Articles | Volume 18, issue 17
https://doi.org/10.5194/amt-18-4293-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-4293-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The impact of differences in retrieval algorithms between processing centers on GNSS radio occultation refractivity retrievals in the planetary boundary layer
Atmospheric and Environmental Research, Inc., Lexington, MA 02421, USA
Stephen S. Leroy
Atmospheric and Environmental Research, Inc., Lexington, MA 02421, USA
Chi O. Ao
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
E. Robert Kursinski
PlanetiQ, 15000 West 6th Avenue, Suite 202, Golden, CO 80041, USA
Kevin J. Nelson
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Kuo-Nung Wang
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Feiqin Xie
Department of Physical and Environmental Sciences, Texas A&M University, Corpus Christi, TX 78412, USA
Related authors
No articles found.
Manisha Ganeshan, Dong L. Wu, Joseph A. Santanello, Jie Gong, Chi Ao, Panagiotis Vergados, and Kevin J. Nelson
Atmos. Meas. Tech., 18, 1389–1403, https://doi.org/10.5194/amt-18-1389-2025, https://doi.org/10.5194/amt-18-1389-2025, 2025
Short summary
Short summary
This study explores the potential of two newly launched commercial Global Navigation Satellite System (GNSS) radio occultation (RO) satellite missions for advancing Arctic lower-atmospheric studies. The products have a good sampling of the lower Arctic atmosphere and are useful to derive the planetary boundary layer (PBL) height during winter months. This research is a step towards closing the observation gap in polar regions due to the decomissioning of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1) GNSS RO mission and the lack of high-latitude coverage by its successor (COSMIC-2).
Jonas E. Katona, Manuel de la Torre Juárez, Terence L. Kubar, F. Joseph Turk, Kuo-Nung Wang, and Ramon Padullés
Atmos. Meas. Tech., 18, 953–970, https://doi.org/10.5194/amt-18-953-2025, https://doi.org/10.5194/amt-18-953-2025, 2025
Short summary
Short summary
Polarimetric radio occultations (PROs) use polarized radio signals from satellites to detect moisture and precipitation in Earth's atmosphere. By applying nonlinear regression and k-means cluster analysis to over 2 years of PRO and non-PRO data, this study shows how deviations from a refractivity model relate to vertical profiles of water vapor pressure (moisture) and that differences between components of PRO signals correlate directly with vertical profiles of water path (precipitation).
Endrit Shehaj, Stephen Leroy, Kerri Cahoy, Alain Geiger, Laura Crocetti, Gregor Moeller, Benedikt Soja, and Markus Rothacher
Atmos. Meas. Tech., 18, 57–72, https://doi.org/10.5194/amt-18-57-2025, https://doi.org/10.5194/amt-18-57-2025, 2025
Short summary
Short summary
This work investigates whether machine learning (ML) can offer an alternative to existing methods to map radio occultation (RO) products, allowing the extraction of information not visible in direct observations. ML can further improve the results of Bayesian interpolation, a state-of-the-art method to map RO observations. The results display improvements in horizontal and temporal domains, at heights ranging from the planetary boundary layer up to the lower stratosphere, and for all seasons.
Ramon Padullés, Estel Cardellach, Antía Paz, Santi Oliveras, Douglas C. Hunt, Sergey Sokolovskiy, Jan-Peter Weiss, Kuo-Nung Wang, F. Joe Turk, Chi O. Ao, and Manuel de la Torre Juárez
Earth Syst. Sci. Data, 16, 5643–5663, https://doi.org/10.5194/essd-16-5643-2024, https://doi.org/10.5194/essd-16-5643-2024, 2024
Short summary
Short summary
This dataset provides, for the first time, combined observations of clouds and precipitation with coincident retrievals of atmospheric thermodynamics obtained from the same space-based instrument. Furthermore, it provides the locations of the ray trajectories of the observations along various precipitation-related products interpolated into them with the aim of fostering the use of such dataset in scientific and operational applications.
