EGU23-2992
https://doi.org/10.5194/egusphere-egu23-2992
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multi-source water vapor tomography based on ray-tracing technique

Ming Shangguan, Meng Dang, and Xu Cheng
Ming Shangguan et al.
  • School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China (shanggm@cug.edu.cn)

GNSS water vapor tomography has proven to be a near-real-time cost-effective method to obtain the three-dimensional distribution of atmospheric water vapor. Many previous studies have used various methods to derive the GNSS water vapor tomography. However, the number and distribution of GNSS signals limit the accuracy and spatial resolution of GNSS water vapor tomography, which could cause an ill-posed inverse problem. This study tries to use multi-source observations (GNSS, MODIS and ERA5) in Hongkong with the help of the ray-tracing technique to increase the number of signals and voxels crossed by rays for the water vapor reconstruction. Water vapor tomography are derived based on multi-source data and validated with the radiosonde data. Experimental results demonstrate that the proposed method is helpful to improve the quality of water vapor tomography.

How to cite: Shangguan, M., Dang, M., and Cheng, X.: Multi-source water vapor tomography based on ray-tracing technique, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2992, https://doi.org/10.5194/egusphere-egu23-2992, 2023.