Empirical analysis and modeling of errors of atmospheric profiles from GPS radio occultation

Scherllin‐Pirscher, Barbara; Steiner, Andrea; Kirchengast, Gottfried; Kuo, Ying‐Hwa; Foelsche, Ulrich

doi:10.5194/amt-4-1875-2011

Cited by 86 publications

(91 citation statements)

References 46 publications

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“…Ho et al, 2009;Scherllin-Pirscher et al, 2011b) and further on to about 0.12 % decade −1 in bending angle (factor ∼2.4; e.g. Sofieva and Kyrölä, 2004;Scherllin-Pirscher et al, 2011b).…”

Section: Mean Trends and Structural Uncertaintymentioning

confidence: 99%

Quantification of structural uncertainty in climate data records from GPS radio occultation

et al. 2013

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Global Positioning System (GPS) radio occultation (RO) has provided continuous observations of the Earth's atmosphere since 2001 with global coverage, all-weather capability, and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS). Precise time measurements enable long-term stability but careful processing is needed. Here we provide climate-oriented atmospheric scientists with multicenter-based results on the long-term stability of RO climatological fields for trend studies. We quantify the structural uncertainty of atmospheric trends estimated from the RO record, which arises from current processing schemes of six international RO processing centers, DMI Copenhagen, EUM Darmstadt, GFZ Potsdam, JPL Pasadena, UCAR Boulder, and WEGC Graz. Monthly-mean zonal-mean fields of bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature from the CHAMP mission are compared for September 2001 to September 2008. We find that structural uncertainty is lowest in the tropics and mid-latitudes (50° S to 50° N) from 8 km to 25 km for all inspected RO variables. In this region, the structural uncertainty in trends over 7 yr is <0.03% for bending angle, refractivity, and pressure, <3 m for geopotential height of pressure levels, and <0.06 K for temperature; low enough for detecting a climate change signal within about a decade. Larger structural uncertainty above about 25 km and at high latitudes is attributable to differences in the processing schemes, which undergo continuous improvements. Though current use of RO for reliable climate trend assessment is bound to 50° S to 50° N, our results show that quality, consistency, and reproducibility are favorable in the UTLS for the establishment of a climate benchmark record

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Section: Mean Trends and Structural Uncertaintymentioning

confidence: 99%

Quantification of structural uncertainty in climate data records from GPS radio occultation

et al. 2013

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“…The target domain for the comparative statistical analysis is from 5 km to 35 km height (upper 15 troposphere and lower stratosphere, UTLS), since commonly the data quality above 35 km and below 5 km is less good, due to the ionospheric effects and tropospheric multipath effects, respectively (e.g., Scherllin-Pirscher et al, 2011aSteiner et al, 2013). We first inspect difference statistics to ECMWF and subsequently to radiosondes.…”

Section: Gnos Bds Ro Single-difference and Zero-difference Results Anmentioning

confidence: 99%

Evaluation of atmospheric profiles derived from single- and zero-difference excess phase processing of BeiDou System radio occultation data of the FY-3C GNOS mission

Bai¹,

Liu²,

Meng³

et al. 2017

Preprint

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The Global Navigation Satellite System (GNSS) Occultation Sounder (GNOS) is one of the 20 new generation payloads onboard the Chinese FengYun 3 (FY-3) series of operational meteorological satellites for sounding the Earth's neutral atmosphere and ionosphere. GNOS was designed for acquiring setting and rising radio occultation (RO) data by using GNSS signals from both the Chinese BeiDou System (BDS) and the U.S. Global Positioning System (GPS). An ultra-stable oscillator with 1-sec stability (Allan deviation) at the level of 10 -12 was 25 installed on FY-3C GNOS, thus both zero-difference and single-difference excess phase processing methods should be feasible for FY-3C GNOS observations. In this study we focus on evaluating zero-difference processing of BDS RO data vs. single-difference processing, in satellites. We used a 3-month set of GNOS BDS RO data (October to December 2013) for the evaluation and compared atmospheric bending angle and refractivity profiles, derived from 5 single-and zero-difference excess phase data, against co-located profiles from ECMWF (European Centre for Medium-Range Weather Forecasts) analyses. We also compared against co-located refractivity profiles from radiosondes. The statistical evaluation against these reference data shows that the results from single-and zero-difference processing are consistent in both bias and standard deviation, clearly demonstrating the feasibility of zero-10 differencing for GNOS BDS RO observations. The average bias (and standard deviation) of the bending angle and refractivity profiles were found to be as small as about 0.05%-0.2% (and 0.7%-1.6%) over the upper troposphere and lower stratosphere, including for the GEO, IGSO, and MEO subsets. Zero-differencing was found to perform slightly better, as may be expected from its lower vulnerability to noise. The validation results establish that GNOS can 15 provide, on top of GPS RO profiles, accurate and precise BDS RO profiles both from singleand zero-difference processing. The GNOS observations by the series of FY-3 satellites will thus provide important contributions to numerical weather prediction and global climate change analysis.

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“…Error or uncertainty propagation through the geometric optical part of the retrieval chain has been investigated in a series of theoretical and empirical studies (Kursinski et al, 1997;Syndergaard, 1999;Palmer et al, 2000;Rieder and Kirchengast, 2001;Kuo et al, 2004;Steiner and Kirchengast, 2005;Schreiner et al, 2007;Scherllin-Pirscher et al, 2011b;Scherllin-Pirscher et al, 2011a;Scherllin-Pirscher et al, 2017;Innerkofler et al, 2016;Schwarz et al, 2016; Published by Copernicus Publications on behalf of the European Geosciences Union.…”

Section: Introductionmentioning

confidence: 99%

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

Горбунов

Kirchengast

2018

Atmos. Meas. Tech.

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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 (BA) 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 about the lowest 2 km 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 of 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 (CT) 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 and capable of reducing bending angle and corresponding refractivity biases by about a factor of 5. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower bounded by the uncertainty from the (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 and 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.

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Empirical analysis and modeling of errors of atmospheric profiles from GPS radio occultation

Cited by 86 publications

References 46 publications

Quantification of structural uncertainty in climate data records from GPS radio occultation

Quantification of structural uncertainty in climate data records from GPS radio occultation

Evaluation of atmospheric profiles derived from single- and zero-difference excess phase processing of BeiDou System radio occultation data of the FY-3C GNOS mission

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

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