# Characterizing Ionospheric Effects on GNSS Reflectometry at Grazing Angles from Space
###### Abstract  
Coherent observations in GNSS reflectometry are prominent in regions with smooth reflecting surfaces and at grazing elevation angles. However, within these lower elevation ranges, GNSS signals traverse a more extensive atmospheric path, and increased ionospheric effects (e.g., delay biases) are expected. These biases can be mitigated by employing dual-frequency receivers or models tailored for single-frequency receivers. In preparation for the single-frequency GNSS-R ESA \"PRETTY\" mission, this study aims to characterize ionospheric effects under variable parameter conditions: elevation angles in the grazing range (5\({}^{\circ}\) to 30\({}^{\circ}\)), latitude-dependent regions (north, tropic, south) and diurnal changes (day and nighttime). The investigation employs simulations using orbit data from Spire Global Inc.'s Lemur-2 CubeSat constellation at the solar minimum (F10.7 index at 75) on March, 2021. Changes towards higher solar activity are accounted for with an additional scenario (F10.7 index at 180) on March, 2023. The electron density associated with each reflection event is determined using the Neustrelitz Electron Density Model (NEDM2020) and the NeQuick 2 model. The results from periods of low solar activity reveal fluctuations of up to approximately 300 TECUs in slant total electron content, 19 m in relative ionospheric delay for the GPS L1 frequency, 2 Hz in Doppler shifts, and variations in the peak electron density height ranging from 215 to 330 km. Sea surface height uncertainty associated with ionospheric model-based corrections in group delay altimetric inversion can reach a standard deviation at the meter level. GNSS reflectometry; grazing angles; ionospheric delay; ionospheric Doppler shift; NEDM2020 model; NeQuick model; PRETTY mission Article  
Characterizing Ionospheric Effects on GNSS Reflectometry at Grazing Angles from Space  
[PERSON], [PERSON]; [PERSON], [PERSON]. ionospheric studies across diverse spatial and temporal scales. Ground-based atmospheric-sounding techniques employing continuously operating reference station (CORS) networks and GNSS receivers, which operate on low Earth orbit (LEO) satellites for the analysis of refracted radio signals via GNSS radio occultation (GNSS-RO), provide key observations for improving global weather forecasts [3]. To further broaden the observations, GNSS reflectometry (GNSS-R) has emerged as a complementary technique that leverages signals reflected off the Earth's surface. This approach not only facilitates the retrieval of reflecting surface properties but also serves as an atmospheric-sounding tool. In order to understand ionospheric ranging delays within space-borne GNSS-R, simulations are conducted as detailed in [4]. The simulation is based on the Cyclone GNSS (CYGNSS) [5] mission and encompasses different elevation angles, latitudes, and solar activities. The results reveal an inverse relationship between the satellite elevation angle and ionospheric delay, with a larger ionospheric influence at low latitudes. In [6], the impact of scintillation effects on reflectometry has been explored using data from UK TechDemoSat-1 [7]. These effects lead to a degradation of the signal-to-noise ratio that can be utilized for altimetry and scatterometry performance assessments. More recently, studies have been carried out to retrieve the total electron content (TEC) from coherent reflectometry observations. In the work presented in [8], a methodology was introduced for sTEC estimation along the paths of incident and reflected signal rays. This estimation is based on coherent dual-frequency GNSS-R measurements obtained from Spire Global low Earth orbit (LEO) CubeSats. The outcomes have demonstrated a favorable alignment between reflectometry sTEC estimations and the global ionospheric TEC maps (GIM). Furthermore, an algorithm outlined in [9] combines sTEC observation from space-borne reflectometry using CubeSats and data collected from ground-based GNSS stations to generate vertical TEC (vTEC) maps in the Arctic region.