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

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doi:10.5194/amt-2017-145
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
16 May 2017
Review status
This discussion paper is under review for the journal Atmospheric Measurement Techniques (AMT).
Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals
Michael Gorbunov1 and Gottfried Kirchengast2,3 1A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia
2Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria
3Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
Abstract. A new reference occultation processing system (rOPS) will include a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval chain with integrated uncertainty propagation. In this paper, we focus on wave-optics bending angle retrieval in the lower troposphere and introduce 1. an empirically estimated boundary layer bias (BLB) model then employed to reduce the systematic uncertainty of excess phases and bending angles in the lowest about two kilometers of the troposphere, and 2. the estimation of (residual) systematic uncertainties and their propagation together with random uncertainties from excess phase to bending angle profiles. Our BLB model describes the estimated bias of the excess phase transferred from the estimated bias of the bending angle, for which the model is built, informed by analyzing refractivity fluctuation statistics shown to induce such biases. The model is derived from regression analysis using a large ensemble of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) RO observations and concurrent European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. It is formulated in terms predictors and adaptive functions (powers and cross-products of predictors), where we use six main predictors derived from observations: impact altitude, latitude, bending angle and its standard deviation, canonical transform amplitude and its fluctuation index. Based on an ensemble of test days, independent of the days of data used for the regression analysis to establish the BLB model, we find the model very effective for bias reduction, capable of reducing bending angle and corresponding refractivity biases by about a factor of five. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower-bounded by the uncertainty from (indirect) use of ECMWF analysis fields but is significantly lower than the systematic uncertainty without BLB correction. The systematic and random uncertainties are propagated from excess phase to bending angle profiles, using a perturbation approach and the wave-optical method recently introduced by Gorbunov and Kirchengast (2015), starting with estimated excess phase uncertainties. The results are encouraging that this uncertainty propagation approach combined with BLB correction enables a robust reduction and quantification of the uncertainties of excess phases and bending angles in the lower troposphere.

Citation: Gorbunov, M. and Kirchengast, G.: Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2017-145, in review, 2017.
Michael Gorbunov and Gottfried Kirchengast
Michael Gorbunov and Gottfried Kirchengast
Michael Gorbunov and Gottfried Kirchengast

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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.
We study the systematic discreapancies between atmospheric refractivity derived from radio...
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