{"title":"Probabilistic Analysis of the Coefficients of Stochastic Differential Equations in Their Modeling of the Air–Sea Interaction in the North Atlantic","authors":"K. P. Belyaev, N. P. Tuchkova, K. A. Romashina","doi":"10.1134/s1995080224602406","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The observational data for 1979–2018 in the North Atlantic region\nhave been used for the analysis of the heat fluxes. The dynamics\nof air-sea interaction between ocean and atmosphere has been\nmodeled by the stochastic differential equation (SDE) which use\nthe heat fluxes observations taken from those databased. The\ncoefficients of the SDE represented the diffusion stochastic\nprocess have been statistically defined from the original dataset.\nEarlier the existence and uniqueness of the solution in strong\nsense of SDE generated by the modeled diffusion process has been\nproved. In the current work the drift and diffusion coefficients\nhave been smoothed and approximated by the trigonometric functions\nwith sought amplitude and phase characteristics within chosen\nyear. Their spatial and temporal intra-annual variability of those\ncharacteristics has been studied and analyzed. Also, the\ncorresponding Fokker–Planck–Kolmogorov (FPK) equation for the\nSDE with smoothed coefficients has been constructed and\nnumerically solved. Numerical calculations realized on the\nLomonosov-2 supercomputer of the Lomonosov Moscow State\nUniversity.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":"181 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lobachevskii Journal of Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1134/s1995080224602406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
The observational data for 1979–2018 in the North Atlantic region
have been used for the analysis of the heat fluxes. The dynamics
of air-sea interaction between ocean and atmosphere has been
modeled by the stochastic differential equation (SDE) which use
the heat fluxes observations taken from those databased. The
coefficients of the SDE represented the diffusion stochastic
process have been statistically defined from the original dataset.
Earlier the existence and uniqueness of the solution in strong
sense of SDE generated by the modeled diffusion process has been
proved. In the current work the drift and diffusion coefficients
have been smoothed and approximated by the trigonometric functions
with sought amplitude and phase characteristics within chosen
year. Their spatial and temporal intra-annual variability of those
characteristics has been studied and analyzed. Also, the
corresponding Fokker–Planck–Kolmogorov (FPK) equation for the
SDE with smoothed coefficients has been constructed and
numerically solved. Numerical calculations realized on the
Lomonosov-2 supercomputer of the Lomonosov Moscow State
University.
期刊介绍:
Lobachevskii Journal of Mathematics is an international peer reviewed journal published in collaboration with the Russian Academy of Sciences and Kazan Federal University. The journal covers mathematical topics associated with the name of famous Russian mathematician Nikolai Lobachevsky (Lobachevskii). The journal publishes research articles on geometry and topology, algebra, complex analysis, functional analysis, differential equations and mathematical physics, probability theory and stochastic processes, computational mathematics, mathematical modeling, numerical methods and program complexes, computer science, optimal control, and theory of algorithms as well as applied mathematics. The journal welcomes manuscripts from all countries in the English language.