A simulation study with a new residual ionospheric error model for GPS radio occultation climatologies

Danzer, Julia; Healy, S. B.; Culverwell, I. D.

doi:10.5194/amt-8-3395-2015

Cited by 36 publications

(55 citation statements)

References 22 publications

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“…It has become a significant tool for investigating signal propagation in RO technology. For example, Ladreiter and Kirchengast (1996), Syndergaard (2000), Gobiet and Kirchengast (2004), Steiner and Kirchengast (2005), Hoque 10 and Jakowski (2010), Mannucci et al (2011), Danzer et al (2013Danzer et al ( , 2015, and Liu et al (2013Liu et al ( , 2015 have employed this method inter alia or with a main topical focus to investigate the ionospheric effects on GNSS RO signals.…”

Section: Ray Tracing Methodsmentioning

confidence: 99%

“…However, the higher-order residual ionospheric error (RIE) after this correction is still not negligible for high accuracy applications such as RO-based climate change monitoring (Steiner et al, , 2013. This applies especially above about 35 km altitude where the RIE becomes increasingly relevant compared to the exponentially-decreasing magnitude of the neutral atmospheric bending angle (Syndergaard, 2000;Mannucci et al, 2011;Danzer et al, 2013Danzer et al, , 2015Liu et 15 al., 2013Liu et 15 al., , 2015Healy and Culverwell, 2015).…”

mentioning

confidence: 99%

“…A wide array of studies related to a better understanding of higher-order ionospheric errors in GNSS RO data have been conducted already by a range of scientists (Bassiri and Hajj, 1993;Vorob'ev and Krasil'nikova, 1994;Ladreiter and Kirchengast, 1996;Syndergaard, 2000;Gorbunov, 2002;Jakowski, 2010, 2011;Mannucci et al, 2011;Danzer et al, 2013Danzer et al, , 2015Healy and Culverwell, 2015). Atmos.…”

mentioning

confidence: 99%

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Analysis of ionospheric structure influences on residual ionospheric errors in GNSS radio occultation bending angles based on ray tracing simulations

Liu¹,

Kirchengast²,

Sun³

et al. 2017

Preprint

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The Global Navigation Satellite System (GNSS) radio occultation (RO) technique is widely used to observe the atmosphere for applications such as numerical weather prediction and global climate monitoring. The ionosphere is a major error source to RO at upper stratospheric altitudes and a linear dual-frequency bending angle correction is commonly used to remove the first-order ionospheric effect. However, the residual higher-order ionospheric error (RIE) can still be significant so that it needs to be further mitigated for high accuracy applications, especially from 30 km altitude upward where the RIE is most relevant compared to the decreasing magnitude of the atmospheric bending angle. In a previous study we quantified RIEs using an ensemble of about 700 quasi-realistic end-to-end simulated RO events, finding typical RIEs at the 0.1 to 0.5 rad noise level, but were left with 26 exceptional events with 5 anomalous RIEs at the 1 to 10 rad level that remained unexplained. In this study, we focused on investigating the causes of the high RIE of these exceptional events, employing detailed along-raypath analyses of atmospheric and ionospheric refractivities, impact parameter changes, and bending angles and RIEs under asymmetric and symmetric ionospheric structures. We found that the main causes of the high RIEs are a combination of physics-based effects, where asymmetric ionospheric conditions play the 10 primary role, more than the ionization level driven by solar activity, and technical ray tracer effects due to occasions of imperfect smoothness in ionospheric refractivity model derivatives. We also found that along-ray impact parameter variations of more than 10 to 20 m are well possible due to ionospheric asymmetries, and depending on prevailing horizontal refractivity gradients are positive or negative relative to the initial impact parameter at the GNSS transmitter. Furthermore, mesospheric RIEs are 15 found generally higher than upper stratospheric ones, likely due to being closer in tangent point heights to the ionospheric E layer peaking near 105 km, which increases RIE vulnerability. In future we will further improve the along-ray modeling system to fully isolate technical from physics-based effects and to use it beyond this work for additional GNSS RO signal propagation studies.

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Section: Ray Tracing Methodsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Analysis of ionospheric structure influences on residual ionospheric errors in GNSS radio occultation bending angles based on ray tracing simulations

Liu¹,

Kirchengast²,

Sun³

et al. 2017

Preprint

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“…The residual higher order ionospheric effects are accounted for by a 'conservative best-guess' value (0.05 µrad, reflecting results of Liu et al (2015) and Danzer et al (2013Danzer et al ( , 2015) and added (in root-mean-square form) to the systematic uncertainty 5 profile u s αr , leading to a total estimated systematic uncertainty in this example case of ∼ 0.07 µrad (Figure 8b). Within this uncertainty, the one dominating component from orbit uncertainties (∼ 0.05 µrad, cf.…”

Section: Ionospheric Correctionmentioning

confidence: 99%

“…Based on previous studies (e.g., Liu et al, 2013Liu et al, , 2015Danzer et al, 2013Danzer et al, , 2015, u s RIB is taken to be constant along the entire profile, and is estimated to amount to 0.05 µrad. These last two components, u The resolution of the retrieved bending angle, w αr , essentially corresponds to the higher resolution of the two bending angle 10 profiles α F1 and α F2 , and thus generally closely matches w αF1 in most cases.…”

mentioning

confidence: 99%

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

Schwarz¹,

Kirchengast²,

Schwaerz³

2017

Preprint

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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 5 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 ba-10 sic 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 15 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.

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Integrating uncertainty propagation in GNSS radio occultation retrieval: From bending angle to dry‐air atmospheric profiles

Schwarz

Kirchengast

Schwaerz

2017

Earth and Space Science

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Global Navigation Satellite Systems (GNSS) Radio Occultation (RO) observations, globally available as a continuous record since 2001, are highly accurate and long-term stable data records. Essential climate variables for the thermodynamic state of the free atmosphere, such as temperature and tropospheric water vapor profiles (involving background information), can be derived from these records, which consequentially have the potential to serve as climate benchmark data. In order to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties need to be quantified and traced throughout the retrieval chain. The new Reference Occultation Processing System at the Wegener Center aims to deliver such an accurate retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented for uncertainty propagation from RO bending angle profiles to dry-air variables (pressure and temperature), for estimated random and systematic uncertainties, and for coestimates of observation-to-background weighting ratio profiles. We estimated systematic uncertainty profiles with the same operators as used for the basic profiles retrieval. The random uncertainty propagation was integrated by a covariance propagation approach and validated using Monte-Carlo ensemble methods. We present the results of the validation and demonstrate how the algorithm performs for individual simulated RO events and for ensembles of real RO events. We also compare the new results from the integrated uncertainty propagation to previous ones from empirical error analyses for RO-retrieved atmospheric profiles. We find that the new uncertainty estimation chain shows robust performance and is in good agreement with previous comparable results.

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A simulation study with a new residual ionospheric error model for GPS radio occultation climatologies

Cited by 36 publications

References 22 publications

Analysis of ionospheric structure influences on residual ionospheric errors in GNSS radio occultation bending angles based on ray tracing simulations

Analysis of ionospheric structure influences on residual ionospheric errors in GNSS radio occultation bending angles based on ray tracing simulations

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

Integrating uncertainty propagation in GNSS radio occultation retrieval: From bending angle to dry‐air atmospheric profiles

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