Inferring the Ionospheric State With the Far Ultraviolet Imager on the Fengyun-4C Geostationary Satellite: Retrieval Algorithm and Verification

The Multiband Ultraviolet Spectrum Imager (MUSI) is an optical remote sensing instrument scheduled to launch on the Fengyun-4C meteorological satellite in 2024. MUSI is designed to measure the airglow emissions between similar to 120 and 160 nm above the East Asia and Pacific region from a geostationary orbit to infer ionospheric parameters. Here we develop a lookup-table algorithm for retrieving the peak electron density (nmF2) and the Total Electron Content (TEC) from nighttime observations of the OI 135.6 nm emission. The algorithm takes into account the north-south asymmetry of the equatorial ionization anomaly and the atmospheric variations with solar activity and local time. Analysis of synthetic observations shows that the assumptions made in the algorithm only lead to similar to 2%-4% uncertainties in the retrievals under the modeled ionospheric conditions. The algorithm is verified by retrieving nmF2 and TEC from the Global-Scale Observations of the Limb and Disk (GOLD) mission and comparing with coincided radio measurements. The comparison indicates almost negligible systematic differences (typically less than similar to 3%) between the GOLD and the ionosonde nmF2, which are within the error limit of the GOLD retrievals. The accuracy of the GOLD TEC retrievals is shown to be comparable to (or in some sense even better than) that of the measurements from the Global Navigation Satellite System. Several simplified yet robust retrieval methods are also developed, which can be readily implemented for both existing and upcoming missions. Our results promote far ultraviolet (FUV) remote sensing to be a key technology for accurate determination of the ionospheric state. We develop a lookup-table algorithm for ionosphere retrieval with the FUV spectral imager on the Fengyun-4C geostationary satelliteAssumptions made in the algorithm lead to only similar to 2%-4% uncertainties in the nmF2 and Total Electron Content (TEC) retrievals under the modeled ionospheric conditionsThe algorithm is verified by retrieving nmF2 and TEC from the Global-Scale Observations of the Limb and Disk observations and comparing with external radio measurements