@Article{SousasantosKherSobr:2017:AlPoEq,
author = "Sousasantos, Jonas de and Kherani, Esfhan Alam and Sobral,
Jos{\'e} Humberto Andrade",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "An alternative possibility to equatorial plasma bubble forecasting
through mathematical modeling and Digisonde data",
journal = "Journal of Geophysical Research: Space Physics",
year = "2017",
volume = "122",
number = "2",
pages = "2079--2088",
month = "Feb.",
abstract = "Equatorial plasma bubbles (EPBs), or large-scale plasma depleted
regions, are one of the subjects of great interest in space
weather research since such phenomena have been extensively
reported to cause strong degrading effects on transionospheric
radio propagation at low latitudes, especially over the Brazilian
region, where satellite communication interruptions by the EPBs
have been, frequently, registered. One of the most difficult tasks
for this field of scientific research is the forecasting of such
plasma-depleted structures. This forecasting capability would be
of significant help for users of positioning/navigation systems
operating in the low-latitude/equatorial region all over the
world. Recently, some efforts have been made trying to assess and
improve the capability of predicting the EPB events. The purpose
of this paper is to present an alternative approach to EPB
prediction by means of the use of mathematical numerical
simulation associated with ionospheric vertical drift, obtained
through Digisonde data, focusing on telling beforehand whether
ionospheric plasma instability processes will evolve or not into
EPB structures. Modulations in the ionospheric vertical motion
induced by gravity waves prior to the prereversal enhancement
occurrence were used as input in the numerical model. A comparison
between the numerical results and the observed EPB phenomena
through CCD all-sky image data reveals a considerable coherence
and supports the hypothesis of a capability of short-term
forecasting.",
doi = "10.1002/2016JA023241",
url = "http://dx.doi.org/10.1002/2016JA023241",
issn = "2169-9380",
language = "en",
targetfile = "sousa_jonas.pdf",
urlaccessdate = "27 abr. 2024"
}