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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2017-159
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
13 Jun 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles
Jakob Schwarz, Gottfried Kirchengast, and Marc Schwaerz Wegener Center for Climate and Global Change (WEGC) and Institute for Geophysics, Astrophysics and Meteorology/Institute of Physics University of Graz, Graz, Austria
Abstract. Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets, and are globally available as a continuous record since 2001. Essential climate variables for the thermodynamic state of the free atmosphere, such as pressure, temperature and tropospheric water vapor profiles (involving background information), can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte-Carlo ensemble methods. The algorithm performance is demonstrated using test-day ensembles of simulated data as well as real RO event data from the satellite missions CHAMP and COSMIC. The results of the Monte-Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications

Citation: Schwarz, J., Kirchengast, G., and Schwaerz, M.: Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-159, in review, 2017.
Jakob Schwarz et al.
Jakob Schwarz et al.
Jakob Schwarz et al.

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Short summary
We process Global Navigation Satellite System radio occultation (RO) observations in a new way with integrated uncertainty propagation; in this study with focus on retrieving atmospheric bending angles from RO excess phase profiles. We find that this new approach within our novel reference occultation processing system (rOPS) exploits the strengths of RO such as its high accuracy and long-term stability in a reliable manner for global climate monitoring and other weather and climate uses.
We process Global Navigation Satellite System radio occultation (RO) observations in a new way...
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