Analysis of Intra-Annual Variability of Heat Fluxes in the North Atlantic Based on Approximation of Trajectories of the Stochastic Diffusion Process

To analyze heat fluxes, observational data for 1979–2018 were used for the North Atlantic. The spatiotemporal variability of the total heat flux was modeled using stochastic diffusion. The coefficients of the stochastic differential equation were estimated by using nonparametric statistics. Previously, the existence and uniqueness of a solution in the strong sense of the stochastic differential equation generated by the constructed diffusion process was proven when Kolmogorov’s conditions were met. In this work, the coefficients of the equation were approximated using trigonometric polynomials whose amplitudes and phases depended on the flow values. Using a given series of 40 years in length from 1979 to 2018, spatial maps and time curves were constructed. The results are shown for 1999 and 2018, and their comparative analysis is also carried out. Numerical calculations were performed on the Lomonosov-2 supercomputer at Lomonosov Moscow State University.

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Publication Details

Journal
Automatic Documentation and Mathematical Linguistics
Published
2024-12-01
DOI
https://doi.org/10.3103/s0005105525700487
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.28
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article

Analysis of Intra-Annual Variability of Heat Fluxes in the North Atlantic Based on Approximation of Trajectories of the Stochastic Diffusion Process

Konstantin Belyaev, N. P. Tuchkova, G. M. Mikhaylov, K. A. Romashina
1 citations
Automatic Documentation and Mathematical Linguistics
Climate variability and models
0.28
article

Analysis of Intra-Annual Variability of Heat Fluxes in the North Atlantic Based on Approximation of Trajectories of the Stochastic Diffusion Process

Konstantin Belyaev, N. P. Tuchkova, G. M. Mikhaylov, K. A. Romashina
article en
1 citations

Abstract

To analyze heat fluxes, observational data for 1979–2018 were used for the North Atlantic. The spatiotemporal variability of the total heat flux was modeled using stochastic diffusion. The coefficients of the stochastic differential equation were estimated by using nonparametric statistics. Previously, the existence and uniqueness of a solution in the strong sense of the stochastic differential equation generated by the constructed diffusion process was proven when Kolmogorov’s conditions were met. In this work, the coefficients of the equation were approximated using trigonometric polynomials whose amplitudes and phases depended on the flow values. Using a given series of 40 years in length from 1979 to 2018, spatial maps and time curves were constructed. The results are shown for 1999 and 2018, and their comparative analysis is also carried out. Numerical calculations were performed on the Lomonosov-2 supercomputer at Lomonosov Moscow State University.

Automatic Documentation and Mathematical LinguisticsVol. 58(S6)
Lomonosov Moscow State University (RU), Institute of Oceanology. PP Shirshov Russian Academy of Sciences (RU), Dorodnitsyn Computing Centre (RU), Computing Center (RU)
Life below water
Openalex Percentile: Top 39%
Climate variability and models
0.28
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