Thomas E. Winning Jr., Feiqin Xie, and Kevin J. Nelson
Atmos. Meas. Tech., 17, 6851–6863, https://doi.org/10.5194/amt-17-6851-2024, https://doi.org/10.5194/amt-17-6851-2024, 2024
Short summary
Short summary
The effect of ducting due to the presence of the planetary boundary layer (PBL) is prevalent over the northeastern Pacific Ocean from Los Angeles to Honolulu, USA. The ducting-induced refractivity bias in the radiosonde climatology and ERA5 data is highly correlated with the height of the PBL. The magnitude of bias is linearly dependent on the strength of ducting but not the location, and the overall reanalysis data systematically underestimate the height of the PBL by as much as 120 m.
Kuo-Nung Wang, Chi O. Ao, Mary G. Morris, George A. Hajj, Marcin J. Kurowski, Francis J. Turk, and Angelyn W. Moore
Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, https://doi.org/10.5194/amt-17-583-2024, 2024
Short summary
Short summary
In this article, we described a joint retrieval approach combining two techniques, RO and MWR, to obtain high vertical resolution and solve for temperature and moisture independently. The results show that the complicated structure in the lower troposphere can be better resolved with much smaller biases, and the RO+MWR combination is the most stable scenario in our sensitivity analysis. This approach is also applied to real data (COSMIC-2/Suomi-NPP) to show the promise of joint RO+MWR retrieval.
Alex Meredith, Stephen Leroy, Lucy Halperin, and Kerri Cahoy
Atmos. Meas. Tech., 16, 3345–3361, https://doi.org/10.5194/amt-16-3345-2023, https://doi.org/10.5194/amt-16-3345-2023, 2023
Short summary
Short summary
We developed a new efficient algorithm leveraging orbital dynamics to collocate radio occultation soundings with microwave radiance soundings. This new algorithm is 99 % accurate and is much faster than traditional collocation-finding approaches. Speeding up collocation finding is useful for calibrating and validating microwave radiometers and for data assimilation into numerical weather prediction models. Our algorithm can also be used to predict collocation yield for new satellite missions.
Kevin J. Nelson, Feiqin Xie, Bryan C. Chan, Ashish Goel, Jonathan Kosh, Tyler G. R. Reid, Corey R. Snyder, and Paul M. Tarantino
Atmos. Meas. Tech., 16, 941–954, https://doi.org/10.5194/amt-16-941-2023, https://doi.org/10.5194/amt-16-941-2023, 2023
Short summary
Short summary
Global Navigation Satellite System (GNSS) radio occultation (RO) remote sensing is effective for atmospheric profiling. The capability of a low-cost and scalable commercial off-the-shelf (COTS) GNSS receiver on board high-altitude balloons is tested in two campaigns. Preliminary results demonstrate high-quality refractivity observations from the COTS RO receiver, which is worth further improvement for dense atmospheric observations over a targeted region.
Anthony J. Mannucci, Chi O. Ao, Byron A. Iijima, Thomas K. Meehan, Panagiotis Vergados, E. Robert Kursinski, and William S. Schreiner
Atmos. Meas. Tech., 15, 4971–4987, https://doi.org/10.5194/amt-15-4971-2022, https://doi.org/10.5194/amt-15-4971-2022, 2022
Short summary
Short summary
The Global Positioning System (GPS) radio occultation (RO) technique is a satellite-based method for producing highly accurate vertical profiles of atmospheric temperature and pressure. RO profiles are used to monitor global climate trends, particularly in that region of the atmosphere that includes the lower stratosphere. Two data sets spanning 1995–1997 that were produced from the first RO satellite are highly accurate and can be used to assess global atmospheric models.
