Development and Assessment of the Atmospheric Pressure Vertical Correction Model With ERA‐Interim and Radiosonde Data. Issue 11 (16th November 2018) - Yao, Yibin; Sun, Zhangyu; Xu, Chaoqian; Zhang, Liang; Wan, Yangyang
Abstract: Atmospheric pressure is a critical parameter in Global Navigation Satellite System (GNSS) technology to calculate zenith hydrostatic delay (ZHD). Because the reference pressure is usually not at the height of the GNSS receiving antenna, a vertical correction of the pressure value is inevitable. This paper used the ERA‐Interim data to develop a grid model for such correction by introducing a new parameter. Then, the ERA‐Interim and radiosonde data were employed for assessing the newly built model along with other two types of state‐of‐art vertical correction methods (which are named as the virtual temperature ( T v )‐based model and the temperature ( T 0 )‐based model in this paper). Furthermore, the assessments were conducted in two cases where the measured meteorological data are available and unavailable. Results show that the T v ‐based model and the T 0 ‐based model may have limitations in some ice‐covered regions (e.g. the Antarctica, the Qinghai‐Tibetan Plateau and the Greenland), but the grid model built in this paper does not show the weaknesses. For the results of the four different assessments devised in this paper (assessed with the ERA‐Interim or radiosonde data, with or without the measured meteorological data), the grid model always shows the highest precision among these three models, and the T 0 ‐based model has higher accuracy than the T v ‐based model. Additionally, this paper found that when the height differences of the correction are large, the T v ‐based model may have large uncertainties while the grid model is still applicable. Key Points: A new global grid model for vertical correction of atmospheric pressure is developed The performances of three different types of the pressure vertical correction models are assessed with ERA‐Interim and radiosonde data The performances are assessed in two cases where measured meteorological data are available and unavailable