.png){kind=icon}
.png){kind=icon}
Return
A segment-based approach for global vertical adjustment of precipitable water vapor
.png){kind=icon}
PRE
AI
M
S
L
Y
X
X
W
L
DOI：10.1016/j.asr.2026.02.046.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The Precipitable Water Vapor (PWV) vertical adjustment model can correct PWV errors between datasets caused by height differences, thereby integrating PWV from various sources. However, previous global adjustment models have ignored regional variations in PWV and differences in height, resulting in decreased performance in different topography and climate regions. A global segmented PWV vertical adjustment model (GS-PWV) has been developed based on ERA5 (the fifth generation of European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis) data to address this issue. The GS-PWV model is evaluated using multi-source PWV data, with the high-precision global PWV vertical adjustment model (GPWV-H) serving as the reference. Using ERA5 and radiosonde PWV profiles as reference datasets, the GS-PWV model has a Bias of-0.07 mm/-0.11 mm and an RMSE of 1.00 mm/1.02 mm, respectively. The RMSE is improved by 9.09% and 25.00%, respectively, compared to the GPWV-H model. The ERA5 PWV at different resolutions is interpolated to GNSS stations using two vertical adjustment models. The findings show that the RMSE of the GS-PWV model improves that of the GPWV-H model by 2.44-3.57%. These results show that the GS-PWV model has stable accuracy and provides an important reference for atmospheric research and the fusion of multi-source PWV. (c) 2026 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Keywords:
Segmentation function
PWV lapse rate
Global Navigation Satellite Systems (GNSS)
Vertical adjustment
Journal
IF:
2.8
Papers:
1.3K
Citations:
2.0W
Organization
Cited Papers