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Pavel Perezhogin
Pavel Perezhogin
PostDoc in Courant Institute of Mathematical Sciences, New York University
Adresă de e-mail confirmată pe phystech.edu - Pagina de pornire
Titlu
Citat de
Citat de
Anul
Benchmarking of machine learning ocean subgrid parameterizations in an idealized model
A Ross, Z Li, P Perezhogin, C Fernandez‐Granda, L Zanna
Journal of Advances in Modeling Earth Systems 15 (1), 2023
642023
Generative data‐driven approaches for stochastic subgrid parameterizations in an idealized ocean model
P Perezhogin, L Zanna, C Fernandez‐Granda
Journal of Advances in Modeling Earth Systems 15 (10), e2023MS003681, 2023
252023
Implementation and evaluation of a machine learned mesoscale eddy parameterization into a numerical ocean circulation model
C Zhang, P Perezhogin, C Gultekin, A Adcroft, C Fernandez‐Granda, ...
Journal of Advances in Modeling Earth Systems 15 (10), e2023MS003697, 2023
182023
Deterministic and stochastic parameterizations of kinetic energy backscatter in the NEMO ocean model in double-gyre configuration
P Perezhogin
IOP conference series: Earth and environmental science 386 (1), 012025, 2019
132019
Stochastic and deterministic kinetic energy backscatter parameterizations for simulation of the two-dimensional turbulence
PA Perezhogin, AV Glazunov, AS Gritsun
Russian Journal of Numerical Analysis and Mathematical Modelling 34 (4), 197-213, 2019
122019
Comparison of numerical advection schemes in two-dimensional turbulence simulation
PA Perezhogin, AV Glazunov, EV Mortikov, VP Dymnikov
Russian Journal of Numerical Analysis and Mathematical Modelling 32 (1), 47-60, 2017
122017
Testing of kinetic energy backscatter parameterizations in the NEMO ocean model
PA Perezhogin
Russian Journal of Numerical Analysis and Mathematical Modelling 35 (2), 69-82, 2020
112020
Optimal energy growth in stably stratified turbulent Couette flow
GV Zasko, AV Glazunov, EV Mortikov, YM Nechepurenko, PA Perezhogin
Boundary-Layer Meteorology 187 (1), 395-421, 2023
92023
Modeling of quasi-equilibrium states of a two-dimensional ideal fluid
PA Perezhogin, VP Dymnikov
Doklady Physics 62, 248-252, 2017
9*2017
Equilibrium states of finite-dimensional approximations of a two-dimensional incompressible inviscid fluid
PA Perezhogin, VP Dymnikov
Russian Journal of Nonlinear Dynamics 13 (1), 55-79, 2017
9*2017
Data-driven dimensionality reduction and causal inference for spatiotemporal climate fields
F Falasca, P Perezhogin, L Zanna
Physical Review E 109 (4), 044202, 2024
82024
Systems of hydrodynamic type that approximate two-dimensional ideal fluid equations
VP Dymnikov, PA Perezhogin
Izvestiya, Atmospheric and Oceanic Physics 54, 232-241, 2018
7*2018
Subgrid parameterizations of ocean mesoscale eddies based on Germano decomposition
P Perezhogin, A Glazunov
Journal of Advances in Modeling Earth Systems 15 (10), e2023MS003771, 2023
62023
Reliable coarse-grained turbulent simulations through combined offline learning and neural emulation
C Pedersen, L Zanna, J Bruna, P Perezhogin
arXiv preprint arXiv:2307.13144, 2023
52023
A stable implementation of a data‐driven scale‐aware mesoscale parameterization
P Perezhogin, C Zhang, A Adcroft, C Fernandez‐Granda, L Zanna
Journal of Advances in Modeling Earth Systems 16 (10), e2023MS004104, 2024
4*2024
Advanced parallel implementation of the coupled ocean–ice model FEMAO (version 2.0) with load balancing
P Perezhogin, I Chernov, N Iakovlev
Geoscientific Model Development 14 (2), 843-857, 2021
42021
Расчет эволюции трехмерной концентрации атмосферного углекислого газа в климатической модели ИВМ РАН
ЕМ Володин, ПА Пережогин
Труды Гидрометцентра России 357, 2015
32015
2D turbulence closures for the barotropic jet instability simulation
PA Perezhogin
Russian Journal of Numerical Analysis and Mathematical Modelling 35 (1), 21-35, 2020
22020
A priori and a posteriori analysis in Large eddy simulation of the two-dimensional decaying turbulence using Explicit filtering approach
P Perezhogin, A Glazunov
EGU General Assembly Conference Abstracts, EGU21-2382, 2021
12021
A new data-driven subgrid 2d turbulence parameterization and comparison with conventional kinetic energy backscatter parameterizations in NEMO ocean model
P Perezhogin
EGU General Assembly Conference Abstracts, 19890, 2020
12020
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