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Global Navigation Satellite System (GNSS) Airborne Radio Occultation (ARO) Observations from the Atmospheric River Reconnaissance Field Campaigns

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Global Navigation Satellite System (GNSS) Airborne Radio Occultation (ARO) Observations from the Atmospheric River Reconnaissance Field Campaigns

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Extent

6 digital objects.

Cite This Work

Haase, Jennifer S.; Cao, Bing (2025). Global Navigation Satellite System (GNSS) Airborne Radio Occultation (ARO) Observations from the Atmospheric River Reconnaissance Field Campaigns. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0348KRP

Description

The airborne radio occultation (ARO) technique is based on precise measurements of Global Navigation Satellite System (GNSS) signal delays collected from a receiver onboard an aircraft as GNSS satellites set or rise. The excess signal delay induced by propagation through the atmosphere can be converted to ray path refractive bending, which is further interpreted in terms of the refractive index, pressure, temperature, and moisture of a stratified atmosphere. ARO inherits the advantages of high vertical resolution and all-weather capability of spaceborne RO observations and has the additional advantage of continuous and dense sampling of the targeted storm area. The horizontal drift of the representative tangent point retrieval coordinate is an important characteristic of ARO profiles, which greatly extends the sensing area from underneath the aircraft to both sides of the flight track (up to 500 km). This ARO dataset complements the dropsonde, flight level meteorological, and Doppler radar observations by providing simultaneous measurements at no additional expendable cost in the reconnaissance flights. Atmospheric Rivers (ARs) are narrow filaments of high moisture flux responsible for most of the horizontal transport of water vapor from the tropics to mid-latitudes. Improving forecasts of ARs through numerical weather prediction (NWP) is important for increasing the resilience of the western US to flooding and droughts. The AR Reconnaissance (AR Recon) program is a collaborative effort of the Center for Western Weather and Water Extremes (CW3E) and the National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Prediction (NCEP), involving several domestic and international partners, that focuses on atmospheric dynamics, the predictability of ARs, airborne instrumentation, and data assimilation in numerical weather modeling.

Creation Date
  • 2018 to present
Date Issued
  • 2025
Creator
Principal Investigator
Funding

National Science Foundation AGS-1642650 and AGS-1454125. The work was carried out in collaboration with CW3E/UCSD under the Atmospheric River Research Program through sponsorship from the California Department of Water Resources and the US Army Corps of Engineers.

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Language
  • English
Identifier

Identifier: Bing Cao: https://orcid.org/0000-0001-8245-1283

Identifier: Jennifer S. Haase: https://orcid.org/0000-0001-8468-2368

Identifier: Kate Lord: https://orcid.org/0000-0003-3498-0994

Identifier: Michael J. Murphy: https://orcid.org/0000-0003-3309-1597

Identifier: Natelie Contreas: https://orcid.org/0009-0002-9364-910X

Identifier: Nghi Do: https://orcid.org/0000-0002-6584-2933

Identifier: Noah Barton: https://orcid.org/0009-0009-7585-862X

Identifier: Pawel Hordyniec: https://orcid.org/0000-0002-2404-3422

Related Resources

    Primary associated publication

    • Cao, B., Haase, J. S., Murphy Jr., M. J., and Wilson, A. M.: Observing atmospheric rivers using multi-GNSS airborne radio occultation: system description and data evaluation, Atmos. Meas. Tech. Discuss. [preprint, in review, 2024.], https://doi.org/10.5194/amt-2024-119

    • Chen, X. M., S. H. Chen, J. S. Haase, B. J. Murphy, K. N. Wang, J. L. Garrison, S. Y. Chen, C. Y. Huang, L. Adhikari, and F. Xie (2018), The Impact of Airborne Radio Occultation Observations on the Simulation of Hurricane Karl (2010), Monthly Weather Review, 146, 329-350. (23 pp). https://doi.org/10.1175/MWR-D-17-0001.1

    • Cobb, A., Ralph, F. M., Tallapragada, V., Wilson, A. M., Davis, C. A., Monache, L. D., Doyle, J. D., Pappenberger, F., Reynolds, C. A., Subramanian, A., Black, P. G., Cannon, F., Castellano, C., Cordeira, J. M., Haase, J. S., Hecht, C., Kawzenuk, B., Lavers, D. A., Murphy, M. J., Jr., Parrish, J., Rickert, R., Rutz, J. J., Torn, R., Wu, X., & Zheng, M. (2022). Atmospheric River Reconnaissance 2021: A Review. Weather and Forecasting https://doi.org/10.1175/WAF-D-21-0164.1

    • Haase, J., Murphy, M., Cao, B., Ralph, F., Zheng, M., & Delle Monache, L. (2021). Multi-GNSS Airborne Radio Occultation Observations as a Complement to Dropsondes in Atmospheric River Reconnaissance. Journal of Geophysical Research-Atmospheres, 126(21). https://doi.org/10.1029/2021JD034865

    • Murphy, M. J., J. S. Haase, R. Padullés, S.-H. Chen, and M. A. Morris (2019), The potential for discriminating microphysical processes in numerical weather forecasts using airborne polarimetric radio occultations, Remote Sensing Special Issue "Radar Polarimetry—Applications in Remote Sensing of the Atmosphere”, 11, 2268. https://doi.org/10.3390/rs11192268

    • Murphy, M., & Haase, J. (2022). Evaluation of GNSS Radio Occultation Profiles in the Vicinity of Atmospheric Rivers. Atmosphere, 13(9). https://doi.org/10.3390/atmos13091495

    • Wilson, A., Cobb, A., Ralph, F., Tallapragada, V., Davis, C., Doyle, J., Delle Monache, L., Pappenberger, F., Reynolds, C., Subramanian, A., Cannon, F., Cordeira, J., Haase, J., Hecht, C., Lavers, D., Rutz, J., & Zheng, M. (2022). Atmospheric River Reconnaissance Workshop Promotes Research and Operations Partnership. Bulletin of the American Meteorological Society, 103(3), E810–E816. https://doi.org/10.1175/BAMS-D-21-0259.1

    • Xie, F. Q., L. Adhikari, J. S. Haase, B. Murphy, K. N. Wang, and J. L. Garrison (2018), Sensitivity of airborne radio occultation to tropospheric properties over ocean and land, Atmospheric Measurement Techniques, 11, 763-780. (18 pp). https://doi.org/10.5194/amt-11-763-2018

    Related data

    Collection image

    • Image credit: Bing Cao. "Schematic diagram of the ARO."

Global Navigation Satellite System (GNSS) Airborne Radio Occultation (ARO) Observations from the Atmospheric River Reconna...
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