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 re...
Published in: | Remote Sensing |
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Main Authors: | , , , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2025
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Subjects: | |
Online Access: | https://doi.org/10.3390/rs17050841 |
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author | Richard Matthias Herrmann Christoph Ritter Christine Böckmann Sandra Graßl |
author_facet | Richard Matthias Herrmann Christoph Ritter Christine Böckmann Sandra Graßl |
author_sort | Richard Matthias Herrmann |
collection | MDPI Open Access Publishing |
container_issue | 5 |
container_start_page | 841 |
container_title | Remote Sensing |
container_volume | 17 |
description | 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. |
format | Text |
genre | Arctic |
genre_facet | Arctic |
geographic | Arctic |
geographic_facet | Arctic |
id | ftmdpi:oai:mdpi.com:/2072-4292/17/5/841/ |
institution | Open Polar |
language | English |
op_collection_id | ftmdpi |
op_coverage | agris |
op_doi | https://doi.org/10.3390/rs17050841 |
op_relation | https://dx.doi.org/10.3390/rs17050841 |
op_rights | https://creativecommons.org/licenses/by/4.0/ |
op_source | Remote Sensing Volume 17 Issue 5 Pages: 841 |
publishDate | 2025 |
publisher | Multidisciplinary Digital Publishing Institute |
record_format | openpolar |
spelling | ftmdpi:oai:mdpi.com:/2072-4292/17/5/841/ 2025-03-30T15:03:23+00:00 Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques Richard Matthias Herrmann Christoph Ritter Christine Böckmann Sandra Graßl agris 2025-02-27 application/pdf https://doi.org/10.3390/rs17050841 eng eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs17050841 https://creativecommons.org/licenses/by/4.0/ Remote Sensing Volume 17 Issue 5 Pages: 841 Raman Lidar aerosols extinction coefficient profile retrieval regularization Text 2025 ftmdpi https://doi.org/10.3390/rs17050841 2025-03-03T15:30:51Z 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. Text Arctic MDPI Open Access Publishing Arctic Remote Sensing 17 5 841 |
spellingShingle | Raman Lidar aerosols extinction coefficient profile retrieval regularization Richard Matthias Herrmann Christoph Ritter Christine Böckmann Sandra Graßl Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques |
title | Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques |
title_full | Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques |
title_fullStr | Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques |
title_full_unstemmed | Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques |
title_short | Improved Method for the Retrieval of Extinction Coefficient Profile by Regularization Techniques |
title_sort | improved method for the retrieval of extinction coefficient profile by regularization techniques |
topic | Raman Lidar aerosols extinction coefficient profile retrieval regularization |
topic_facet | Raman Lidar aerosols extinction coefficient profile retrieval regularization |
url | https://doi.org/10.3390/rs17050841 |