Articles | Volume 25, issue 6
https://doi.org/10.5194/acp-25-3567-2025
https://doi.org/10.5194/acp-25-3567-2025
Measurement report
 | 
26 Mar 2025
Measurement report |  | 26 Mar 2025

Measurement report: Can zenith wet delay from GNSS “see” atmospheric turbulence? Insights from case studies across diverse climate zones

Gaël Kermarrec, Xavier Calbet, Zhiguo Deng, and Cintia Carbajal Henken

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Cited articles

Banville, S. and Langley, R. B.: Monitoring the Ionosphere Using Integer-Leveled GLONASS Measurements, in: Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), 4–18 September 2015, Tampa, Florida, pp. 3578–3588, 2015. a
Basu, S. and Holtslag, A.: Revisiting and revising Tatarskii's formulation for the temperature structure parameter (χT) in atmospheric flows, Environ. Fluid Mech., 22, 1107–1119, https://doi.org/10.1007/s10652-022-09880-3, 2022. a
Bevis, M., Businger, S., Herring, T. A., Rocken, C., Anthes, R. A., and Ware, R. H.: GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System, J. Geophys. Res., 97, 15787–15801, 1992. a, b, c, d
Boehm, J., Werl, B., and Schuh, H.: Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data, J. Geophys. Res., 111, https://doi.org/10.1029/2005JB003629, 2006. a
Calbet, X., Peinado-Galan, N., DeSouza-Machado, S., Kursinski, E. R., Oria, P., Ward, D., Otarola, A., Rípodas, P., and Kivi, R.: Can turbulence within the field of view cause significant biases in radiative transfer modeling at the 183 GHz band?, Atmos. Meas. Tech., 11, 6409–6417, https://doi.org/10.5194/amt-11-6409-2018, 2018. a
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Atmospheric delays affect global navigation satellite system (GNSS) signals. This study analyses the wet delay, a variable component caused by atmospheric water vapor, using a novel filtering method to examine small-scale turbulent variations. Case studies at five global stations revealed daily and seasonal turbulence patterns. This research will improve water vapour and cloud models, enhance nowcasting, and refine stochastic modelling for GNSS and very long baseline interferometry.

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