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Real‐time retrieval of precipitable water vapor from GPS precise point positioning
Author(s) -
Yuan Yubin,
Zhang Kefei,
Rohm Witold,
Choy Suelynn,
Norman Robert,
Wang ChuanSheng
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2014jd021486
Subject(s) - nowcasting , radiosonde , zenith , global positioning system , depth sounding , precipitable water , meteorology , environmental science , numerical weather prediction , troposphere , satellite , remote sensing , mean squared error , precise point positioning , gnss applications , water vapor , geography , computer science , mathematics , statistics , telecommunications , engineering , cartography , aerospace engineering
Sensing of precipitable water vapor (PWV) using the Global Positioning System (GPS) has been intensively investigated in the past 2 decades. However, it still remains a challenging task at a high temporal resolution and in the real‐time mode. In this study the accuracy of real‐time zenith total delay (ZTD) and PWV using the GPS precise point positioning (PPP) technique is investigated. GPS observations in a 1 month period from 20 globally distributed stations are selected for testing. The derived real‐time ZTDs at most stations agree well with the tropospheric products from the International Global Navigation Satellite Systems Service, and the root‐mean‐square errors (RMSEs) are <13 mm, which meet the threshold value of 15 mm if ZTDs are input to numerical weather prediction models. The RMSE of the retrieved PWVs in comparison with the radiosonde‐derived values are ≤3 mm, which is the threshold RMSE of PWVs as inputs to weather nowcasting. The theoretical accuracy of PWVs is also discussed, and 3 mm quality of PWVs is proved achievable in different temperature and humidity conditions. This implies that the real‐time GPS PPP technique can be complementary to current atmospheric sounding systems, especially for nowcasting of extreme weather due to its real‐time, all‐day, and all‐weather capabilities and high temporal resolutions.