An Abel transform for deriving line‐of‐sight wind profiles from LEO‐LEO infrared laser occultation measurements

Syndergaard, Stig; Kirchengast, Gottfried

doi:10.1002/2015jd023535

Cited by 12 publications

(8 citation statements)

References 43 publications

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“…We calculate the transform matrix of the Abel integral A Abl using the first-order solution of the powerful piecewise analytical rule recently developed by Syndergaard and Kirchengast [2016],…”

Section: A2 Refractivity Retrievalmentioning

confidence: 99%

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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Section: A2 Refractivity Retrievalmentioning

confidence: 99%

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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“…, a is the Earth's equatorial radius of 6 378.1370 km, and b is the Earth's polar radius of 6 356.7523 km (WGS84, World Geodetic System, 1984). Furthermore, we study the formulation of Earth's Gaussian radius of curvature at latitude ϕ (Torge, 2001):…”

Section: Wegc Implementationmentioning

confidence: 99%

Response to referee #2

Danzer¹

2018

Preprint

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Global Navigation Satellite System (GNSS) radio occultation (RO) data enable the retrieval of near-vertical profiles of atmospheric parameters like bending angle, refractivity, pressure, and temperature. The retrieval step from bending angle to refractivity, however, involves an Abel integral with an upper limit of infinity. RO data are practically limited to altitudes below about 80 km and the observed bending angle profiles show decreasing signal-to-noise ratio with increasing altitude. Some kind of high-altitude background data are therefore needed in order to perform this retrieval step (this approach is known as high-altitude initialization). Any bias in the background data will affect all RO data products beyond bending angle. A reduction of the influence of the background is therefore desirable-in particular for climate applications. Recently a new approach for the production of GNSS radio occultation climatologies has been proposed. The idea is to perform the averaging of individual profiles in bending angle space and then propagate the mean bending angle profiles through the Abel transform. Climatological products of refractivity, density, pressure, and temperature are directly retrieved from the mean bending angles. The averaging of a large number of profiles suppresses noise in the data, enabling observed bending angle data to be used up to 80 km without the need for a priori information. Some background information for the Abel integral is still necessary above 80 km. This work is a follow-up study, having the focus on the comparison of the average profile inversion climatologies (API) from the two processing centers WEGC and DMI, which study monthly COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) data from January to March 2011. The impact of different backgrounds above 80 km is tested, and different implementations of the Abel integral are investigated. Results are compared for the climatological products with ECMWF analyses, MIPAS, and SABER data. It is shown that different implementations of the Abel integral have little impact on the API climatologies. On the other hand, different extrapolations of the bending angle profile above 80 km play a key role in the resulting monthly mean refractivities above 35 km in altitude. Below that respective altitude the API climatologies show a good agreement between the two processing centers WEGC and DMI. Due to the downward propagation within the retrieval, effects of the high-altitude initialization lead to differences in dry-temperature climatologies down to 20 km in altitude. When applying an exponential extrapolation to the bending angles above 80 km at both centers, the dry-temperature climatologies agree among WEGC, DMI, ECMWF analysis, and MIPAS up to 35 km in altitude within ± 0.5 K and up to 40 km in altitude within ±1 K. We conclude that the API retrieval is a valid approach up to the lower stratosphere. It is a computationally efficient alternative method for producing dry atmospheric RO climatologies.

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“…After that each bending angle profile is statistically optimized using an ECMWF 5 short-range bias corrected forecast as background profile (Li et al, 2013(Li et al, , 2015. As a next step the refractivity is calculated, applying the method described in Appendix B in Syndergaard and Kirchengast (2016) and a linear combination inbetween (Gleisner and Healy, 2013). Together with the average bending angles, the average radii of curvature are built, where we test three different implementations of mean R c (see Eq.…”

Section: Wegc Implementationmentioning

confidence: 99%

“…When data and background are combined by statistical optimization, the observations are inversely weighted with the measurement error. A bias in the background profile will result in a bias in the retrieved profile down to an 20 altitude that depends on the noise of the data. The hydrostatic integral in the retrieval step from density to pressure will lead to a further downward propagation of potential biases in background data.…”

Section: Introductionmentioning

confidence: 99%

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Comparison study of COSMIC RO dry air climatologies based on average profile inversion

Danzer¹,

Schwärz²,

Proschek³

et al. 2018

Preprint

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Abstract.Recently a new approach for the production of GNSS radio occultation climatologies has been proposed. The idea is to perform the averaging of individual profiles already in bending angle space and propagating the mean bending angle profiles through the Abel transform. Climatological products of refractivity, density, pressure, and temperature are directly retrieved from the mean bending angles. 5The averaging of a large number of profiles suppresses noise in the data, enabling observed bending angle data to be used up to 80 km without the need of a priori information. Above that altitude some background information for the Abel integral is still necessary.This work is a follow up study, having the focus on the comparison of the average profile inversion climatologies (API) from the two processing centers WEGC and DMI, studying monthly COSMIC data from January to March 2011. The impact of between the two processing centers WEGC and DMI. Due to the downward propagation within the retrieval, effects of the upper initialization lead to differences in dry temperature climatologies already at 20 km altitude.Applying at both centers an exponential extrapolation to the bending angles above 80 km, dry temperature climatologies agree between WEGC, DMI, ECMWF analysis, and MIPAS up to 35 km altitude within ±0.5 K, and up to 40 km altitude within ±1 K. We conclude that up to the lower stratosphere the average profile inversion is a valid -and in computation time 20 much faster -alternative for the production of dry atmospheric RO climatologies.

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An Abel transform for deriving line‐of‐sight wind profiles from LEO‐LEO infrared laser occultation measurements

Cited by 12 publications

References 43 publications

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

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

Response to referee #2

Comparison study of COSMIC RO dry air climatologies based on average profile inversion

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