IONONEST—A Bayesian approach to modeling the lower ionosphere. Issue 8 (11th August 2016)

• Record Type: Journal Article
• Authors: Martin, Poppy L.; Scaife, Anna M. M.; McKay, Derek; McCrea, Ian
• Is Part Of: Radio science. Volume 51:Issue 8(2016:Aug.)
• Page Start: 1332
• Page End: 1349
• Publication Date: 2016-08-11
• Subjects: ionospheric modeling -- nested sampling -- riometry; Radio meteorology -- Periodicals; Radio wave propagation -- Periodicals; 621.38405
• DOI: 10.1002/2016RS005965
• Languages: English
• ISSNs: 0048-6604

Abstract

Abstract: Obtaining high‐resolution electron density height profiles for the D region of the ionosphere as a well‐sampled function of time is difficult for most methods of ionospheric measurement. Here we present a new method of using multifrequency riometry data for producing D region height profiles via inverse methods. To obtain these profiles, we use the nested sampling technique, implemented through our code, IONONEST. We demonstrate this approach using new data from the Kilpisjärvi Atmospheric Imaging Receiver Array (KAIRA) instrument and consider two electron density models. We compare the recovered height profiles from the KAIRA data with those from incoherent scatter radar using data from the European Incoherent Scatter Facility (EISCAT) instrument and find that there is good agreement between the two techniques, allowing for instrumental differences. Key Points: We present IONONEST, a Bayesian method for producing D region electron density height profiles from multifrequency absorption measurements This method can quantitatively distinguish between electron density height profile models We validate the method through comparison with EISCAT VHF data