Cited articles
Adler, R., Huffman, G., Chang, A., Ferraro, R., Xie, P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., and Arkin, P.: The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeorol., 4, 1147–1167, 2003. a
Alexander, P., de la Torre, A., and Schmidt, T.: Global Stratospheric Properties of Gravity Waves From 1 Year of Radio Occultations, J. Geophys. Res., 129, e2023JD040609, https://doi.org/10.1029/2023JD040609, 2024. a
Anthes, R., Bernhardt, P., Chen, Y., Cucurull, L., Dymond, K., Ector, D., Healy, S., Ho, S., Hunt, D., Kuo, Y., Liu, H., Manning, K., McCormick, C., Meehan, T., Randel, W., Rocken, C., Schreiner, W., Sokolovskiy, S., Syndergaard, S., Thompson, D., Trenberth, K., Wee, T., Yen, N., and Zeng, Z.: The COSMIC/FORMOSAT-3 Mission: Early Results, B. Am. Meteorol. Soc., 89, 313–334, https://doi.org/10.1175/BAMS-89-3-313, 2008. a, b, c
Ao, C., Waliser, D., Chan, S., Li, J., Tian, B., Xie, F., and Mannucci, A.: Planetary boundary layer heights from GPS radio occultation refractivity and humidity profiles, J. Geophys. Res., 117, D16117, https://doi.org/10.1029/2012JD017598, 2012. a, b
Bauer, P., Radnóti, G., Healy, S., and Cardinali, C.: GNSS Radio Occultation Constellation Observing System Experiments, Mon. Weather Rev., 142, 555–572, https://doi.org/10.1175/MWR-D-13-00130.1, 2014. a
Born, M. and Wolf, E.: Principles of Optics, 6th edn., Cambridge University Press, Cambridge, England, https://doi.org/10.1017/CBO9781139644181, 1980. a
Cardellach, E. and Oliveras, S.: Assessment of a potential reflection flag product, Tech. rep., IEEC, Barcelona, Spain, https://rom-saf.eumetsat.int/general-documents/rsr/rsr_23.pdf (last access: 14 April 2025), 2016. a
Cardellach, E., Oliveras, S., and Rius, A.: Applications of the Reflected Signals Found in GNSS Radio Occultation Events, https://www.ecmwf.int/sites/default/files/elibrary/2008/7460-applications-reflected-signals-found-gnss-radio-occultation-events.pdf (last access: 14 April 2025), 2008. a
Cardinali, C. and Healy, S.: Impact of GPS radio occultation measurements in the ECMWF system using adjoint-based diagnostics, Q. J. Roy. Meteor. Soc., 140, 2315–2320, https://doi.org/10.1002/qj.2300, 2014. a
Chang, H., Lee, J., Yoon, H., Morton, Y., and Saltman, A.: Performance assessment of radio occultation data from GeoOptics by comparing with COSMIC data, Earth Planets Space, 74, 17, https://doi.org/10.1186/s40623-022-01667-6, 2022. a
Cucurull, L.: Recent Impact of COSMIC-2 with Improved Radio Occultation Data Assimilation Algorithms, Weather Forecast., 38, 1829–1847, https://doi.org/10.1175/WAF-D-22-0186.1, 2023. a
Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hersbach, H., Hólm, E., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A., Monge-Sanz, B., Morcrette, J., Park, B., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011. a
European Centre for Medium-Range Weather Forecasts: ERA5 Reanalysis Model Level Data, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/XV5R-5344, 2022. a, b, c
Feng, X., Xie, F., Ao, C., and Anthes, R.: Ducting and Biases of GPS Radio Occultation Bending Angle and Refractivity in the Moist Lower Troposphere, J. Atmos. Ocean. Tech., 37, 1013–1025, https://doi.org/10.1175/JTECH-D-19-0206.1, 2020. a, b, c, d
Fjeldbo, G. and Eshleman, V.: The atmosphere of Mars analyzed by integral inversion of the Mariner IV occultation data, Planet. Space Sci., 16, 1035–1059, https://doi.org/10.1016/0032-0633(68)90020-2, 1968. a
