Assessment of the impact of FORMOSAT‐7/COSMIC‐2 GNSS RO observations on midlatitude and low‐latitude ionosphere specification : observing system simulation experiments using ensemble square root filter

The Formosa Satellite‐7/Constellation Observing System for Meteorology, Ionosphere, and Climate‐2 (FORMOSAT‐7/COSMIC‐2) Global Navigation Satellite System radio occultation (RO) payload can provide global observations of slant total electron content (sTEC) with an unprecedentedly high spatial temporal resolution. Recently, a new ionospheric data assimilation system, the Community Gridpoint Statistical Interpolation (GSI) Ionosphere, is constructed with the National Oceanic and Atmospheric Administration GSI Ensemble Square Root Filter and the Global Ionosphere Plasmasphere and the Thermosphere Ionosphere Electrodynamic General Circulation Model. The paper demonstrates the capability of the GSI Ionosphere to improve the ionospheric specification and make a quantitative assessment of the impact of FORMOSAT‐7/COSMIC‐2 RO data on the ionospheric observing system simulation experiments conducted to calibrate key Ensemble Square Root Filter parameters that control detrimental effects of the sampling errors, particularly on the ensemble‐based estimation of the correlation between observations and model states, in order to yield high‐quality assimilation analysis. Results from the observing system simulation experiments show that (1) an ensemble size larger than 70 is recommended for assimilation of RO sTEC data with the GSI Ionosphere and (2) localizing the impact of observations around the tangent points in the horizontal direction with a length scale of 5,000 km is effective in improving assimilation analysis quality. Assimilation of sTEC data from FORMOSAT‐7/COSMIC‐2 can considerably improve the global ionospheric specification through the application of the GSI Ionosphere. The GSI Ionosphere can provide instantaneous global pictures of the ionosphere variability and help characterize day‐to‐day variability of the ionosphere and deepen our understanding of the observed day‐to‐day variability.Published versio