@Article{ChenDeReChMoPi:2020:DeEmMo,
author = "Chen, Sony Su and Denardini, Clezio Marcos and Resende, Laysa
Cristina Ara{\'u}jo and Chagas, Ronan Arraes Jardim and Moro,
Juliano and Pican{\c{c}}o, Giorgio Arlan da Silva",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Development of an Empirical Model for Estimating the Quiet Day
Curve (QDC) Over the Brazilian Sector",
journal = "Radio Science",
year = "2020",
volume = "55",
number = "12",
pages = "e2020RS007105",
note = "{Setores de Atividade: Pesquisa e desenvolvimento
cient{\'{\i}}fico.}",
keywords = "Quiet Day Curve, Quiet Conditions, Geomagnetism, Space Weather.",
abstract = "The Embrace Magnetometer Network (Embrace MagNet) uses a series of
magnetometers over South America to monitor the Earths space
environment and to study space weather. One of the common
techniques used to study the effects of the magnetic disturbances
in the globe is through the Quiet Day Curve (QDC) of the
geomagnetic field components. These types of QDC are calculated
based on geomagnetic field data collected by magnetometers in the
5 quietest days for each month at each station. Thus, we developed
and implemented an empirical model based on the QDC H component
obtained by the Embrace MagNet. This model ought to be used as a
prediction device when data is not available. The proposed
algorithm is a function of the solar activity, the day of the
year, and the universal time, which was adjusted based on 12
stations across to the South America sector between 2010 and 2018.
Our results show that the values computed by this model are in
good agreement with the observational data for the QDC. Finally,
it is essential to mention that the QDC model presented in this
study is the only available forecasting tool of the Embrace MagNet
stations to the date, providing data with a high confidence level
in the Brazilian sector.",
doi = "10.1029/2020rs007105",
url = "http://dx.doi.org/10.1029/2020rs007105",
issn = "0048-6604",
label = "lattes: 8030262077949409 2 ChenNaReChMoPi:2020:DeEmMo",
language = "en",
targetfile = "chen_development.pdf",
url = "https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020RS007105",
urlaccessdate = "27 abr. 2024"
}