Fjeldbo, G., Kliore, A., and Eshleman, V.: Neutral atmosphere of Venus as studied with Mariner-V radio occultation experiments, Astron. J., 76, 123–140, https://doi.org/10.1086/111096, 1971. a
Gleisner, H., Ringer, M., and Healy, S.: Monitoring global climate change using GNSS radio occultation, npj Climate Atmos. Sci., 5, 6, https://doi.org/10.1038/s41612-022-00229-7, 2022. a
Golea, V., Knapp, K., Young, A., Inamdar, A., Hankins, B., and NOAA's Climate Data Record Program: International Satellite Cloud Climatology Project Climate Data Record, H-Series ISCPP, https://doi.org/10.7289/V5QZ281S, 2016. a
Gorbunov, M.: Canonical transform method for processing radio occultation data in the lower troposphere, Radio Sci., 37, 9-1–9-10, https://doi.org/10.1029/2000RS002592, 2002a. a
Gorbunov, M. and Lauritsen, K.: Analysis of wave fields by Fourier integral operators and their application for radio occultations, Radio Sci., 39, RS4010, https://doi.org/10.1029/2003RS002971, 2004. a, b, c, d
Gorbunov, M., Benzon, H., Jensen, A., Lohmann, M., and Nielsen, A.: Comparative analysis of radio occultation processing approaches based on Fourier integral operators, Radio Sci., 39, RS6004, https://doi.org/10.1029/2003RS002916, 2004. a, b
Gorbunov, M., Irisov, V., and Rocken, C.: Noise Floor and Signal-to-Noise Ratio of Radio Occultation Observations: A Cross-Mission Statistical Comparison, Remote Sens.-Basel, 14, 691, https://doi.org/10.3390/rs14030691, 2022a. a
Gorbunov, M., Irisov, V., and Rocken, C.: The Influence of the Signal-to-Noise Ratio upon Radio Occultation Retrievals, Remote Sens.-Basel, 14, 2742, https://doi.org/10.3390/rs14122742, 2022b. a
Gorbunov, M. E.: Ionospheric correction and statistical optimization of radio occultation data, Radio Sci., 37, 17-1–17-9, https://doi.org/10.1029/2000RS002370, 2002b. a
Gorbunov, M. E.: Radio-holographic analysis of Microlab-1 radio occultation data in the lower troposphere, J. Geophys. Res.-Atmos., 107, ACK 7-1–ACK 7-10, https://doi.org/10.1029/2001JD000889, 2002c. a
Hajj, G., Kursinski, E., Romans, L., Bertiger, W., and Leroy, S.: A technical description of atmospheric sounding by GPS occultation, J. Atmos. Sol.-Terr. Phy., 64, 451–469, https://doi.org/10.1016/S1364-6826(01)00114-6, 2002. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Ho, S., Kirchengast, K., Leroy, S., Wickert, J., Mannucci, A., Steiner, A., Hunt, D., Schreiner, W., Sokolovskiy, S., Ao, C., Borsche, M., von Engeln, A., Foelsche, U., Heise, S., Iijima, B., Kuo, Y., Kursinski, R., Pirscher, B., Ringer, M., Rocken, C., and Schmidt, T.: Estimating the uncertainty of using GPS radio occultation data for climate monitoring: Intercomparisons of CHAMP refractivity climate records from 2002 to 2006 from different data centers, J. Geophys. Res., 114, D23107, https://doi.org/doi:10.1029/2009JD011969, 2009. a
Ho, S., Zhou, X., Kuo, Y., Hunt, D., and Wang, J.: Global Evaluation of Radiosonde Water Vapor Systematic Biases using GPS Radio Occultation from COSMIC and ECMWF Analysis, Remote Sens.-Basel, 2, 1320–1330, https://doi.org/10.3390/rs2051320, 2010. a
