×

Application of continuous data assimilation in high-resolution ocean modeling. (English) Zbl 07893904

Summary: We demonstrate a formulation of the Azouani-Olson-Titi (AOT) algorithm in the MPAS-Ocean implementation of the primitive equations of the ocean, presenting global ocean simulations with realistic coastlines and bathymetry. We observe an exponentially fast decay in the error before reaching a certain error level, which depends on the terms involved and whether the AOT feedback control term was handled implicitly or explicitly. A wide range of errors was observed for both schemes, with the implicit scheme typically exhibiting lower error levels, depending on the specific physical terms included in the model. Several factors seem to be contributing to this wide range, but the vertical mixing term is demonstrated to be an especially problematic term. This study provides insight into the promises and challenges of adapting the AOT algorithm to the setting of high-resolution, realistic ocean models.

MSC:

86A05 Hydrology, hydrography, oceanography
35F50 Systems of nonlinear first-order PDEs
35Q86 PDEs in connection with geophysics
37N10 Dynamical systems in fluid mechanics, oceanography and meteorology

References:

[1] D. A. Albanez, H. J. Nussenzveig Lopes, and E. S. Titi. Continuous data assimilation for the three-dimensional Navier-Stokes-α model. Asymptotic Anal., 97(1-2):139-164, 2016. · Zbl 1344.35078
[2] R. A. Anthes. Data assimilation and initialization of hurricane prediction models. J. Atmos. Sci., 31(3):702-719, 1974.
[3] M. Asch, M. Bocquet, and M. Nodet. Data Assimilation: Methods, Algorithms, and Applications. SIAM, 2016.
[4] A. Azouani, E. Olson, and E. S. Titi. Continuous data assimilation using general interpolant observables. J. Nonlinear Sci., 24(2):277-304, 2014. · Zbl 1291.35168
[5] A. Azouani and E. S. Titi. Feedback control of nonlinear dissipative systems by finite deter-mining parameters-a reaction-diffusion paradigm. Evol. Equ. Control Theory, 3(4):579-594, 2014. · Zbl 1304.35715
[6] H. Bessaih, E. Olson, and E. S. Titi. Continuous data assimilation with stochastically noisy data. Nonlinearity, 28(3):729-753, 2015. · Zbl 1308.35161
[7] A. Biswas, Z. Bradshaw, and M. Jolly. Convergence of a mobile data assimilation scheme for the 2D Navier-Stokes equations. arXiv:2210.11282, 2022.
[8] A. Biswas, Z. Bradshaw, and M. S. Jolly. Data assimilation for the Navier-Stokes equations using local observables. SIAM J. Appl. Dyn. Syst., 20(4):2174-2203, 2021. · Zbl 1480.35309
[9] E. Carlson, J. Hudson, and A. Larios. Parameter recovery for the 2 dimensional Navier-Stokes equations via continuous data assimilation. SIAM J. Sci. Comput., 42(1):A250-A270, 2020. · Zbl 1474.35515
[10] E. Carlson, J. Hudson, A. Larios, V. R. Martinez, E. Ng, and J. Whitehead. Dynamically learning the parameters of a chaotic system using partial observations. Discrete Contin Dyn Syst Ser A, 42(8):3809-3839, 2022. · Zbl 1502.37092
[11] E. Carlson, A. Larios, and E. S. Titi. Super-exponential convergence rate of a nonlinear continuous data assimilation algorithm: The 2D Navier-Stokes equations paradigm. 2023. (Submitted) arXiv:2304.01128.
[12] E. Carlson, L. Van Roekel, M. Petersen, H. C. Godinez, and A. Larios. CDA algorithm imple-mented in MPAS-O to improve eddy effects in a mesoscale simulation. 2023. (Submitted).
[13] E. Celik and E. Olson. Data assimilation using time-delay nudging in the presence of Gaus-sian noise. arXiv e-prints, 2022.
