A Case Study of the 3D Water Vapor Tomography Model Based on a Fast Voxel Traversal Algorithm for Ray Tracing

A fast voxel traversal algorithm for ray tracing was applied to build a 4 × 4 × 20 tomography model using the observation data of 11 ground-based Global Navigation Satellite System (GNSS) meteorology (GNSS/MET) stations in Hebei Province, China. The precipitation water vapor (PWV) observed at 05 a.m...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2021-06, Vol.13 (12), p.2422
Main Authors: Hu, Heng, Liu, Min, Zhong, Jiqin, Deng, Xin, Cao, Yunchang, Fang, Peng
Format: Article
Language:English
Subjects:
3D water vapor tomography
Accuracy
Algorithms
Deviation
Efficiency
Floors
Forecasting
GFS
Global navigation satellite system
Global positioning systems
GNSS/MET
GPS
Horizontal distribution
Humidity
Mathematical models
Meteorology
Navigation systems
Precipitation
Ray tracing
the fast voxel traversal algorithm
Tomography
Universal time
Vapor density
Vertical distribution
Water vapor
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Summary:A fast voxel traversal algorithm for ray tracing was applied to build a 4 × 4 × 20 tomography model using the observation data of 11 ground-based Global Navigation Satellite System (GNSS) meteorology (GNSS/MET) stations in Hebei Province, China. The precipitation water vapor (PWV) observed at 05 a.m. (Universal Time Coordinated: UTC) on 10 December 2019, was used to reconstruct three-dimensional (3D) water vapor density fields over the test area. The tomographic results (GNSS_T) show that the water vapor density above this area is mainly below 25 g/m3 and is concentrated between the first to the fourth layers. The vertical distribution conforms to the exponential characteristics, while the horizontal distribution shows a decreasing trend from southwest to northeast. In addition, the results of the 0.25° grid dataset generated by the Global Forecast System (GFS) of the National Center for Environmental Forecasting (NCEP) (GFS_L) were interpolated to the height of the tomographic grid, which is in good agreement with the tomographic results. GFS_L is larger than GNSS_T on the first floor at the surface, with an average deviation of 0.19 g/m3. In contrast, GFS_L from the second floor to the top of the model is smaller than GNSS_T, with the average deviations distributed between −0.08 and −0.15 g/m3.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs13122422