Ho, S., Hunt, D., Steiner, A., Mannucci, A., Kirchengast, G., Gleisner, H., Heise, S., von Engeln, A., Marquardt, C., Sokolovskiy, S., Schreiner, W., Scherllin-Pirscher, B., Ao, C., Wickert, J., Syndergaard, S., Lauritsen, K., Leroy, S., Kursinski, E., Kuo, Y., Foelsche, U., Schmidt, T., and Gorbunov, M.: Reproducibility of GPS radio occultation data for climate monitoring: Profile-to-profile inter-comparison of CHAMP and climate records 2002 to 2008 from six data centers, J. Geophys. Res., 117, D18111, https://doi.org/10.1029/2012JD017665, 2012. a, b, c, d
Jensen, A., Lohmann, M., Benzon, H., and Nielsen, A.: Full spectrum inversion of radio occultation signals, Radio Sci., 38, 1040, https://doi.org/10.1029/2002RS002763, 2003. a
Jensen, A., Lohmann, M., Nielsen, A., and Benzon, H.: Geometrical optics phase matching of radio occultation signals, Radio Sci., 39, RS3009, https://doi.org/10.1029/2003RS002899, 2004. a, b, c
Jin, F.-F.: Tropical ocean-atmosphere interaction, the Pacific cold tongue, and the El Niño-Southern Oscillation, Science, 274, 76–78, 1996. a
Johnston, B. and Xie, F.: Characterizing Extratropical Tropopause Bimodality and its Relationship to the Occurrence of Double Tropopauses Using COSMIC GPS Radio Occultation Observations, Remote Sens.-Basel, 12, 1109, https://doi.org/10.3390/rs12071109, 2018. a
Johnston, B., Xie, F., and Liu, C.: The Effects of Deep Convection on Regional Temperature Structure in the Tropical Upper Troposphere and Lower Stratosphere, J. Geophys. Res., 123, 1585–1603, https://doi.org/10.1002/2017JD027120, 2018. a
Kuo, Y., Wee, T., Sokolovskiy, S., Rocken, C., Schreiner, W., Hunt, D., and Anthes, R.: Inversion and Error Estimation of GPS Radio Occultation Data, J. Meteorol. Soc. Jpn., 82, 507–531, https://doi.org/10.2151/jmsj.2004.507, 2004. a
Kursinski, E., Hajj, G., Hardy, K., Romans, L., and Schofield, J.: Observing tropospheric water-vapor by radio occultation using the Global Positioning System, Geophys. Res. Lett., 22, 2365–2368, https://doi.org/10.1029/95GL02127, 1995. a
Kursinski, E., Hajj, G., Bertiger, W., Leroy, S., Meehan, T., Romans, L., Schofield, J., McCleese, D., Melbourne, W., Thornton, C., Yunck, T., Eyre, J., and Nagatani, R.: Initial results of radio occultation observations of Earth's atmosphere using the Global Positioning System, Science, 271, 1107–1110, https://doi.org/10.1126/science.271.5252.1107, 1996. a
Kursinski, E., Hajj, G., Schofield, J., Linfield, R., and Hardy, K.: Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System, J. Geophys. Res., 102, 23429–23465, https://doi.org/10.1029/97JD01569, 1997. a, b, c
Kursinski, E., Hajj, G., Leroy, S., and Herman, B.: The GPS radio occultation technique, Terrestrial, Atmospheric and Oceanic Sciences (TAO), 11, 53–114, https://doi.org/10.3319/TAO.2000.11.1.53(COSMIC), 2000. a, b
Lasota, E., Steiner, A. K., Kirchengast, G., and Biondi, R.: Tropical cyclones vertical structure from GNSS radio occultation: an archive covering the period 2001–2018, Earth Syst. Sci. Data, 12, 2679–2693, https://doi.org/10.5194/essd-12-2679-2020, 2020. a, b
Leroy, S. and McVey, A.: GNSS Radio Occultation Data in the AWS Cloud: Utilities and Examples, Zenodo, https://doi.org/10.5281/zenodo.7799039, 2023. a, b
Leroy, S., McVey, A., Leidner, S., Zhang, H., and Gleisner, H.: GNSS Radio Occultation Data in the AWS Cloud, Earth and Space Sci., 11, e2023EA003021, https://doi.org/10.1029/2023EA003021, 2024. a
Liou, Y., Pavelyev, A., Liu, S., Pavelyev, A., Yen, N., Huang, C., and Fong, C.: FORMOSAT-3/COSMIC GPS Radio Occultation Mission: Preliminary Results, IEEE T. Geosci. Remote, 45, 3813–3844, https://doi.org/10.1109/TGRS.2007.903365, 2007. a
