# Evaluation of GNSS-TEC Data-Driven IRI-2016 Model for Electron Density
## 1 Introduction  
The ionosphere is the Earth's upper atmosphere, which extends from about 60 km above the ground to an altitude of about 2000 km, and contains a large number of free electrons and ions, which have a significant impact on radio systems, such as satellite navigation, communications, and radar detection [1; 2; 3]. Therefore, it is particularly important to obtain accurate information about the ionosphere [4; 5]. The international reference ionosphere (IRI) is an empirical ionospheric model jointly developed by the committee on space research (COSPAR) and the international union of radio science (URSI) using global multi-source ionospheric observation data. Given the time and location, the IRI model can describe the ionosphere-related information, including total electron content (TEC), ionospheric electron density (IED), F2-layer peak electron density (NmF2), F2-layer peak electron density height (hmF2), and other ionospheric parameters, which are used to characterize the variations of the ionospheric state [6]. Due to the small amount of observational data in China used in the establishment of the IRI model, many scholars have evaluated and studied the applicability of the IRI model within the China region [7; 8; 9; 10; 11; 12; 13; 14; 15]. The IRI-2016 model is better able to predict the trend ofthe F2-layer critical frequency (foF2) with solar activity in the China region, but there is still a certain bias in predicting the fine structure of ionospheric anomalies [10; 16]. With the continuous enrichment of ionospheric observations, IRI modeling has begun to shift from providing ionospheric climatological information to improving the accuracy of the model calculations and real-time weather descriptions. Based on this, many researchers are committed to improving the prediction accuracy of IRI models in order to enhance their application in scientific research and engineering practice. In particular, it is one of the more effective methods to improve the accuracy of the IRI models by adjusting the IRI driving parameters (IG12 index and RZ12 index) with high-precision GNSS-TEC data [17; 18; 19; 20; 21]. The driving parameters used within the standard IRI models are adjusted with the aim of minimizing the error differences between the IRI-TEC and GNSS-TEC. The IG index is the Ionosonde Global monthly index based on nontime foF2 ionosonde measurements recorded at four reference stations: two from the Southern Hemisphere (Port Stanley/UK and Canberra/Canada) and two from the Northern Hemisphere (Kokubunji/Japan and Chilton/UK). The index takes into account both solar activity and ionospheric information, which can better reflect the variation of the ionosphere. And the IG12 is the 12 month running-mean of the ionospheric IG index [6; 22; 23]. Combined with GPS-TEC, [PERSON] et al. [24] verified the improved performance of the IRI model in the Nigerian region. [PERSON] et al. [25] characterized foF2 before and after the improvement. [PERSON] et al. [26] used GNSS-TEC to update the IG12 values, interpolated the IG12 values in response to the large differences in the updated IG12 values at different locations and times, and compared and analyzed different temporal and spatial interpolation schemes, ultimately determining the optimal scheme. That is, the temporal resolution was one hour, using linear interpolation to obtain the updated IG12 index for each time, and the spatial resolution was \(5^{\circ}\times 2.5^{\circ}\) (longitude \(\times\) latitude), using bilinear interpolation to obtain the updated IG12 index for each position. The use of the updated IG12 values to drive IRI-2016 results in a great improvement in the accuracy of TEC calculated by IRI-2016. Meanwhile, the daily grid map of IG-up values and equivalent IG12 values in the mainland China region are also provided to ensure that the improved IRI-2016 model can be used to get the corresponding TEC in regions where there are no other more effective means (e.g., GNSS and ionosonde) to obtain high-precision ionospheric information.