, the reanalysis data (1993-2012) comprising assimilation of the temperature and salinity unperturbed profiles in the model are used. Variability of temperature and salinity (density) profiles in the main pycnocline is reproduced more accurately in the reanalysis for 1993-2014. Root-meansquare deviations of the sea level fields (resulted from the reanalysis for 1993-2014) from the altimetry ones in the first decade of seasonal and inter-annual variability are smaller than those (estimated in the same way) obtained from the reanalysis data for 1992-2015 in which the AVISO data and the sea surface temperature are assimilated. The root-mean-square deviations of the sea level increase in the second decade of the period. It is explained by the fact that decrease of the training set is accompanied by lowering of accuracy in reconstructing the fields of the temperature and salinity pseudo-measurements based on the altimetry and Argo buoys' data. Synoptic variability of the sea currents' fields in 1993-2014 is studied by analyzing the maps of the sea level integral dispersion. The values of sea level dispersion are found to be high on vast areas in the western and eastern parts of the basin. It is conditioned by generation and movement of the Sevastopol anticyclone, formation of synoptic vortices in the southwestern region of the western cyclonic water cycle, dynamics and evolution of the Caucasian anticyclonic vortices and the Batumi anticyclone. The local area to the northwest off Sinop is also noted.

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“…The atmospheric fields were preset by the results of the ERA-Interim reanalysis [18]. Such an approach is methodologically close to obtaining the ensemble of the model state vectors for assessing the covariations' matrix in the developed parallel algorithm of the ensemble optimal interpolation described in [21]. Let…”

Section: Selection Of the Relaxation Parameter In The Transport-diffumentioning

confidence: 99%

Application of the Adaptive Statistics Method for Reanalysis of the Black Sea Fields Including Assimilation of the Temperature and Salinity Pseudo-Measurements in the Model

Коротаев¹,

Knysh²,

Лишаев³

et al. 2018

PhO

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To assimilate the thermohaline parameters' pseudo-measurements in the model, applied is the method of adaptive statistics, the characteristic feature of which consists in adjusting the three-dimensional errors' dispersions of the temperature and salinity forecast to the water circulation in the basin. The three-dimensional fields of the temperature and salinity pseudo-measurements are reconstructed in the 100-500 m layer based on the altimetry data and the Argo buoys' limited measurements. The method is approved and validated by comparing the sea fields reconstructed in the reanalysis for 2012 with the Argo measurements. It is revealed that on the horizons 100, 113 and 125 m, the dispersions of differences (residuals) between the temperature pseudo-measurements and its model values somewhat exceed the model dispersion; whereas on the horizons within the 150-500 m layer, they are smaller. The daily standard deviation of the model level (relative to that reconstructed using the altimetry data) is smaller than the deviation calculated in the forecast; and during the March -September period, it is lower than the standard deviation resulted from the pseudo-measurements' assimilation by the simplified method. Resolution of the mesoscale vortices in the currents' fields is higher in case the method of adaptive statistics is used.

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ARGO data assimilation into the ocean dynamics model with high spatial resolution using Ensemble Optimal Interpolation (EnOI)

Cited by 18 publications

References 19 publications

Estimation of the Meridional Heat and Mass Transport in the South Atlantic by Using the Joint Atmosphere and Ocean Circulation Model with Data Assimilation and Visualization Facilities

Estimation of the Meridional Heat and Mass Transport in the South Atlantic by Using the Joint Atmosphere and Ocean Circulation Model with Data Assimilation and Visualization Facilities

Untitled

Application of the Adaptive Statistics Method for Reanalysis of the Black Sea Fields Including Assimilation of the Temperature and Salinity Pseudo-Measurements in the Model

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