Ivan Berezin

Mr. Ivan Berezin

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2019 in Izvestiya, Atmospheric and Oceanic Physics
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YTYu M. Timofeev
Yu M. Timofeev
IBIvan Berezin
Ivan Berezin
YVYana Virolainen
Yana Virolainen
MMMaria Makarova
Maria Makarova
APAlexander Polyakov
Alexander Polyakov
СФСтефани Фока
Стефани Фока
The results of studying spatial–temporal CO2variations near St. Petersburg in 2014–2017 based on satellite measurements (OCO-2 satellite) and ground-based spectroscopic and local...

1 January 2017 in Izvestiya, Atmospheric and Oceanic Physics
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Journal Article
Closed access
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IBIvan Berezin
Ivan Berezin
YTYu. M. Timofeyev
Yu. M. Timofeyev
YVYana Virolainen
Yana Virolainen
IFI. S. Frantsuzova
I. S. Frantsuzova
KVK. A. Volkova
K. A. Volkova
ISI. Slutsker
I. Slutsker
Water vapor plays a key role in weather and climate forming, which leads to the need for continuous monitoring of its content in different parts of the Earth. Intercomparison and validation of...

5 December 2022 in Universe
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IBIvan Berezin
Ivan Berezin
ATAndrey G. Tlatov
Andrey G. Tlatov
The Wang–Sheeley–Arge (WSA) solar wind (SW) model is based on the idea that weakly expanding coronal magnetic field tubes are associated with sources of fast SWs and vice versa. A parameter called the “flux tube expansion” (FTE) is used to determine the degree of expansion of magnetic tubes. The FTE is calculated based on the coronal magnetic field model, usually in the potential approximation. The second input parameter for the WSA model is the great circle distance from the base of the open magnetic field line in the photosphere to the boundary of the corresponding coronal hole (DCHB). These two coronal magnetic field parameters are related by an empirical relationship with the solar wind velocity near the Sun. The WSA model has shortcomings and does not fully explain the solar wind formation mechanisms. In the present work, we model various coronal magnetic field parameters in the potential-field source-surface (PFSS) approximation from a long series of magnetographic observations: the Solar Telescope-magnetograph for Operative Prognoses (STOP) (Kislovodsk Mountain Astronomical Station), the Helioseismic and magnetic imager (SDO/HMI), and data from the Wilcox Solar Observatory (WSO). Our main goal is to identify correlations between the coronal magnetic field parameters and the observed SW velocity in order to use them for modeling SW. We found that the SW velocity correlates relatively well with some geometric properties of the magnetic tubes, including the force line length, the latitude of the force line footpoints, and the DCHB. We propose a formula for calculating the SW velocity based on these parameters. The presented relationship does not use FTE and showed a better correlation with observations compared to the WSA model.

13 July 2016 in International Journal of Remote Sensing
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Journal Article
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YVYana Virolainen
Yana Virolainen
YTYury Timofeyev
Yury Timofeyev
IBIvan Berezin
Ivan Berezin
APAnatoly Poberovsky
Anatoly Poberovsky
APAlexander Polyakov
Alexander Polyakov
HIHamud Imhasin
Hamud Imhasin
Regular comparison of different systems for monitoring atmospheric integrated water vapour (IWV) is part of their testing and validation protocol. We compared coincident measurements of IWV over Saint Petersburg (Russia) from ground-based Fourier-transform spectrometer Bruker IFS 125 HR (FTIR) and microwave radiometer RPG-HATPRO (MW) at the Peterhof site between March 2013 and June 2015. This study is a contribution towards global efforts to make such inter-comparisons at various ground-based sites. Since FTIR measures solar radiance, the vast majority of coincident pairs correspond to the spring and summer seasons. The numbers of measurements in the dry season (from October to April) and in the wet season (from May to September) are almost identical, comprising 616 and 638 pairs, respectively. MW and FTIR data sets demonstrate a high level of agreement: the mean relative difference between MW and FTIR data is less than 3% (0.3 mm), with standard deviation from the means of about 4% (0.4 mm). Notwithstanding the short distance between both instruments (150 m), they can monitor different air masses: MW is a zenith-viewing instrument whereas FTIR follows the sun. We analysed the FTIR observation fields under different solar zenith and azimuth angles, taking into account the location of the Peterhof site between the Gulf of Finland and rural suburbs of Saint Petersburg. Although in general MW measurements slightly overestimated IWV in comparison with the FTIR data, we detected several episodes when FTIR gave higher values than MW. These episodes relate to the FTIR observations directed at the coastal region with more humid air than that above the measurement site. We may conclude at this stage of our investigations that the spatial inhomogeneity of humidity fields in the atmosphere causes the most significant differences between the two data sets. Detailed analysis of variation in spatial IWV, e.g. using a MW radiometer in angular scanning mode, is an issue for future research.

1 May 2016 in Atmospheric and Oceanic Optics
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IBIvan Berezin
Ivan Berezin
YTYu. M. Timofeyev
Yu. M. Timofeyev
YVYana Virolainen
Yana Virolainen
KVK. A. Volkova
K. A. Volkova

29 January 2023 in Physics
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ATAndrey G. Tlatov
Andrey G. Tlatov
IBIvan Berezin
Ivan Berezin
The magnetic field in the interplanetary medium is formed by the action of magnetic field sources on the photosphere of the Sun and currents in the expanding atmosphere of the Sun and the solar wind. In turn, the high-speed plasma flow changes the configuration of the magnetic field lines. The problem of determining the parameters of the magnetic field near the Sun is thus a three-dimensional problem of the interaction of the magnetic field and the plasma of the solar wind. We present analytical expressions for calculating the total magnetic field vector B→(r, θ, ϕ) (in spherical coordinates) for a radially expanding solar wind flow of finite conductivity. The parameters of the solar wind are given in the form of a dimensionless magnetic Reynolds number given as an arbitrary function of the radius, r: Rm = rσμv=ξ(r), where σ, μ, and v denote, respectively, the conductivity, magnetic permeability, and velocity of the solar wind. The solution for the magnetic field components is obtained in the form of a decomposition in spherical functions and a radial part depending on the distance from the Sun. Examples of calculations of the configuration of magnetic fields and structures of the solar corona for the solar eclipse of 21 August 2017 are given.