[14] E. Celik, E. Olson, and E. S. Titi. Spectral filtering of interpolant observables for a discrete-in-time downscaling data assimilation algorithm. SIAM J. Appl. Dyn. Syst., 18(2):1118-1142, 2019. · Zbl 1428.35276
[15] S. Desamsetti, H. Dasari, S. Langodan, O. Knio, I. Hoteit, and E. S. Titi. Efficient dynamical downscaling of general circulation models using continuous data assimilation. Quarterly Journal of the Royal Meteorological Society, 2019.
[16] A. E. Diegel and L. G. Rebholz. Continuous data assimilation and long-time accuracy in a C 0 interior penalty method for the Cahn-Hilliard equation. Appl. Math. Comput., 424:Paper No. 127042, 22, 2022. · Zbl 1510.65242
[17] Y. J. Du and M.-C. Shiue. Analysis and computation of continuous data assimilation algo-rithms for Lorenz 63 system based on nonlinear nudging techniques. J. Computat. and Appl. Math., 386:113246, 2021. · Zbl 1461.65210
[18] D. Engwirda. Locally-optimal Delaunay-refinement and optimisation-based mesh generation. PhD thesis, School of Mathematics and Statistics, The University of Sydney, 2014.
[19] D. Engwirda. Voronoi-based point-placement for three-dimensional Delaunay-refinement. Procedia Engineering, 124:330-342, 2015.
[20] D. Engwirda. Conforming restricted Delaunay mesh generation for piecewise smooth com-plexes. Procedia Engineering, 163:84-96, 2016.
[21] D. Engwirda. Generalised primal-dual grids for unstructured co-volume schemes. J. Comp. Phys., 375:155-176, 2018. · Zbl 1416.65325
[22] D. Engwirda and D. Ivers. Off-centre steiner points for Delaunay-refinement on curved surfaces. Computer-Aided Design, 72:157-171, 2016.
[23] A. Farhat, N. E. Glatt-Holtz, V. R. Martinez, S. A. McQuarrie, and J. P. Whitehead. Data as-similation in large Prandtl Rayleigh-Bénard convection from thermal measurements. SIAM J. Appl. Dyn. Syst., 19(1):510-540, 2020. · Zbl 1434.76041
[24] A. Farhat, M. S. Jolly, and E. S. Titi. Continuous data assimilation for the 2D Bénard convec-tion through velocity measurements alone. Phys. D, 303:59-66, 2015. · Zbl 1364.76053
[25] A. Farhat, A. Larios, V. R. Martinez, and J. P. Whitehead. Identifying the body force from partial observations of a 2D incompressible velocity field. (Submitted) arXiv:2302.04701, 2023.
[26] A. Farhat, E. Lunasin, and E. S. Titi. Abridged continuous data assimilation for the 2D Navier-Stokes equations utilizing measurements of only one component of the velocity field. J. Math. Fluid Mech., 18(1):1-23, 2016. · Zbl 1334.35202
[27] A. Farhat, E. Lunasin, and E. S. Titi. Data assimilation algorithm for 3D Bénard convection in porous media employing only temperature measurements. J. Math. Anal. Appl., 438(1):492-506, 2016. · Zbl 1334.35230
[28] A. Farhat, E. Lunasin, and E. S. Titi. On the Charney conjecture of data assimilation employ-ing temperature measurements alone: the paradigm of 3D planetary geostrophic model. Mathematics of Climate and Weather Forecasting, 2(1), 2016. · Zbl 1364.86017
[29] A. Farhat, E. Lunasin, and E. S. Titi. Continuous data assimilation for a 2D Bénard convection system through horizontal velocity measurements alone. J. Nonlinear Sci., pages 1-23, 2017.
[30] C. Foias, C. F. Mondaini, and E. S. Titi. A discrete data assimilation scheme for the solutions of the two-dimensional Navier-Stokes equations and their statistics. SIAM J. Appl. Dyn. Syst., 15(4):2109-2142, 2016. · Zbl 1362.35208
