The International Reference Ionosphere (IRI) model is a widely used empirical model to describe ionospheric climatology. However, IRI represents the monthly averages of the ionospheric parameters, which makes it difficult to capture the local and short-term ionospheric variations. To overcome this limitation, we propose a data ingestion method using a combination of ground-based and space-borne observations. The ionospheric parameters from ground-based Global Navigation Satellite System (GNSS), ionosondes, space-borne GNSS radio occultation and satellite altimetry observations are ingested into the IRI-2020 model to improve its accuracy. The outputs of the ingested IRI (IRI_inge) are assessed by case study and statistical analysis, with reference to independent ionosonde observations and global ionospheric maps. The case study shows that IRI_inge expresses the diurnal and local variations of the ionosphere better than the standard IRI (IRI_stan) in both high and low solar activity periods. The relative error of ionospheric electron density profiles from IRI_inge is generally less than 10%, and the vertical total electron content from IRI_inge has an accuracy improvement of 39.0% compared to that from IRI_stan. The statistical analysis shows that IRI_inge performs more stable than IRI_stan, and its output generally has smaller REs and root-mean-square errors, especially in daytime and storm time. The proposed method significantly improves IRI-2020 on the accuracy of the output parameters and the ability to present the short-term variations of the ionosphere.

国际参考电离层 (IRI) 模型是广泛使用的描述电离层气候学的经验模型。然而，IRI代表电离层参数的月平均值，这使得难以捕捉局部和短期的电离层变化。为了克服这一限制，我们提出了一种结合地面和星载观测的数据摄取方法。IRI-2020 模型将来自地面全球导航卫星系统 (GNSS)、电离探空仪、星载 GNSS 无线电掩星和卫星测高观测的电离层参数纳入 IRI-2020 模型中，以提高其准确性。摄入 IRI (IRI _inge ) 的输出通过案例研究和统计分析进行评估，并参考独立的电离探空仪观测结果和全球电离层地图。案例研究表明，在太阳活动高峰期和低谷期， IRI _{inge都比标准 IRI (IRI stan} )更好地表达了电离层的昼夜和局部变化。_{IRI inge}电离层电子密度剖面相对误差一般小于10%，IRI _inge垂直总电子含量精度较IRI _stan提高39.0% 。统计分析表明，IRI _{inge比IRI stan}表现更稳定，其输出普遍具有较小的RE和均方根误差，特别是在白天和暴风雨时段。该方法显着提高了IRI-2020输出参数的准确性以及呈现电离层短期变化的能力。