Mannucci, A., Ao, C., and Williamson, W.: GNSS Radio Occultation, Chap. 33, John Wiley & Sons, Ltd, 971–1013, https://doi.org/10.1002/9781119458449.ch33, 2020. a
Moum, J., Perlin, A., Nash, J., and McPhaden, M.: Seasonal sea surface cooling in the equatorial Pacific cold tongue controlled by ocean mixing, Nature, 500, 64–67, 2013. a
National Academies of Sciences, Engineering, and Medicine: Thriving on Our Changing Planet: A Decadal Strategy for Earth Observation from Space, The National Academies Press, Washington, D. C., https://doi.org/10.17226/24938, 2018. a
Randel, W. and Wu, F.: Kelvin wave variability near the equatorial tropopause observed in GPS radio occultation measurements, J. Geophys. Res., 110, D03102, https://doi.org/10.1029/2004JD005006, 2005. a
Randel, W., Wu, F., and Ríos, W.: Thermal variability of the tropical tropopause region derived from GPS/MET observations, J. Geophys. Res., 108, 4024, https://doi.org/10.1029/2002JD002595, 2003. a
Rocken, C., Kuo, Y., Schreiner, W., Hunt, D., Sokolovskiy, S., and McCormick, C.: COSMIC system description, Terr. Atmos. Ocean. Sci., 11, 21–52, 2000. a
ROM SAF: ROM SAF Radio Occultation Climate Data Record – COSMIC, EUMETSAT SAF on Radio Occultation Meteorology, Tech. rep., https://doi.org/10.15770/EUM_SAF_GRM_0003, 2019. a
Schmidt, T., Alexander, P., and de la Torre, A.: Stratospheric gravity wave momentum flux from radio occultations, J. Geophys. Res., 121, 4443–4467, https://doi.org/10.1002/2015JD024135, 2016. a
Schreiner, W., Weiss, J., Braun, J., Chu, V., Fong, J., Hunt, D., Kuo, Y.-H., Meehan, T., Serafino, W., Sjoberg, J., Sokolovskiy, S., Talaat, E., Wee, T., and Zeng, Z.: COSMIC-2 Radio Occultation Constellation: First Results, Geophys. Res. Lett., 47, e2019GL086841, https://doi.org/10.1029/2019GL086841, 2020. a, b
Sievert, T., Rasch, J., Carlström, A., Pettersson, M. I., and Vu, V.: Comparing reflection signatures in radio occultation measurements using the full spectrum inversion and phase matching methods, vol. 10786, 107860A, International Society for Optics and Photonics, SPIE, https://doi.org/10.1117/12.2325386, 2018. a
Smith, E. and Weintraub, S.: The constants in the equation for atmospheric refractive index at radio frequencies, P. IEEE, 41, 1035–1037, 1953. a
Sokolovskiy, S.: Modeling and inverting radio occultation signals in the moist troposphere, Radio Sci., 36, 441–458, https://doi.org/10.1029/1999RS002273, 2001. a, b, c, d
Sokolovskiy, S.: Effect of superrefraction on inversions of radio occultation signals in the lower troposphere, Radio Sci., 38, 1058, https://doi.org/10.1029/2002RS002728, 2003. a, b, c
Sokolovskiy, S., Rocken, C., Hunt, D., Schreiner, W., Johnson, J., Masters, D., and Esterhuizen, S.: GPS profiling of the lower troposphere from space: Inversion and demodulation of the open-loop radio occultation signals, Geophys. Res. Lett., 33, L14816, https://doi.org/10.1029/2006GL026112, 2006. a
Sokolovskiy, S., Schreiner, W., Zeng, Z., Hunt, D., Lin, Y., and Kuo, Y.: Observation, analysis, and modeling deep radio occultation signals: Effects of tropospheric ducts and interfering signals, Radio Sci., 49, 954–970, https://doi.org/10.1002/2014RS005436, 2014. a
