Application of dynamical error estimation for statistical optimization of radio occultation bending angles

Radio Science ◽  
2005 ◽  
Vol 40 (3) ◽  
pp. n/a-n/a ◽  
Author(s):  
Martin S. Lohmann
Keyword(s):  
Error Estimation ◽  
Radio Occultation ◽  
Statistical Optimization ◽  
Dynamical Error ◽  
Bending Angles

scholarly journals Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis

2015 ◽  
Vol 8 (8) ◽  
pp. 3447-3465 ◽  
Author(s):  
Y. Li ◽  
G. Kirchengast ◽  
B. Scherllin-Pirscher ◽  
R. Norman ◽  
Y. B. Yuan ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Processing System ◽  
Covariance Matrices ◽  
Statistical Optimization ◽  
Observation Error ◽  
Random Errors ◽  
Correlation Matrices ◽  
Error Covariance ◽  
Global Mean ◽  
Bending Angles

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.

scholarly journals A new dynamic approach for statistical optimization of GNSS radio occultation bending angles for optimal climate monitoring utility

2013 ◽  
Vol 118 (23) ◽  
pp. 13,022-13,040 ◽  
Author(s):  
Y. Li ◽  
G. Kirchengast ◽  
B. Scherllin-Pirscher ◽  
S. Wu ◽  
M. Schwaerz ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Statistical Optimization ◽  
Dynamic Approach ◽  
Climate Monitoring ◽  
Bending Angles

scholarly journals Dynamic statistical optimization of GNSS radio occultation bending angles: an advanced algorithm and its performance analysis

2015 ◽  
Vol 8 (1) ◽  
pp. 811-855 ◽  
Author(s):  
Y. Li ◽  
G. Kirchengast ◽  
B. Scherllin-Pirscher ◽  
R. Norman ◽  
Y. B. Yuan ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Processing System ◽  
Covariance Matrices ◽  
Statistical Optimization ◽  
Observation Error ◽  
Random Errors ◽  
Correlation Matrices ◽  
Error Covariance ◽  
Global Mean ◽  
Bending Angles

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 CHAMP and 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 in random errors (standard deviations) of optimized bending angles down to about two-thirds 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; (4) produces 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.

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

2018 ◽  
Vol 11 (4) ◽  
pp. 2427-2440 ◽  
Author(s):  
Congliang Liu ◽  
Gottfried Kirchengast ◽  
Yueqiang Sun ◽  
Kefei Zhang ◽  
Robert Norman ◽  
...  
Keyword(s):  
Impact Parameter ◽  
Radio Occultation ◽  
Global Climate ◽  
Weather Prediction ◽  
Signal Propagation ◽  
Satellite System ◽  
Primary Role ◽  
Dual Frequency ◽  
Bending Angle ◽  
Bending Angles

Abstract. 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 higher-order residual ionospheric error (RIE) can still be significant, so it needs to be further mitigated for high-accuracy applications, especially from 35 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 µrad noise level, but were left with 26 exceptional events with anomalous RIEs at the 1 to 10 µrad level that remained unexplained. In this study, we focused on investigating the causes of the high RIE of these exceptional events, employing detailed along-ray-path 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 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 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 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 the 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.

scholarly journals A modification to the standard ionospheric correction method used in GPS radio occultation

2015 ◽  
Vol 8 (8) ◽  
pp. 3385-3393 ◽  
Author(s):  
S. B. Healy ◽  
I. D. Culverwell
Keyword(s):  
Impact Parameter ◽  
Radio Occultation ◽  
Order Term ◽  
Weather Prediction ◽  
Implicit Assumption ◽  
Ionospheric Correction ◽  
Gps Radio Occultation ◽  
Uncertainty Estimates ◽  
The Impact ◽  
Bending Angles

Abstract. A modification to the standard bending-angle correction used in GPS radio occultation (GPS-RO) is proposed. The modified approach should reduce systematic residual ionospheric errors in GPS radio occultation climatologies. A new second-order term is introduced in order to account for a known source of systematic error, which is generally neglected. The new term has the form κ(a) × (αL1(a)-αL2(a))2, where a is the impact parameter and (αL1, αL2) are the L1 and L2 bending angles, respectively. The variable κ is a weak function of the impact parameter, a, but it does depend on a priori ionospheric information. The theoretical basis of the new term is examined. The sensitivity of κ to the assumed ionospheric parameters is investigated in one-dimensional simulations, and it is shown that κ ≃ 10–20 rad−1. We note that the current implicit assumption is κ=0, and this is probably adequate for numerical weather prediction applications. However, the uncertainty in κ should be included in the uncertainty estimates for the geophysical climatologies produced from GPS-RO measurements. The limitations of the new ionospheric correction when applied to CHAMP (Challenging Minisatellite Payload) measurements are noted. These arise because of the assumption that the refractive index is unity at the satellite, made when deriving bending angles from the Doppler shift values.

scholarly journals CHAMP climate data based on inversion of monthly average bending angles

