A Comprehensive Assessment of Radio Occultation Ionospheric Measurements at Mid-Latitudes

Friday, 18 December 2015
Poster Hall (Moscone South)
Chris Keele1, Christiano G.M. Brum2, Fabiano S Rodrigues1, Nestor Aponte2 and Michael P Sulzer2, (1)University of Texas at Dallas, Richardson, TX, United States, (2)Arecibo Observatory, Arecibo, PR, United States
The GPS radio occultation (RO) has become a widely used technique for global measurements of the ionospheric electron density (Ne). To advance our understanding of the accuracy of the RO profiles at mid latitudes, we performed a comprehensive comparison of RO measurements made by the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites and observations of Ne profiles made by the Arecibo Observatory incoherent scatter radar (ISR).

COSMIC is formed by six satellites in circular, 800 km altitude low-Earth orbit (LEO) at 72° inclination. The satellites orbit in their own plane, approximately 24° apart in ascending node. The satellites are equipped with dual-frequency GPS receivers capable of making measurements of the total electron content (TEC) along the signal path and, therefore, RO observations.

The Arecibo ISR, located at(18.35°N, 66.75°W; ∼28.25°N dip latitude), operates at a frequency of 430 MHz with a maximum bandwidth of about 1 MHz. The large collecting area provided by the 300 m dish antenna combined with high peak power transmitters (2.0–2.5 MW) allows the radar to make accurate Ne measurements throughout the entire ionospheric F-region and topside heights.

We analyzed 74 and 89 days of line feed and Gregorian data, respectively, collected between 2006 and 2014. There were 638 RO profiles measured within 10° of latitude and 20° of longitude from Arecibo Observatory and within ±10 minutes of the radar measurements.

Preliminary analyses of the observations show patterns in the relationship between densities measured by the Arecibo ISR and densities estimated from the COSMIC ROs. We will present and discuss the behavior of the patterns. We will also present results of a numerical model representing the patterns and discuss the possibility of using this model to improve RO estimates of density profiles.