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 CHAMP climate data based on the inversion of monthly average bending angles

2014 ◽  
Vol 7 (12) ◽  
pp. 4071-4079 ◽  
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. Global Navigation Satellite System Radio Occultation (GNSS-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 (CHAllenging Mini-satellite Payload) 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 the suppression of random noise – statistical and through data quality prescreening – 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 (European Organisation for the Exploitation of Meteorological Satellites) 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 (Danish Meteorological Institute) below altitudes of 35 km. Between 35 and 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 (European Centre for Medium-range Weather Forecasts) were generally smaller for the new approach than for the standard retrieval.

scholarly journals Consistency and structural uncertainty of multi-mission GPS radio occultation records

2019 ◽  
Author(s):  
Andrea K. Steiner ◽  
Florian Ladstädter ◽  
Chi O. Ao ◽  
Hans Gleisner ◽  
Shu-Peng Ho ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Global Climate ◽  
Structural Uncertainty ◽  
Climate Data ◽  
Climate Trend ◽  
Bending Angle ◽  
Term Stability ◽  
Long Term Stability ◽  
High Vertical Resolution

Abstract. Atmospheric climate monitoring requires observations of high-quality conforming to the criteria of the Global Climate Observing System (GCOS). Radio occultation (RO) data based on Global Positioning System (GPS) signals are available since 2001 from several satellite missions with global coverage, high accuracy, and high vertical resolution in the troposphere and lower stratosphere. We assess the consistency and long-term stability of multi-satellite RO observations for use as climate data records. As a measure of long-term stability, we quantify the structural uncertainty of RO data products arising from different processing schemes. We analyze atmospheric variables from bending angle to temperature for four RO missions, CHAMP, Formosat-3/COSMIC, GRACE, and Metop, provided by five data centers. The comparisons are based on profile-to-profile differences, aggregated to monthly means. Structural uncertainty in trends is found lowest from 8 km to 25 km altitude globally for all inspected RO variables and missions. For temperature, it is < 0.05 K per decade in the global mean and < 0.1 K per decade at all latitudes. Above 25 km, the uncertainty increases for CHAMP while data from the other missions are based on advanced receivers and are usable to higher altitudes for climate trend studies: dry temperature to 35 km, refractivity to 40 km, and bending angle to 50 km. Larger differences in RO data at high altitudes and latitudes are mainly due to different implementation choices in the retrievals. The intercomparison helped to further enhance the maturity of the RO record and confirms the climate quality of multi-satellite RO observations towards establishing a GCOS climate data record.

scholarly journals Consistency and structural uncertainty of multi-mission GPS radio occultation records

2020 ◽  
Vol 13 (5) ◽  
pp. 2547-2575 ◽  
Author(s):  
Andrea K. Steiner ◽  
Florian Ladstädter ◽  
Chi O. Ao ◽  
Hans Gleisner ◽  
Shu-Peng Ho ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Global Climate ◽  
Structural Uncertainty ◽  
Climate Data ◽  
Climate Trend ◽  
Bending Angle ◽  
Term Stability ◽  
Long Term Stability ◽  
High Vertical Resolution

Abstract. Atmospheric climate monitoring requires observations of high quality that conform to the criteria of the Global Climate Observing System (GCOS). Radio occultation (RO) data based on Global Positioning System (GPS) signals are available since 2001 from several satellite missions with global coverage, high accuracy, and high vertical resolution in the troposphere and lower stratosphere. We assess the consistency and long-term stability of multi-satellite RO observations for use as climate data records. As a measure of long-term stability, we quantify the structural uncertainty of RO data products arising from different processing schemes. We analyze atmospheric variables from bending angle to temperature for four RO missions, CHAMP, Formosat-3/COSMIC, GRACE, and Metop, provided by five data centers. The comparisons are based on profile-to-profile differences aggregated to monthly medians. Structural uncertainty in trends is found to be lowest from 8 to 25 km of altitude globally for all inspected RO variables and missions. For temperature, it is < 0.05 K per decade in the global mean and < 0.1 K per decade at all latitudes. Above 25 km, the uncertainty increases for CHAMP, while data from the other missions – based on advanced receivers – are usable to higher altitudes for climate trend studies: dry temperature to 35 km, refractivity to 40 km, and bending angle to 50 km. Larger differences in RO data at high altitudes and latitudes are mainly due to different implementation choices in the retrievals. The intercomparison helped to further enhance the maturity of the RO record and confirms the climate quality of multi-satellite RO observations towards establishing a GCOS climate data record.

scholarly journals A simplified approach for generating GNSS radio occultation refractivity climatologies

2012 ◽  
Vol 5 (4) ◽  
pp. 5245-5269
Author(s):  
H. Gleisner ◽  
S. B. Healy
Keyword(s):  
Radio Occultation ◽  
A Priori ◽  
Statistical Optimization ◽  
Bending Angle ◽  
New Approach ◽  
Simplified Approach ◽  
Processing Step ◽  
Retrieval Scheme ◽  
Angle Space ◽  
Future Work

