Stability Studies of a Coupled Model to Perturbation of Initial Data

Main Article Content

Konstantin Pavlovich Belyaev
Gury Mikhaylovich Mikhaylov
Alexey Nikolaevich Salnikov
Natalia Pavlovna Tuchkova

Abstract

The stability problem is considered in terms of the classical Lyapunov definition. For this, a set of initial conditions is set, consisting of their preliminary calculations, and the spread of the trajectories obtained as a result of numerical simulation is analyzed. This procedure is implemented as a series of ensemble experiments with a joint MPI-ESM model of the Institute of Meteorology M. Planck (Germany). For numerical modeling, a series of different initial values of the characteristic fields was specified and the model was integrated, starting from each of these fields for different time periods. Extreme ocean level characteristics over a period of 30 years were studied. The statistical distribution was built, the parameters of this distribution were estimated, and the statistical forecast for 5 years in advance was studied. It is shown that the statistical forecast of the level corresponds to the calculated forecast obtained by the model. The localization of extreme level values was studied and an analysis of these results was carried out. Numerical calculations were performed on the Lomonosov-2 supercomputer of Lomonosov Moscow State University.

Article Details

Author Biographies

Konstantin Pavlovich Belyaev

Leading scientist of Shirshov Institute of Oceanology, Russian Academy of Science. Doctor of science, professor of Dept of Appiied Math and Cybernetics, Lomonosov Moscow State University. Research interests – math modelling and data assimilation, statistical analysis of natural data.

Gury Mikhaylovich Mikhaylov

Leading scientist of Dorodnicyn computing center FRC SCS RAS, PhD in physics with a math degree. Research interests include architecture of computing systems and networks, computing and information technology.

Alexey Nikolaevich Salnikov

Leading researcher Dept of Appiied Math and Cybernetics, Lomonosov Moscow State University, PhD in physics with a math degree. Research interests include bioinformatics, parallel and supercomputing programming

Natalia Pavlovna Tuchkova

Senior researcher of Dorodnicyn computing center FRC SCS RAS, PhD in physics with a math degree, graduated from CS Faculty of Lomonosov MSU. The expert in the field of algorithmic languages and information technologies.

References

Bronselaer B., Winton M., Griffies S.M., Stouffer R.J., Hurlin W.J., Rodgers K., Russell J.L. Change in future climate due to Antarctic meltwater // Nature. 2018. V. 564. Issue 7734. P. 53–58. https://www.nature.com/articles/s41586-018-0712-z (доступно 07.11.2019)

Holt J., Polton J., Huthnance J., Wakelin S., Enda O'Dea E., Harle J., Yool A., Artioli Y., Blackford Y., Siddorn J., Inall M. Climate-Driven Change in the North Atlantic and Arctic Oceans Can Greatly Reduce the Circulation of the North Sea // Geophysical Research Letters. 2018. https://doi.org/10.1029/2018GL078878 (доступно 07.11.2019)

Jungclaus J.H., Fischer N., Haak H., Lohmann K., Marotzke J., Matei D., Mikolajewicz U., Notz D., Storch J.S. Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model // J. of Advances in Modeling Earth Systems. 2013. Issue 2. P. 422–446. https://doi.org/10.1002/jame.20023 (доступно 07.11.2019)

Taylor K.E., Stouffer R.J., Meehl G.A. An overview of CMIP5 and the experiment design // Bulletin American Meteorological Society. 2012. V. 93. No. 4. https://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-11-00094.1 (доступно 07.11.2019)

Марчук Г.И., Дымников В.П., Залесный В.Б. Математические модели в геофизической гидродинамике и численные методы их реализации. Л.: Гидрометиздат, 1987. 296 с.

Наац В.И., Наац И.Э. Математические модели и численные методы в задачах экологического мониторинга атмосферы. М.: ФИЗМАТЛИТ, 2010. 328 с.

The Intergovernmental Panel on Climate Change. https://www.ipcc.ch/ (доступно 01.07.2019)

Breckling S.M., Pahlevani N.F. A sensitivity study of the Navier-Stokes-α model // Computers and Mathematics with Applications. 2018. V. 75. P. 666-689.

Belyaev K.P., Kirchner I., Kuleshov A.A., Tuchkova N.P. Numerical Realization of Hybrid Data Assimilation Algorithm in Ensemble Experiments with the MPIESM Coupled Model. In: Velarde M., Tarakanov R., Marchenko A. (eds). The Ocean in Motion. Springer Oceanography. 2018. P. 447–459. https://doi.org/ 10.1007/978-3-319-71934-4_27

Baehr J., Fröhlich K., Botzet M. et al. The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model // Climate Dynamic. 2015. V. 44. Issue 9-10. P. 2723–2735. https://doi.org/ 10.1007/s00382-014-2399-7

Notz D., Haumann F.A., Haak H., Jungclaus J.H., Marotzke J. Arctic sea-ice evolution as modeled by Max Planck Institute for meteorology’s Earth system model // J. of Advances in Modeling Earth Systems. 2013. V. 5. P. 173–194. https://doi.org/ 10.1002/jame.20016 (доступно 07.11.2019)

Global warming of 1.5 °C https://www.ipcc.ch/sr15/ (access 01.07.2019)

WMO Statement on the State of the Global Climate in 2019. https://library.wmo.int/doc_num.php?explnum_id=5789 (доступно 07.11.2019)

Koul V., Schrum C., Düsterhus A., Baehr J. Atlantic Inflow to the North Sea Modulated by the Subpolar Gyre in a Historical Simulation with MPI‐ESM // J. of Geophysical Research: Oceans, 2019. V. 124. Issue 3. P. 1807–1826. https://doi.org/ 10.1029/2018JC014738 (доступно 07.11.2019)