A Global Empirical Model of the Ion Temperature in the Ionosphere for the International Reference Ionosphere

This study presents a suggestion for improvement of the ion temperature (Ti) model in the International Reference Ionosphere (IRI). We have re-examined ion temperature data (primarily available from NASA’s Space Physics Data Facility (SPDF)from older satellites and combined them with newly available data from the Defense Meteorological Satellite Program (DMSP), the Communication Navigation Outage Forecasting System (C/NOFS), and from the recently launched Ionospheric Connection Explorer (ICON). We have compiled these data into a unified database comprising in total Ti data from 18 satellites. By comparisons with long term records of ion temperature from the three incoherent scatter radars (ISRs) (Jicamarca, Arecibo, and Millstone Hill), it was found that an intercalibration is needed to achieve consistency with the ISR data and among individual satellite data sets. This database with thus corrected data has been used for the development of a new global empirical model of Ti with inclusion of solar activity variation. This solar activity dependence is represented by an additive correction term to the Ti global pattern. Due to the limited data coverage at altitudes above 1000 km, the altitude range described by the model ranges from 350 km to 850 km covering only the region where generally Ti is higher than the neutral temperature (Tn) and lower than the electron temperature (Te). This approach is consistent with the current description of Ti in the IRI model. However, instead of one anchor point at 430 km altitude as in the current IRI, our approach includes anchor points at 350, 430, 600, and 850 km. At altitudes above 850 km Ti is merged using a gradient derived from the model at 600 and 850 km, with the electron temperature described by the IRI-2016/TBT-2012 option. Comparisons with the ISR data (Jicamarca, Arecibo, Millstone Hill, and Kharkiv) for high and low solar activity and equinox show that the proposed Ti model captures local time variation of Ti at different altitudes and latitudes better than the current IRI-2016 Ti model.