[31] T. Franz, A. Larios, and C. Victor. The bleeps, the sweeps, and the creeps: Convergence rates for dynamic observer patterns via data assimilation for the 2D Navier-Stokes equations. Comput. Methods Appl. Mech. Engrg., 392:Paper No. 114673, 19, 2022. · Zbl 1507.76038
[32] M. Gardner, A. Larios, L. G. Rebholz, D. Vargun, and C. Zerfas. Continuous data assimila-tion applied to a velocity-vorticity formulation of the 2D Navier-Stokes equations. Electron. Res. Arch., 29(3):2223-2247, 2021. · Zbl 1468.65141
[33] M. Gesho, E. Olson, and E. S. Titi. A computational study of a data assimilation algorithm for the two-dimensional Navier-Stokes equations. Commun. Comput. Phys., 19(4):1094-1110, 2016. · Zbl 1373.76027
[34] J.-C. Golaz, P. M. Caldwell, L. P. V. Roekel, M. R. Petersen, Q. Tang, J. D. Wolfe, G. Abeshu, V. Anantharaj, X. S. Asay-Davis, D. C. Bader, S. A. Baldwin, G. Bisht, P. A. Bogenschutz, M. Branstetter, M. A. Brunke, S. R. Brus, S. M. Burrows, P. J. Cameron-Smith, A. S. Donahue, M. Deakin, R. C. Easter, K. J. Evans, Y. Feng, M. Flanner, J. G. Foucar, J. G. Fyke, B. M. Griffin, C. Hannay, B. E. Harrop, M. J. Hoffman, E. C. Hunke, R. L. Jacob, D. W. Jacobsen, N. Jeffery, P. W. Jones, N. D. Keen, S. A. Klein, V. E. Larson, L. R. Leung, H.-Y. Li, W. Lin, W. H. Lipscomb, P.-L. Ma, S. Mahajan, M. E. Maltrud, A. Mametjanov, J. L. McClean, R. B. McCoy, R. B. Neale, S. F. Price, Y. Qian, P. J. Rasch, J. E. J. R. Eyre, W. J. Riley, T. D. Ringler, A. F. Roberts, E. L. Roesler, A. G. Salinger, Z. Shaheen, X. Shi, B. Singh, J. Tang, M. A. Taylor, P. E. Thornton, A. K. Turner, M. Veneziani, H. Wan, H. Wang, S. Wang, D. N. Williams, P. J. Wolfram, P. H. Worley, S. Xie, Y. Yang, J.-H. Yoon, M. D. Zelinka, C. S. Zender, X. Zeng, C. Zhang, K. Zhang, Y. Zhang, X. Zheng, T. Zhou, and Q. Zhu. The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution. J. Adv. Model. Earth Sy., 11(7):2089-2129, 2019.
[35] M. A. E. R. Hammoud, E. S. Titi, I. Hoteit, and O. Knio. Cdanet: A physics-informed deep neural network for downscaling fluid flows. Journal of Advances in Modeling Earth Systems, 14(12):e2022MS003051, 2022.
[36] K. Hayden, E. Olson, and E. S. Titi. Discrete data assimilation in the Lorenz and 2D Navier-Stokes equations. Phys. D, 240(18):1416-1425, 2011. · Zbl 1302.76048
[37] J. E. Hoke and R. A. Anthes. The initialization of numerical models by a dynamic-initialization technique. Monthly Weather Review, 104(12):1551-1556, 1976.
[38] M. S. Jolly, V. R. Martinez, E. J. Olson, and E. S. Titi. Continuous data assimilation with blurred-in-time measurements of the surface quasi-geostrophic equation. Chin. Ann. Math. Ser. B, 40(5):721-764, 2019. · Zbl 1427.35204
[39] M. S. Jolly, V. R. Martinez, and E. S. Titi. A data assimilation algorithm for the subcritical surface quasi-geostrophic equation. Adv. Nonlinear Stud., 17(1):167-192, 2017. · Zbl 1358.35091
[40] S. Lakshmivarahan and J. M. Lewis. Nudging methods: A critical overview. In Data As-similation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II), pages 27-57. Springer, 2013.
[41] A. Larios and Y. Pei. Approximate continuous data assimilation of the 2D Navier-Stokes equations via the Voigt-regularization with observable data. Evol. Equ. Control Theory, 9(3):733-751, 2020. · Zbl 1452.35133
[42] A. Larios and Y. Pei. Nonlinear continuous data assimilation. Evol. Equ. Control Theory, 2024. (. · Zbl 1536.34051
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.