ALL-RUSSIA OPEN ANNUAL CONFERENCES ON
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE
Principal physics, methods and techniques for monitoring the environment, potentially dangerous phenomena and objects
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Proceedings of the 16th Conference (November 12-16, 2018, Moscow, Russia)
Variational Data Assimilation of Satellite Observations in the Model of Sea Hydrothermodynamics
Eugene I. Parmuzin1,2, Valery I. Agoshkov1,3, Natalia B. Zakharova1, Victor P. Shutyaev1,2
- Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences (INM RAS), Moscow, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- Lomonosov Moscow State University, Moscow, Russia
eparmuzin@gmail.comDOI 10.21046/rorse2018.1
Recently, significant results have been achieved in studying and modeling the processes of large-scale sea and ocean variability. This is due to changes in the level of development of tools, methods and equipment. These include: new observational systems (satellites, ARGO buoys, etc.), information analysis methods and numerical algorithms, powerful computers that allow processing large information flows of calculations and observations. We consider the problem of four-dimensional variational data assimilation of satellite data on the sea surface temperature using a model of sea hydrothermodynamics developed at INM RAS in this paper. Problem state and methods for its solution are discussed, the results of numerical experiments with real data of satellite observations are presented, including cases when the observation data are known at the part of the water area.
Keywords: variational data assimilation, satellite observations, sea surface temperature, heat flux, sea hydrodynamics model
References: - [1] Agoshkov V.I., Assovskiy M.V., Parmuzin E.I., Zakharova N.B., Zalesny V.B., Shutyaev V.P. Variational assimilation of observation data in the mathematical model of the Black Sea taking into account the tide-generating forces, Russ. J. Numer. Anal. Math. Modelling, 2015, V. 30, No. 3, PP. 129–142. DOI: 10.1515/rnam-2015-0013
- [2] Agoshkov, V.I., Parmuzin, E.I., Zakharova, N.B., Shutyaev, V.P. Variational assimilation with covariance matrices of observation data errors for the model of the Baltic Sea dynamics, Russ. J. Numer. Anal. Math. Modelling, 2018, v. 33, no. 3, pp. 149-160. DOI: 10.1515/rnam-2018-0013
- [3] Agoshkov V.I., Gusev A.V., Diansky N.A., Oleinikov R.V. An algorithm for the solution of the ocean hydrothermodynamics problem with variational assimilation of the sea level function data, Russ. J. Numer. Anal. Math. Modelling, 2007, 22(2), pp. 1-10. DOI: 10.1515/RJNAMM.2007.007
- [4] Agoshkov V.I., Parmuzin E.I., Shutyaev V.P. A numerical algorithm of variational data assimilation for reconstruction of salinity fluxes on the ocean surface, Russ. J. Numer. Anal. Math. Modelling, 2008, 23(2), 135-161. DOI: 10.1515/RJNAMM.2008.009
- [5] Захарова Н.Б., Зотов А.Э. Обработка данных дистанционного зондирования о температуре поверхности Балтийского моря // Региональные проблемы дистанционного зондирования Земли: материалы V Междунар. Науч. конф., Красноярск, 11-14 сентября 2018 г. – Красноярск: Сиб. Федер. Ун-т, 2018. С. 318-321.
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Section 1. Methods of modeling various phenomena focused on assimilation of remote sensing data
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