A comparison of the LPIM-COSMIC F2 peak parameters determinations against the IRI(CCIR). Issue 8 (15th April 2015)

• Record Type: Journal Article
• Authors: Azpilicueta, F.; Altadill, D.; Brunini, C.; Torta, J.M.; Blanch, E.
• Is Part Of: Advances in space research. Volume 55:Issue 8(2015)
• Page Start: 2012
• Page End: 2019
• Publication Date: 2015-04-15
• Subjects: Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2014.08.008
• Languages: English
• ISSNs: 0273-1177

Abstract

<abstract xml:lang="en" abstract-type="author" id="ab005"> <title id="st045">Abstract</title> <sec> <p id="sp0005">During the last decade the amount of ionosphere measurements, from ground and space born sources, has substantially increased along with the development of high end processing systems. This constitutes a perfect scenario for the International Reference Ionosphere (IRI) to assimilate this huge new database and to satisfy the new needs of the aeronomic community: an IRI with meteorological capability.</p> <p id="sp0010">The first step before the implementation of an assimilative procedure is to validate the new data. This work intends to contribute in this direction by studying the differences (systematic and statistical) between the F2 peak parameters (hmF2 and NmF2) predicted by the IRI(CCIR) and those obtained from the electron density profiles computed with LPIM-COSMIC/Formosat3 (LPIM-C/F3) technique. The analyzed period extends from January 2007 to October 2012, thus covering all the different seasonal Sun–Earth configurations and a range of solar activity going from low to mid-high level.</p> <p id="sp0015">The analysis shows that there is no significant systematic bias between the IRI and LPIM-C/F3 values on both parameters. The obtained differences are comparable to those found between IRI and other models and data sources. In addition a correlation with the solar activity level is observed. The analysis performed is also helpful to study and asses the potentiality of the meteorological information contained in the LPIM-C/F3 by analyzing the standard deviation of the differences. This extra information could represent the key element to improve the IRI predicting capabilities.</p> </sec> </abstract>