Least-Squares Spectral and Coherency Analysis of the Zenith Total Delay Time Series at SuomiNet Station SA56 (UNB2)

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Abstract

Zenith Total Delay (ZTD) from ground-based Global Navigational Satellite Systems (GNSS) observations plays an important role in meteorology. It contains information about the troposphere due to the interactions that GNSS signals have with the atmosphere while traveling from satellites to ground receivers. Since almost all weather is formed in the troposphere, the analysis of a collection of ZTD time series would provide insight about the periodic characteristics of the weather of a place. It would also provide insight about the influences that meteorological parameters such as pressure, temperature and relative humidity have on the weather’s periodic nature. In this study, the least-squares spectral analysis approach is employed to determine the periodic oscillations in a 7-year time series of ZTD obtained from collocated GNSS and meteorological stations at the University of New Brunswick, Fredericton. Least-Squares Coherency Analysis of the time series spectra of the ZTD and its component hydrostatic and wet delays, and pressure, temperature and relative humidity is also performed. This is done to evaluate the level of contributions those parameters have in the periodicities inherent in the ZTD time series. Except for the zenith hydrostatic delay and pressure which show no annual periodic oscillation, the spectra of all the other time series show strong annual and semi-annual oscillations. Being the most dominant oscillation in the ZTD time series, the annual oscillation is largely driven by temperature, and this is maybe due to the high temperature variation characteristic of the climatic zone Fredericton falls under.

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APA

Mayaki, A. O., Santos, M., & Nikolaidou, T. (2023). Least-Squares Spectral and Coherency Analysis of the Zenith Total Delay Time Series at SuomiNet Station SA56 (UNB2). In International Association of Geodesy Symposia (Vol. 152, pp. 269–278). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/1345_2020_110

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