The potential of observing atmospheric rivers with Global Navigation Satellite System (GNSS) radio occultation

Rahimi, Bahareh; Foelsche, Ulrich

doi:https://doi.org/10.5194/amt-18-2481-2025

Articles | Volume 18, issue 11

https://doi.org/10.5194/amt-18-2481-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Observing atmosphere and climate with occultation techniques...

https://doi.org/10.5194/amt-18-2481-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 11

Research article

| Highlight paper

|

12 Jun 2025

Research article | Highlight paper |

| 12 Jun 2025

The potential of observing atmospheric rivers with Global Navigation Satellite System (GNSS) radio occultation

Bahareh Rahimi and Ulrich Foelsche

Data sets

COSMIC-1 Data Products UCAR COSMIC Program https://doi.org/10.5065/ZD80-KD74

Remote Sensing Systems DMSP SSMI/S Daily Environmental Suite on 0.25 deg grid, Version 7 F. J. Wentz et al. https://www.remss.com/missions/ssmi

Model code and software

Python Language Reference, version 3.11 Python Software Foundation https://www.python.org/

netCDF4-python D. Pierce https://github.com/Unidata/netcdf4-python

Array programming with NumPy (https://numpy.org/) Charles R. Harris et al. https://doi.org/10.1038/s41586-020-2649-2

Data structures for statistical computing in Python (https://pandas.pydata.org/) Wes McKinney https://doi.org/10.25080/Majora-92bf1922-00a

xarray: ND labeled arrays and datasets in Python (https://docs.xarray.dev/en/stable/) Stephan Hoyer and Joe Hamman https://doi.org/10.5334/jors.148

Matplotlib: A 2D graphics environment (https://matplotlib.org/) John D. Hunter https://doi.org/10.1109/MCSE.2007.55

Executive editor

Atmospheric rivers (ARs) are recognized as significant contributors to extreme precipitation at mid-latitudes and may increase in frequency and intensity due to climate change. This timely study is the first the show the potential value of GNSS radio occultation (GNSS RO) remote sensing to the study of ARs and in particular how the high vertical resolution of GNSS RO provides information that is complementary to other techniques. The combination of GNSS-RO data with mesoscale models, particularly through assimilation, could further improve our understanding of AR dynamics and the processes leading to extreme precipitation and flooding. This is an important direction for future studies.