Abstract. The possibility of simplifying the retrieval scheme required to produce GNSS radio occultation refractivity climatologies is investigated. In a new, simplified retrieval approach, the main statistical analysis is performed in bending angle space and an estimate of the average bending angle profile is then propagated through an Abel transform. The average is composed of means and medians of ionospheric corrected bending angles up to 80 km. Above that, the observed profile is exponentially extrapolated to infinity using a fixed a priori scale height. The new approach circumvents the need to introduce a "statistical optimization" processing step in which individual bending-angle profiles are merged with a priori data, often taken from a climatology. This processing step can be complex, difficult to interpret, and is generally recognized as a potential source of structural uncertainty. The new scheme is 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. It is shown that the two GNSS radio occultation climatologies agree to within 0.1% from 5 km up to 35–40 km, for the three months January, February, and March 2011. During this time period, the new approach also produces slightly better agreement with ECMWF analyses between 40–50 km, which is encouraging. The possible limitations of the new approach caused by mean residual ionospheric errors and low observation numbers are discussed briefly, and areas for future work are suggested.

scholarly journals Global 3D Features of Error Variances of GPS Radio Occultation and Radiosonde Observations

2020 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Xu Xu ◽  
Xiaolei Zou
Keyword(s):  
Radio Occultation ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Error Variance ◽  
Specific Humidity ◽  
Temperature Error ◽  
Observation Error ◽  
Bending Angle ◽  
Gps Radio Occultation ◽  
Low Latitudes

Global Positioning System (GPS) radio occultation (RO) and radiosonde (RS) observations are two major types of observations assimilated in numerical weather prediction (NWP) systems. Observation error variances are required input that determines the weightings given to observations in data assimilation. This study estimates the error variances of global GPS RO refractivity and bending angle and RS temperature and humidity observations at 521 selected RS stations using the three-cornered hat method with additional ERA-Interim reanalysis and Global Forecast System forecast data available from 1 January 2016 to 31 August 2019. The global distributions, of both RO and RS observation error variances, are analyzed in terms of vertical and latitudinal variations. Error variances of RO refractivity and bending angle and RS specific humidity in the lower troposphere, such as at 850 hPa (3.5 km impact height for the bending angle), all increase with decreasing latitude. The error variances of RO refractivity and bending angle and RS specific humidity can reach about 30 N-unit2, 3 × 10−6 rad2, and 2 (g kg−1)2, respectively. There is also a good symmetry of the error variances of both RO refractivity and bending angle with respect to the equator between the Northern and Southern Hemispheres at all vertical levels. In this study, we provide the mean error variances of refractivity and bending angle in every 5°-latitude band between the equator and 60°N, as well as every interval of 10 hPa pressure or 0.2 km impact height. The RS temperature error variance distribution differs from those of refractivity, bending angle, and humidity, which, at low latitudes, are smaller (less than 1 K2) than those in the midlatitudes (more than 3 K2). In the midlatitudes, the RS temperature error variances in North America are larger than those in East Asia and Europe, which may arise from different radiosonde types among the above three regions.

scholarly journals Retrieval of temperature and water vapor profiles from radio occultation refractivity and bending angle measurements using an Optimal Estimation approach: a simulation study

2005 ◽  
Vol 5 (6) ◽  
pp. 1665-1677 ◽  
Author(s):  
A. von Engeln ◽  
G. Nedoluha
Keyword(s):  
Water Vapor ◽  
Radio Occultation ◽  
A Priori ◽  
Estimation Method ◽  
Lower Troposphere ◽  
Optimal Estimation ◽  
Pronounced Difference ◽  
Bending Angle ◽  
Advantages And Disadvantages ◽  
The Impact

Abstract. The Optimal Estimation Method is used to retrieve temperature and water vapor profiles from simulated radio occultation measurements in order to assess how different retrieval schemes may affect the assimilation of this data. High resolution ECMWF global fields are used by a state-of-the-art radio occultation simulator to provide quasi-realistic bending angle and refractivity profiles. Both types of profiles are used in the retrieval process to assess their advantages and disadvantages. The impact of the GPS measurement is expressed as an improvement over the a priori knowledge (taken from a 24h old analysis). Large improvements are found for temperature in the upper troposphere and lower stratosphere. Only very small improvements are found in the lower troposphere, where water vapor is present. Water vapor improvements are only significant between about 1 km to 7 km. No pronounced difference is found between retrievals based upon bending angles or refractivity. Results are compared to idealized retrievals, where the atmosphere is spherically symmetric and instrument noise is not included. Comparing idealized to quasi-realistic calculations shows that the main impact of a ray tracing algorithm can be expected for low latitude water vapor, where the horizontal variability is high. We also address the effect of altitude correlations in the temperature and water vapor. Overall, we find that water vapor and temperature retrievals using bending angle profiles are more CPU intensive than refractivity profiles, but that they do not provide significantly better results.

Characterizing Ionospheric Effect on GNSS Radio Occultation Atmospheric Bending Angle

2020 ◽  
Vol 125 (6) ◽  
Author(s):  
Mingzhe Li ◽  
Xinan Yue ◽  
Weixing Wan ◽  
William S. Schreiner
Keyword(s):  
Radio Occultation ◽  
Ionospheric Effect ◽  
Bending Angle

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.

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