A Prototype of a Background Solar Wind Forecasting Service Based on MHD Modeling and WSA Boundary Conditions

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A prototype service for MHD modeling of the calm solar wind and forecasting the speed and density of solar wind particles in interplanetary space, similar to the NOAA and ESA services, has been created. The service consists of an MHD simulator, a module for processing simulation results, and a web interface. The simulator is based on the implementation of the TVDLF method in the PLUTO package. The boundary conditions of the model (density, radial velocity, magnetic field, temperature) at a distance of 0.1 AU from the origin are obtained regularly from the corresponding NOAA service, in which they are calculated according to the WSA model based on the magnetograms of the GONG network. Two modes of boundary conditions are available: constant and daily. The simulations were carried out on a uniform grid in the range of 0.1–1.7 AU by distance (512 elements), –60°...+60° by latitude (60 elements), 0°–360° by longitude (180 elements). The calculated particle velocity and density maps are compared with the NOAA SWPC and NASA CCMC calculations under the same boundary conditions. A retrospective comparison of the resulting forecasts with data from direct measurements (OMNI) was carried out.

作者简介

S. Arutyunyan

St. Petersburg State Electrotechnical University “LETI”, 197022, St. Petersburg, Russia

Email: dapavlov@etu.ru
Россия, Санкт-Петербург

A. Kodukov

St. Petersburg State Electrotechnical University “LETI”, 197022, St. Petersburg, Russia

Email: dapavlov@etu.ru
Россия, Санкт-Петербург

M. Subbotin

St. Petersburg State Electrotechnical University “LETI”, 197022, St. Petersburg, Russia

Email: dapavlov@etu.ru
Россия, Санкт-Петербург

D. Pavlov

St. Petersburg State Electrotechnical University “LETI”, 197022, St. Petersburg, Russia; St. Petersburg State University, 199034, St. Petersburg, Russia

编辑信件的主要联系方式.
Email: dapavlov@etu.ru
Россия, Санкт-Петербург; Россия, Санкт-Петербург

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版权所有 © С. Арутюнян, А. Кодуков, М. Субботин, Д. Павлов, 2023

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