Articles | Volume 11, issue 1
https://doi.org/10.5194/amt-11-111-2018
https://doi.org/10.5194/amt-11-111-2018
Research article
 | 
10 Jan 2018
Research article |  | 10 Jan 2018

Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals

Michael E. Gorbunov and Gottfried Kirchengast

Related authors

Generalized canonical transform method for radio occultation sounding with improved retrieval in the presence of horizontal gradients
Michael Gorbunov, Gottfried Kirchengast, and Kent B. Lauritsen
Atmos. Meas. Tech., 14, 853–867, https://doi.org/10.5194/amt-14-853-2021,https://doi.org/10.5194/amt-14-853-2021, 2021
Short summary
The influence of the signal-to-noise ratio upon radio occultation inversion quality
Michael Gorbunov
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-114,https://doi.org/10.5194/amt-2020-114, 2020
Revised manuscript not accepted
Reflected ray retrieval from radio occultation data using radio holographic filtering of wave fields in ray space
Michael E. Gorbunov, Estel Cardellach, and Kent B. Lauritsen
Atmos. Meas. Tech., 11, 1181–1191, https://doi.org/10.5194/amt-11-1181-2018,https://doi.org/10.5194/amt-11-1181-2018, 2018
Short summary
Fluctuations of radio occultation signals in sounding the Earth's atmosphere
Valery Kan, Michael E. Gorbunov, and Viktoria F. Sofieva
Atmos. Meas. Tech., 11, 663–680, https://doi.org/10.5194/amt-11-663-2018,https://doi.org/10.5194/amt-11-663-2018, 2018
Short summary
Quantification of structural uncertainty in climate data records from GPS radio occultation
A. K. Steiner, D. Hunt, S.-P. Ho, G. Kirchengast, A. J. Mannucci, B. Scherllin-Pirscher, H. Gleisner, A. von Engeln, T. Schmidt, C. Ao, S. S. Leroy, E. R. Kursinski, U. Foelsche, M. Gorbunov, S. Heise, Y.-H. Kuo, K. B. Lauritsen, C. Marquardt, C. Rocken, W. Schreiner, S. Sokolovskiy, S. Syndergaard, and J. Wickert
Atmos. Chem. Phys., 13, 1469–1484, https://doi.org/10.5194/acp-13-1469-2013,https://doi.org/10.5194/acp-13-1469-2013, 2013

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024,https://doi.org/10.5194/amt-17-3933-2024, 2024
Short summary
Scale separation for gravity wave analysis from 3D temperature observations in the mesosphere and lower thermosphere (MLT) region
Björn Linder, Peter Preusse, Qiuyu Chen, Ole Martin Christensen, Lukas Krasauskas, Linda Megner, Manfred Ern, and Jörg Gumbel
Atmos. Meas. Tech., 17, 3829–3841, https://doi.org/10.5194/amt-17-3829-2024,https://doi.org/10.5194/amt-17-3829-2024, 2024
Short summary
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024,https://doi.org/10.5194/amt-17-3605-2024, 2024
Short summary
High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation
Sanja Dmitrovic, Johnathan W. Hair, Brian L. Collister, Ewan Crosbie, Marta A. Fenn, Richard A. Ferrare, David B. Harper, Chris A. Hostetler, Yongxiang Hu, John A. Reagan, Claire E. Robinson, Shane T. Seaman, Taylor J. Shingler, Kenneth L. Thornhill, Holger Vömel, Xubin Zeng, and Armin Sorooshian
Atmos. Meas. Tech., 17, 3515–3532, https://doi.org/10.5194/amt-17-3515-2024,https://doi.org/10.5194/amt-17-3515-2024, 2024
Short summary
Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms
Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024,https://doi.org/10.5194/amt-17-3377-2024, 2024
Short summary

Cited articles

Ao, C.: Effect of ducting on radio occultation measurements: An assessment based on high-resolution radiosonde soundings, Radio Sci., 42, RS2008, https://doi.org/10.1029/2006RS003485, 2007. a
Gorbunov, M.: Wave Optics Propagator Package: Description and User Guide, Technical report for contract eum/co/10/460000812/cja order 4500005632, EUMETSAT, Darmstadt, 2011. a, b, c
Gorbunov, M.: Statistical analysis of systematic errors in RO measurements, ROM SAF Visiting Scientist Report 20, Danish Meteorological Institute, Copenhagen, available at: http://www.romsaf.org/Publications/reports/romsaf_vs20_rep_v11.pdf (last access: 20 December 2017), (SAF/ROM/DMI/REP/VS20/001), 2014. a, b, c, d
Gorbunov, M.: Development of wave optics code for the retrieval of bending angle profiles for reflected rays, ROM SAF CDOP-2, Visiting Scientist Report 27, Danish Meteorological Institute, European Centre for Medium-Range Weather Forecasts, Institut d'Estudis Espacials de Catalunya, Met Office, available at: http://www.romsaf.org/Publications/reports/romsaf_vs27_rep_v10.pdf (last access: 20 December 2017), (SAF/ROM/DMI/REP/VS27/001), 2016. a, b, c
Gorbunov, M. E.: 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, 2002. a
Download
Short summary
We study the systematic discreapancies between atmospheric refractivity derived from radio occulation (RO) sounding of the Earth's atmosphere and the reanalyses of the European Centre for Medium-Range Weather Forecasts. We construct a regression-based bias model. The model can be used for the RO data propagation in the new reference occultation processing system (rOPS) including the uncertainty propagation through the retrieval chain.