Abstract

The Global Navigation Satellite System (GNSS) plays an important role in retrieving high temporal–spatial resolution precipitable water vapor (PWV) and its applications. The weighted mean temperature (Tm) is a key parameter for the GNSS PWV estimation, which acts as the conversion factor from the zenith wet delay (ZWD) to the PWV. The Tm is determined by the air pressure and water vapor pressure, while it is not available nearby most GNSS stations. The empirical formular is often applied for the GNSS station surface temperature (Ts) but has a lower accuracy. In this paper, the temporal and spatial distribution characteristics of the coefficients of the linear Tm-Ts model are analyzed, and then a piecewise-linear Tm-Ts relationship is established for each GPS station using radiosonde data collected from 2011 to 2019. The Tm accuracy was increased by more than 10% and 20% for 86 and 52 radiosonde stations, respectively. The PWV time series at 377 GNSS stations from the infrastructure construction of national geodetic datum modernization and Crustal Movement Observation Network of China (CMONC) were further obtained from the GPS observations and meteorological data from 2011 to 2019. The PWV accuracy was improved when compared with the Bevis model. Furthermore, the daily and monthly average values, long-term trend, and its change characteristics of the PWV were analyzed using the high-precision inversion model. The results showed that the averaged PWV was higher in Central-Eastern China and Southern China and lower in Northwest China, Northeast China, and North China. The PWV is increasing in most parts of China, while the some PWVs in North China show a downward trend.

Highlights

  • Introduction iationsWater vapor is an important part of the Earth’s hydrosphere and plays a key role in the energy exchange and water cycle in nature

  • One of the indicators to measure the amount of atmospheric water vapor is the precipitable water vapor (PWV), which represents a certain height of the water column produced by the condensation of all tropospheric atmospheric water vapor in the column per unit bottom area at any time into liquid water

  • We estimated the monthly coefficients at each station, and and some PWV in North China is downward from 2011 to 2019

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Summary

Observation Data

The infrastructure construction of national geodetic datum modernization in China was launched in 2012 and completed in 2017, which contained 210 GPS stations. A highprecision, dynamic, and unified modern surveying and mapping datum system was established to provide coordinate frame services, including data products, real-time positioning, processing and analysis, and other services [28]. Network of China (CMONC) was established in 2006 and completed in 2012, which contained 360 GPS stations [29,30]. The National Geomatics Center of China (NGCC) provided the hourly ZTD data and 1-h measured temperature and atmospheric pressure data at these GPS stations from 2011 to 2019. Hasthe released and pilot balloon with more than 2700 stations around worldradiosonde since 1905, including balloon observations with more than stations around the world since. 1905, including air pressure, temperature, geopotential height, and relative humidity air pressure, temperature, geopotential height, and humidity

24 January
Distribution
Establishment
PWV from Site-Specific Piecewise-Linear Tm -Ts Relationship
PWV from Radiosonde
Fitting
Spatial Distribution and Characteristics of the m-T
Comparison with Bevis m-Ts Relationship
Comparison with GPS-Derived PWV and Radiosonde PWV
Spatial Distribution of PWV in China
Seasonal Variations of PWV in China
Long-Term Variation Trend of PWV in China
Discussion
Conclusions
Full Text
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