Articles | Volume 25, issue 23
https://doi.org/10.5194/acp-25-17797-2025
https://doi.org/10.5194/acp-25-17797-2025
Research article
 | 
08 Dec 2025
Research article |  | 08 Dec 2025

Constraining microphysics assumptions on the modeling of Atmospheric Rivers using GNSS Polarimetric Radio Occultations

Antía Paz, Ramon Padullés, and Estel Cardellach

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The PAZ polarimetric radio occultation research dataset for scientific applications
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Cited articles

Bringi, V. N. and Chandrasekar, V.: Polarimetric Doppler weather radar: principles and applications, Cambridge university press, ISBN 9780511541094, 2001. a
Cardellach, E., Tomás, S., Oliveras, S., Padullés, R., Rius, A., de la Torre-Juárez, M., Turk, F. J., Ao, C. O., Kursinski, E. R., Schreiner, B., Ector, D., and Cucurull, L.: Sensitivity of PAZ LEO Polarimetric GNSS Radio-Occultation Experiment to Precipitation Events, IEEE Transactions on Geoscience and Remote Sensing, 53, 190–206, https://doi.org/10.1109/TGRS.2014.2320309, 2015. a
Cardellach, E., Oliveras, S., Rius, A., Tomás, S., Ao, C., Franklin, G. W., Iijima, B. A., Kuang, D., Meehan, T. K., Padullés, R., de la Torre Juárez, M., Turk, F., Hunt, D. C., Schreiner, W. S., Sokolovskiy, S. V., Hove, T. V., Weiss, J. P., Yoon, Y., Zeng, Z., Clapp, J., Xia-Serafino, W., and Cerezo, F.: Sensing Heavy Precipitation With GNSS Polarimetric Radio Occultations, Geophysical Research Letters, https://doi.org/10.1029/2018GL080412, 2019. a, b
Chen, S. H. and Sun, W. Y.: A one-dimensional time dependent cloud model, Journal of the Meteorological Society of Japan, https://doi.org/10.2151/jmsj.80.99, 2002. a, b
Chen, S.-Y., Kuo, Y.-H., Li, H.-W., Padullés, R., Cardellach, E., and Turk, F. J.: Comparisons of polarimetric radio occultation measurements with WRF model simulation for tropical cyclones, Atmos. Meas. Tech., 18, 5265–5280, https://doi.org/10.5194/amt-18-5265-2025, 2025. a
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This study explores how different assumptions in cloud microphysics affect the vertical distribution of hydrometeors during extreme precipitation events, such as atmospheric rivers. Using a combination of high-resolution weather simulations and radiative transfer modeling, we identify snow as the dominant contributor to the observed vertical signal. The analysis highlights the sensitivity of precipitation structure to particle properties, that could help refine atmospheric modeling approaches.
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