During extreme ionospheric storms, anomalous ionospheric delays and gradients could cause potential integrity threats to users of GNSS (Global Navigation Satellite System) augmentation systems. GNSS augmentation ground facilities must monitor these ionospheric anomalies defined by a threat model and alarm the users of safely-of-life applications within time-to-alerts. Because the ionospheric anomaly threat model is developed using data collected from GNSS reference stations, the use of poor-quality data can degrade the performance of the threat model. As the total number of stations increases, the number of station with poor GNSS data quality also increases. This paper analyzes the quality of data collected from Korean GPS reference stations using comprehensive GNSS data quality check algorithms. The results show that the range of good and poor qualities varies noticeably for each quality parameter. Especially erroneous ionospheric delay and gradients estimates are produced due to poor quality data. The results obtained in this study should be a basis for determining GPS data quality criteria in the development of ionospheric threat models.