Sokolovskiy, S., Zeng, Z., Hunt, D., Weiss, J., Braun, J., Schreiner, W., Anthes, R., Kuo, Y., Zhang, H., Lenschow, D., and Vanhove, T.: Detection of superrefraction at the Top of the Atmospheric Boundary Layer from COSMIC-2 Radio Occultations, J. Atmos. Ocean. Tech., 41, 65–78, https://doi.org/10.1175/JTECH-D-22-0100.1, 2024. a, b
Steiner, A. K., Hunt, D., Ho, S.-P., Kirchengast, G., Mannucci, A. J., Scherllin-Pirscher, B., Gleisner, H., von Engeln, A., Schmidt, T., Ao, C., Leroy, S. S., Kursinski, E. R., Foelsche, U., Gorbunov, M., Heise, S., Kuo, Y.-H., Lauritsen, K. B., Marquardt, C., Rocken, C., Schreiner, W., Sokolovskiy, S., Syndergaard, S., and Wickert, J.: Quantification of structural uncertainty in climate data records from GPS radio occultation, Atmos. Chem. Phys., 13, 1469–1484, https://doi.org/10.5194/acp-13-1469-2013, 2013. a
Steiner, A., Ladstädter, F., Randel, W., Maycock, A., Fu, Q., Claud, C., Gleisner, H., Haimberger, L., Ho, S., Keckhut, P., Leblack, T., Mears, C., Polvani, L., Santer, B., Schmidt, T., Sofieva, V., Wing, R., and Zou, C.: Observed Temperature Changes in the Troposphere and Stratosphere from 1979 to 2018, J. Climate, 33, 8165–8194, https://doi.org/10.1175/JCLI-D-19-0998.1, 2020. a
Syndergaard, S., Nielsen, J., and Lauritsen, K.: Algorithm Theoretical Baseline Document: Level 1B bending angles, Tech. rep., Radio Occultation Meteorology Satellite Application Facility (ROM SAF), Lyngbyvej 100, Copenhagen, Denmark, https://rom-saf.eumetsat.int/product_documents/romsaf_atbd_ba.pdf (last access: 20 April 2025), 2020. a, b
Syndergaard, S., Nielsen, J., and Lauritsen, K.: Algorithm Theoretical Baseline Document: Level 2A refractivity profiles, Tech. rep., Radio Occultation Meteorology Satellite Application Facility (ROM SAF), Lyngbyvej 100, Copenhagen, Denmark, https://rom-saf.eumetsat.int/product_documents/romsaf_atbd_ref.pdf (last access: 20 April 2025), 2021. a
Teixeira, J., Piepmeier, J., Nehrir, A., Ao, C., Chen, S., Clayson, C., Fridlind, A., Lebsock, M., McCarty, W., Salmun, H., Santanello, J., Turner, D., Wang, Z., and Zeng, X.: Toward a Global Planetary Boundary Layer Observing System: The NASA PBL Incubation Study Team Report, Tech. rep., National Aeronautics and Space Administration, https://science.nasa.gov/earth-science/decadal-surveys/decadal-pbl/ (last access: 20 May 2024), 2021. a
Tsuda, T., Nishida, M., Rocken, C., and Ware, R.: A Global Morphology of Gravity Wave Activity in the Stratosphere Revealed by the GPS Occultation Data (GPS/MET), J. Geophys. Res., 105, 7257–7273, 2000. a
UCAR: FORMOSAT-3/COSMIC-1 2021 Reprocessing Data Release, https://data.cosmic.ucar.edu/gnss-ro/cosmic1/repro2021/UCAR_COSMIC1_2021_Repro_Notes.pdf (last access: 20 April 2025), 2022. a
Vergados, P., Mannucci, A., and Su, H.: A validation study for GPS radio occultation data with moist thermodynamic structure of tropical cyclones, J. Geophys. Res., 118, 9401–9413, https://doi.org/10.1002/jgrd.50698, 2013. a
Vergados, P., Ao, C., Mannucci, A., and Kursinski, E.: Quantifying the Tropical Upper Tropospheric Warming Amplification Using Radio Occultation Measurements, Earth and Space Sci., 8, e2020EA001597, https://doi.org/10.1029/2020EA001597, 2021. a
Verkhoglyadova, O., Leroy, S., and Ao, C.: Estimation of Winds from GPS Radio Occultations, J. Atmos. Ocean. Tech., 31, 2451–2461, https://doi.org/10.1175/JTECH-D-14-00061.1, 2014. a