2014 ◽  
Vol 7 (7) ◽  
pp. 7811-7835
Author(s):  
J. Danzer ◽  
H. Gleisner ◽  
S. B. Healy
Keyword(s):  
Radio Occultation ◽  
Research Question ◽  
Random Noise ◽  
Full Range ◽  
Statistical Optimization ◽  
Climate Data ◽  
Bending Angle ◽  
Monthly Average ◽  
High Latitude Region ◽  
Champ Data

Abstract. GNSS Radio Occultation (RO) refractivity climatologies for the stratosphere can be obtained from the Abel inversion of monthly average bending-angle profiles. The averaging of large numbers of profiles suppresses random noise and this, in combination with simple exponential extrapolation above an altitude of 80 km, circumvents the need for a "statistical optimization" step in the processing. Using data from the US-Taiwanese COSMIC mission, which provides ~ 1500–2000 occultations per day, it has been shown that this Average-Profile Inversion (API) technique provides a robust method for generating stratospheric refractivity climatologies. Prior to the launch of COSMIC in mid-2006, the data records rely on data from the CHAMP mission. In order to exploit the full range of available RO data, the usage of CHAMP data is also required. CHAMP only provided ~ 200 profiles per day, and the measurements were noisier than COSMIC. As a consequence, the main research question in this study was to see if the average bending angle approach is also applicable to CHAMP data. Different methods for suppression of random noise – statistical and through data quality pre-screening – were tested. The API retrievals were compared with the more conventional approach of averaging individual refractivity profiles, produced with the implementation of statistical optimization used in the EUMETSAT Radio Occultation Meteorology Satellite Application Facility (ROM SAF) operational processing. In this study it is demonstrated that the API retrieval technique works well for CHAMP data, enabling the generation of long-term stratospheric RO climate data records from August 2001 and onward. The resulting CHAMP refractivity climatologies are found to be practically identical to the standard retrieval at the DMI below altitudes of 35 km. Between 35 km to 50 km the differences between the two retrieval methods started to increase, showing largest differences at high latitudes and high altitudes. Furthermore, in the winter hemisphere high latitude region, the biases relative to ECMWF were generally smaller for the new approach than for the standard retrieval.

scholarly journals Simultaneous Radio Occultation Predictions for Inter-Satellite Comparison of Bending Angle Profiles from COSMIC-2 and GeoOptics

2021 ◽  
Vol 13 (18) ◽  
pp. 3644
Author(s):  
Yong Chen ◽  
Xi Shao ◽  
Changyong Cao ◽  
Shu-peng Ho
Keyword(s):  
Radio Occultation ◽  
International System ◽  
Weather Prediction ◽  
Prediction Method ◽  
Low Earth Orbit ◽  
Weather Data ◽  
Bending Angle ◽  
System Of Units ◽  
Leo Satellites ◽  
Bending Angles

The Global Navigation Satellite System (GNSS) radio occultation (RO) is a remote sensing technique that uses International System of Units (SI) traceable GNSS signals for atmospheric limb soundings. The RO bending angle/sounding profiles are needed for assimilation in Numerical Weather Prediction (NWP) models, weather, climate, and space weather applications. Evaluating these RO data to ensure the high data quality for these applications is becoming more and more critical. This study presents a method for predicting radio occultation events, from which simultaneous radio occultation (SRO) for a pair of low-Earth-orbit (LEO) satellites on the limb to the same GNSS satellite can be obtained. The SRO method complements the Simultaneous Nadir Overpass (SNO) method (for nadir viewing satellite instruments), which has been widely used to inter-calibrate LEO to LEO and LEO to geosynchronous-equatorial-orbit (GEO) satellites. Unlike the SNO method, the SRO method involves three satellites: a GNSS and two LEO satellites with RO receivers. The SRO method allows for the direct comparison of bending angles when the simultaneous RO measurements for two LEO satellites receiving the same GNSS signal pass through approximately the same atmosphere within minutes in time and within less than 200 km of distance from each other. The prediction method can also be applied to radiosonde overpass prediction, and coordinate radiosonde launches for inter-comparisons between RO and radiosonde profiles. The main advantage of the SRO comparisons of bending angles is the significantly reduced uncertainties due to the much shorter time and smaller atmospheric path differences than traditional RO comparisons. To demonstrate the usefulness of this method, we present a comparison of the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) and GeoOpitcs RO profiles using SRO data for two time periods: Commercial Weather Data (CWD) data delivery order-1 (DO-1): 15 December 2020–15 January 2021 and CWD DO-2: 17 March 2021–31 August 2021. The results show good agreement in the bending angles between the COSMIC-2 RO measurements and those from GeoOptics, although systematic biases are also found in the inter-comparisons. Instrument and processing algorithm performances for the signal-to-noise ratio (SNR), penetration height, and bending angle retrieval uncertainty are also characterized. Given the efficiency of this method and the many RO measurements that are publicly and commercially available as well as the expansion of receiver capabilities to all GNSS systems, it is expected that this method can be used to validate/inter-calibrate GNSS RO measurements from different missions.

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