Results 11 to 20 of about 139 (96)
Capturing Extreme Water Vapor and Instability With High‐Resolution GNSS Monitoring
This study used data from a high‐resolution Global Navigation Satellite System network (< 10 km spacing), including private stations, to analyze water vapor structure during a heavy rainfall event in Japan. The network captured localized extreme precipitable water vapor (> 70 mm) and a moist absolutely unstable layer near the humid core.
Mikiko Fujita
wiley +1 more source
A Novel Robust High‐Precision Ionospheric Delay Modeling for PPP‐RTK Using Crowdsourced Data
Abstract The performance of PPP‐RTK is critically dependent on the quality of ionospheric corrections derived from a reference network. While the proliferation of mass‐market Global Navigation Satellite System (GNSS) devices offers a promising crowdsourcing opportunity to densify or replace this infrastructure, it introduces the formidable challenge of
Bo Wang +6 more
wiley +1 more source
This study focuses on the critical challenge of selecting an overall optimal ISB stochastic model to improve GNSS PPP performance, which establishes a comprehensive assessment framework integrating positioning accuracy, convergence time, ISB characteristics, residual analysis, correlation metrics and physical mechanism interpretation.
Ban Zhao
wiley +1 more source
Atmospheric Water Vapor and Precipitation Coupling in Southwestern South America
Abstract Most studies linking atmospheric water vapor and precipitation emphasize short records, tropical regions, or the Northern Hemisphere. Long‐term variability of water vapor and its coupling with precipitation remain poorly understood across strong latitudinal and climatic gradients.
Raúl Valenzuela +2 more
wiley +1 more source
Determination of Zenith Tropospheric Delay (ZTD) Using CORS GNSS Data, 2016 – 2020 In Lampung
GNSS satellites transmit signals in the form of electromagnetic waves to ground-based observation stations (receivers). As these signals pass through the atmosphere - particularly the troposphere - they undergo delays and bending due to differences in atmospheric properties.
null Een Lujainatul Isnaini +4 more
openaire +1 more source
Abstract Atmospheric water vapor is an important factor in the formation and evolution of extreme weather events, such as heavy rainfall, typhoons, and major droughts and floods. We analyzed the applicability of precipitable water vapor (PWV) values from the Global Navigation Satellite System Meteorology (GNSS/MET) stations in northeastern China.
Yang Liu +5 more
wiley +1 more source
Abstract The Global Navigation Satellite System (GNSS) real‐time Precise Point Positioning (PPP) technology offers a highly efficient approach for atmospheric Precipitable Water Vapor (PWV) monitoring and extreme weather warning. However, its retrieval accuracy is limited by the performance of orbit and clock products, as well as the coupling effects ...
Wenliang Gao +4 more
wiley +1 more source
Optimizing PPP Performance by Incorporating ZWD Constraints Derived From Data Assimilation
Abstract One of the primary error sources limiting the performance of the Precise Point Positioning (PPP) technique is the atmospheric wet delay, caused by the presence of water vapor in the lower atmosphere. Accurately representing this parameter is crucial for improving the initialization and accuracy of satellite‐based positioning techniques ...
Masoud Dehvari +2 more
wiley +1 more source
Abstract Non‐tidal loading (NTL) introduces surface deformation on the Earth and increases the variability in coordinates measured by space geodetic techniques. Correcting NTL displacements in Global Navigation Satellite Systems (GNSS) analysis has been discussed extensively, commonly at the parameter level.
Jungang Wang +6 more
wiley +1 more source
Abstract From repeat‐pass interferometry, tropospheric signals often prevent the detection of ground deformation signals. In recent years, tropospheric corrections derived from global weather‐based models have been implemented in several InSAR processing chains.
F. Albino +7 more
wiley +1 more source

