A global 3-D electron density reconstruction model based on radio occultation data and neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F21%3A00544520" target="_blank" >RIV/68378289:_____/21:00544520 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1364682621001577?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1364682621001577?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jastp.2021.105702" target="_blank" >10.1016/j.jastp.2021.105702</a>
Alternative languages
Result language
angličtina
Original language name
A global 3-D electron density reconstruction model based on radio occultation data and neural networks
Original language description
The accurate representation of the ionospheric electron density in 3-dimensions is a challenging problem because of the nature of horizontal and vertical structures on both small and large scales. This paper presents the development of a global three-dimensional (3-D) electron density reconstruction based on radio occultation data during 2006-2019 and neural networks. We demonstrate that the developed model based on COSMIC dataset only is capable of reproducing different ionospheric features when compared to independent datasets from ionosondes and incoherent scatter radars (ISR) in low, middle and high latitude regions. Following some existing modelling efforts based on similar or related datasets and technique we divided the problem into fine resolution grid cells of 5 degrees x15 degrees (geographic latitudes/longitudes) followed by development of the neural network subroutine per cell and later combining all the 864 sub-models to compile one global model. This approach has been demonstrated to be appropriate in enabling neural networks to learn, reproduce and generalise local and global behaviour of the ionospheric electron density. Based on ISR data, the 3D model improves maximum electron density of the F2 layer (NmF2) prediction by 10%-20% compared to IRI 2016 model during quiet conditions. For estimation of ionosonde ordinary critical frequency of the F2 layer (foF2) in 2009 at 1200 UT (universal time), the developed 3-D model gives average root mean square error (RMSE) values of 0.83 MHz, 1.06 MHz and 1.16 MHz compared to the IRI 2016 values of 0.92 MHz, 1.09 MHz and 1.01 MHz over the Africa-European, American and Asian sectors respectively making their performances statistically comparable. Compared to ionosonde data, the IRI 2016 model consistently shows a better performance for the hmF2 modelling results in almost all sectors during the investigated periods.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10509 - Meteorology and atmospheric sciences
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Atmospheric and Solar-Terrestrial Physics
ISSN
1364-6826
e-ISSN
1879-1824
Volume of the periodical
221
Issue of the periodical within the volume
15 Sept
Country of publishing house
GB - UNITED KINGDOM
Number of pages
13
Pages from-to
105702
UT code for WoS article
000672855100003
EID of the result in the Scopus database
2-s2.0-85108300827