27 May 2024
 | 27 May 2024
Status: this preprint is currently under review for the journal AMT.

Observing atmospheric rivers using GNSS radio occultation data

Bahareh Rahimi and Ulrich Foelsche

Abstract. Atmospheric Rivers (AR) are comparatively narrow regions in the atmosphere that are responsible for most of the horizontal transport of water vapor in the extra tropics, which are responsible for many extreme precipitation events and floodings at mid-latitudes, including Europe and the US. The critical role of ARs in global moisture transport and precipitation dynamics necessitates accurate water vapor measurements for both understanding and forecasting these phenomena. While the integrated water vapor content (IWV) of ARs can be well measured with microwave and infrared sounders, the vertical structure is less well known. In this study, we analysed if specific humidity profiles and IWV values from Global Navigation Satellite System Radio Occultation (GNSS-RO) measurements provide additional information for the study of ARs, in particular regarding their vertical structure. The retrieval of water vapor from GNSS-RO data requires background information, which is usually incorporated by the one-dimensional variational method (1D-Var) that combine observations and background in an optimal manner. We compared data from the COSMIC Data Analysis and Archive Centre (CDAAC), operated by the University Corporation for Atmospheric Research (UCAR) in Boulder, Colorado with data from the Wegener Center for Climate and Global Change (WEGC) at the University of Graz, Austria. We found that retrievals from both centres agree very well in the altitude range, where the 1D-Var weights the observations strongly, even if the employed background profiles are very different. This demonstrates that GNSS-RO data provide indeed additional vertically-resolved information, which was not already contained in the background or in operational analyses. IWV values from CDAAC and WEGC agree generally very well, however, both tend to underestimate the values obtained by Special Sensor Microwave Imager/Sounder (SSMI/S) data, since GNSS-RO profiles not always reach the lowermost part of the atmosphere, leading to a systematic bias in the IWV data, which decreases with better penetration characteristics of the GNSS-RO data. The results suggest that is promising to combine the GNSS-RO data – with very high vertical resolution with SSMI/S data – with high horizontal resolution to get a more compete view of the 3D structure of ARs.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Bahareh Rahimi and Ulrich Foelsche

Status: open (until 28 Jul 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2024-81', Anonymous Referee #1, 21 Jun 2024 reply
Bahareh Rahimi and Ulrich Foelsche
Bahareh Rahimi and Ulrich Foelsche


Total article views: 169 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
119 43 7 169 5 6
  • HTML: 119
  • PDF: 43
  • XML: 7
  • Total: 169
  • BibTeX: 5
  • EndNote: 6
Views and downloads (calculated since 27 May 2024)
Cumulative views and downloads (calculated since 27 May 2024)

Viewed (geographical distribution)

Total article views: 167 (including HTML, PDF, and XML) Thereof 167 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 24 Jun 2024
Short summary
This study explores the use of GNSS-RO data to improve understanding of the vertical structure of humidity in Atmospheric Rivers (ARs). Specific humidity profiles and IWV values from GNSS-RO are evaluated to assess if this method offers additional insights into ARs' vertical characteristics. The results suggest that combining GNSS-RO data, with its high vertical resolution, with SSMI/S data, known for high horizontal resolution, provides a more complete view of the 3D structure of ARs.