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

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Atmos. Meas. Tech., 8, 3447-3465, 2015
http://www.atmos-meas-tech.net/8/3447/2015/
doi:10.5194/amt-8-3447-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
25 Aug 2015
Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis
Y. Li1,2, G. Kirchengast2,3, B. Scherllin-Pirscher3, R. Norman2, Y. B. Yuan1, J. Fritzer3, M. Schwaerz3, and K. Zhang2 1State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics (IGG), Chinese Academy of Sciences, Wuhan, China
2Satellite Positioning for Atmosphere, Climate, and Environment (SPACE) Research Centre, RMIT University, Melbourne, Victoria, Australia
3Wegener Center for Climate and Global Change (WEGC) and Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
Abstract. We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.

Citation: Li, Y., Kirchengast, G., Scherllin-Pirscher, B., Norman, R., Yuan, Y. B., Fritzer, J., Schwaerz, M., and Zhang, K.: Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis, Atmos. Meas. Tech., 8, 3447-3465, doi:10.5194/amt-8-3447-2015, 2015.
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Short summary
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System-based radio occultation measurements. The new algorithm is evaluated against the OPSv5.6 algorithm developed by the Wegener Center using both simulated and real observed data. It is found that the algorithm can significantly reduce the random errors of optimized bending angles. The retrieved refractivity and temperature profiles are also benefited.
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected...
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