Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques

In this work, we revise the retrieval of extinction coefficient profiles from Raman Lidar. This is an ill-posed problem, and we show that methods like Levenberg–Marquardt or Tikhonov–Phillips can be applied. We test these methods for a synthetic Lidar profile (known solution) with different noise realizations. Further, we apply these methods to three different cases of data from the Arctic: under daylight (Arctic Haze), under daylight with a high and vertically extended aerosol layer, and at nighttime with high extinction. We show that our methods work and allow a trustful derivation of extinction up to clearly higher altitudes (at about half a signal-to-noise ratio) compared with the traditional, non-regularized Ansmann solution. However, these new methods are not trivial and require a choice of parameters, which depend on the noise of the data. As the Lidar signal quality quickly decreases with range, a separation of the profile into several sub-intervals seems beneficial.

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Publication Details

Journal
Remote Sensing
Published
2025-02-27
DOI
https://doi.org/10.3390/rs17050841
Citations
1
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
1.11
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article

Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques

Sandra Graßl, Christine Böckmann, Christoph Ritter, Richard Herrmann
1 citations
Remote Sensing
Atmospheric aerosols and clouds
1.11
article

Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques

Sandra Graßl, Christine Böckmann, Christoph Ritter, Richard Herrmann
article en
1 citations

Abstract

In this work, we revise the retrieval of extinction coefficient profiles from Raman Lidar. This is an ill-posed problem, and we show that methods like Levenberg–Marquardt or Tikhonov–Phillips can be applied. We test these methods for a synthetic Lidar profile (known solution) with different noise realizations. Further, we apply these methods to three different cases of data from the Arctic: under daylight (Arctic Haze), under daylight with a high and vertically extended aerosol layer, and at nighttime with high extinction. We show that our methods work and allow a trustful derivation of extinction up to clearly higher altitudes (at about half a signal-to-noise ratio) compared with the traditional, non-regularized Ansmann solution. However, these new methods are not trivial and require a choice of parameters, which depend on the noise of the data. As the Lidar signal quality quickly decreases with range, a separation of the profile into several sub-intervals seems beneficial.

Remote SensingVol. 17(5)
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), University of Potsdam (DE)
Openalex Percentile: Top 27%
Atmospheric aerosols and clouds
1.11
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