Modern short-wave communication is widely used in various fields of production and life. For example, global navigation satellite systems (GNSS), through short wave positioning and communication, are widely used in the world, especially in the military. Its mobility, survivability and long-distance communication capability have not only become one of the important means of international communication and global communication, but also attracted more and more attention in the field of short-range communications, such as emergency and counter-terrorism, in recent years. The height of the peak electron density (hmF2) and the critical frequency of the F2 layer (foF2) are very important for short wave communication, especially for short wave NVIS (near vertical incident sky-wave) communication. Their changes will directly affect the selection and design of parameters such as the radio wave radiation elevation and the working frequency band in short wave communication lines, and then affect the distance and efficiency of communication.
In recent years, researchers have made several efforts to improve the modelling and forecasting capability of the foF2 and hmF2 parameters, and other relevant ionospheric parameters. For most radio propagation applications, the values of hmF2 and foF2 are of great importance [
1]. So far, the International Reference Ionosphere (IRI) [
2,
3] is the most widely used by the ionospheric community as the standard model of the ionosphere. The IRI model is calculated by using ground multi-source observations and spaceborne satellite observations [
4,
5]. The IRI model can be optimized by GNSS-TEC to establish a virtual ionosonde. Thus, hmF2 and foF2 can be effectively estimated anywhere and anytime to meet the communication requirements of high-frequency signals [
6]. With the enrichment of GNSS observations and the optimization of algorithms, the IRI model has been improved continuously, and substantive progress has been made.
What is more, relevant scholars at home and abroad have carried out a series of fruitful research work using the IRI model and achieved a series of scientific research results. With the diversification of observations and the continuous optimization of algorithms, the IRI model is also improving. In order to better predict foF2 and hmF2 accurately, some scholars have studied foF2/hmF2 modeling and accuracy evaluation using multi-source data [
7,
8,
9,
10,
11,
12,
13], meanwhile, relevant scholars have studied the adaptability analysis of IRI hmF2/foF2 under different geomagnetic activities in different research areas. Some scholars have studied the adaptability of IRI model in different latitudes with ionosonde data [
14,
15,
16,
17,
18,
19,
20]. Some scholars have also studied the adaptability analysis of F2 parameters and improved methods of IRI model during different geomagnetic storms [
21,
22,
23,
24,
25]. There have also been studies of the F2 parameters’ adaptability of different IRI models in high and low solar activity years [
26,
27,
28,
29,
30,
31]. Research has also focused on the foF2 applicability analysis of the IRI model over China [
32,
33,
34]. Compared to the earlier versions of IRI (e.g., IRI-2007 [
3] and IRI-2012 [
8]), the latest version of international reference ionosphere (IRI-2016) [
1] has been greatly improved. Until now, on the one hand, IRI-2016 contains three options for hmF2, which are Bilitza–Sheikh–Eyfrig (BSE-1979) [
9], Altadill–Magdaleno–Torta-Blanch (AMTB-2013) [
7] and Shubin (SHU-2015) [
13]. On the other hand, IRI-2016 offers two modes for foF2, which are the International Radio Consulting Committee (CCIR) [
35] and the International Union of Radio Science (URSI) [
19], both of which have the “F-peak storm model” ‘on’ or ‘off’ options. The BSE-1979 model was proposed by Bilitza et al. in 1979 [
9]. The model depends not only on the correlation between M(3000)F2 and hmF2, but also on the number of sunspots (R12) in 12 months. The AMTB-2013 model was calculated based on the 26 ionosonde observations during geomagnetic calm period from years 1998 to 2006 [
7]. Finally, the SHU-2015 model is obtained from the ionospheric radio occultation data of CHAMP (Challenging Minisatellite Payload) (years 2001 to 2008), GRACE (Gravity Recovery and Climate Experiment) (years 2007 to 2011) and COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) (years 2006 to 2012) and the 62 ionosonde observations in the world from the years 1987 to 2012 [
13]. The main advantage of the new IRI model is that it can directly predict hmF2 instead of using its relationship with M(3000)F2 [
1]. These options provide an opportunity for the users to evaluate hmF2 and foF2 model values and compare them with other data sets in order to provide valuable feedback on uncertainty and differences from real hmF2 and foF2 values. This is necessary for improving model accuracy and measurement technology [
1]. Given the importance of foF2 and hmF2 parameters, mastering the IRI-2016 daily variations for foF2 and hmF2 is of great significance to effectively realize short wave communication (e.g., BeiDou Navigation Satellite System, (BDS)) under various conditions over China.
This paper determines which option performs best under low and high solar activity years, by evaluating the different IRI-2016 hmF2 and foF2 model options with ionosonde data in low, middle and high latitudes over China. In order to accomplish this task, we considered the ionosonde stations of Sanya (Geog.18.34°N, 109.42°E and Geom.8.87°N, 177.99°W), Beijing (Geog.40.30°N, 116.20°E and Geom.30.85°N, 172.10°W) and Mohe (Geog.52.00°N, 122.52°E and 42.73°N, 167.26°W) over China, as shown in
Figure 1. This paper is organized as follows:
Section 2 shows the materials and methods used, and
Section 3 evaluates IRI-2016 model performance of foF2 and hmF2 data by root mean square (RMS) values and mean absolute relative error (MARE). Finally,
Section 4 and
Section 5 give the discussion and conclusion.