Vorob'ev, V. and Krasil'nikova, T.: Estimation of the accuracy of the atmospheric refractive index recovery from Doppler shift measurements at frequencies used in the NAVSTAR system, Phys. Atmos. Ocean., 29, 602–609, 1994. a
Wang, K., Ao, C., and de la Torre Juárez, M.: GNSS-RO Refractivity Bias Correction Under Ducting Layer Using Surface-Reflection Signal, Remote Sens.-Basel, 12, 359, https://doi.org/10.3390/rs12030359, 2020. a
Wang, K.-N., de la Torre Juárez, M., Ao, C. O., and Xie, F.: Correcting negatively biased refractivity below ducts in GNSS radio occultation: an optimal estimation approach towards improving planetary boundary layer (PBL) characterization, Atmos. Meas. Tech., 10, 4761–4776, https://doi.org/10.5194/amt-10-4761-2017, 2017. a
Wang, K.-N., Ao, C. O., Morris, M. G., Hajj, G. A., Kurowski, M. J., Turk, F. J., and Moore, A. W.: Joint 1DVar retrievals of tropospheric temperature and water vapor from Global Navigation Satellite System radio occultation (GNSS-RO) and microwave radiometer observations, Atmos. Meas. Tech., 17, 583–599, https://doi.org/10.5194/amt-17-583-2024, 2024. a
Wang, L. and Alexander, M.: Global estimates of gravity wave parameters from GPS radio occultation temperature data, J. Geophys. Res., 115, D21122, https://doi.org/10.1029/2010JD013860, 2010. a
Xie, F.: An Approach for Retrieving Marine Boundary Layer Refractivity from GPS Occultation Data in the Presence of Superrefraction, J. Atmos. Ocean. Tech., 23, 1629–1644, https://doi.org/10.1175/JTECH1996.1, 2006. a, b, c
Xie, F., Wu, D., Ao, C., Kursinski, E., Mannucci, A., and Syndergaard, S.: Super-refraction effects on GPS radio occultation refractivity in marine boundary layers, Geophys. Res. Lett., 37, L11805, https://doi.org/10.1029/2010GL043299, 2010. a, b, c, d
Xie, F., Wu, D. L., Ao, C. O., Mannucci, A. J., and Kursinski, E. R.: Advances and limitations of atmospheric boundary layer observations with GPS occultation over southeast Pacific Ocean, Atmos. Chem. Phys., 12, 903–918, https://doi.org/10.5194/acp-12-903-2012, 2012. a
Zeng, Z., Sokolovskiy, S., Schreiner, W., Hunt, D., Lin, J., and Kuo, Y.-H.: Ionospheric correction of GPS radio occultation data in the troposphere, Atmos. Meas. Tech., 9, 335–346, https://doi.org/10.5194/amt-9-335-2016, 2016. a
Zeng, Z., Sokolovskiy, S., Hunt, D., Weiss, J., Braun, J., Schreiner, W., Anthes, R., Kuo, Y., Zhang, H., Lenschow, D., and Vanhove, T.: Estimation of the heights of superrefraction layers from radio occultation signals, https://www.cosmic.ucar.edu/sites/default/files/2024-09/13%20-%20Zeng_Zhen_2024.09.16.pptx.pdf (last access: 2 October 2024), 2024. a
Zhang, W., Li, J., and Zhao, X.: Sea surface temperature cooling mode in the Pacific cold tongue, J. Geophys. Res.-Oceans, 115, C12042, https://doi.org/10.1029/2010JC006501, 2010. a
Short summary
Uncertainty estimation for Global Navigation Satellite System (GNSS) radio occultation (RO) soundings in the planetary boundary layer (PBL) depends on the algorithms used to process the RO data. We compare the refractivity retrievals from three RO processing centers – each with their own retrieval algorithm – in the PBL, finding a strong underestimation of refractivity in regions with the strongest refractivity gradients, especially in Jet Propulsion Laboratory (JPL) processing, as well as areas of weak overestimation of refractivity near the poles.
Uncertainty estimation for Global Navigation Satellite System (GNSS) radio occultation (RO)...