A New Approach to Inverting and De-Noising Backscatter from Lidar Observations
Atmospheric lidar observations provide a unique capability to directly observe the vertical profile of cloud and aerosol scattering properties and have proven to be an important capability for the atmospheric science community. For this reason NASA and ESA have put a major emphasis on developing bot...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2016-01-01
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| Series: | EPJ Web of Conferences |
| Online Access: | http://dx.doi.org/10.1051/epjconf/201611925004 |
| _version_ | 1818618272034062336 |
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| author | Marais Willem Hu Yu Hen Holz Robert Eloranta Edwin |
| author_facet | Marais Willem Hu Yu Hen Holz Robert Eloranta Edwin |
| author_sort | Marais Willem |
| collection | DOAJ |
| description | Atmospheric lidar observations provide a unique capability to directly observe the vertical profile of cloud and aerosol scattering properties and have proven to be an important capability for the atmospheric science community. For this reason NASA and ESA have put a major emphasis on developing both space and ground based lidar instruments. Measurement noise (solar background and detector noise) has proven to be a significant limitation and is typically reduced by temporal and vertical averaging. This approach has significant limitations as it results in significant reduction in the spatial information and can introduce biases due to the non-linear relationship between the signal and the retrieved scattering properties. This paper investigates a new approach to de-noising and retrieving cloud and aerosol backscatter properties from lidar observations that leverages a technique developed for medical imaging to de-blur and de-noise images; the accuracy is defined as the error between the true and inverted photon rates. Hence non-linear bias errors can be mitigated and spatial information can be preserved. |
| first_indexed | 2024-12-16T17:18:57Z |
| format | Article |
| id | doaj.art-3d023f6052894a1280b660373e38a5aa |
| institution | Directory Open Access Journal |
| issn | 2100-014X |
| language | English |
| last_indexed | 2024-12-16T17:18:57Z |
| publishDate | 2016-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | EPJ Web of Conferences |
| spelling | doaj.art-3d023f6052894a1280b660373e38a5aa2022-12-21T22:23:13ZengEDP SciencesEPJ Web of Conferences2100-014X2016-01-011192500410.1051/epjconf/201611925004epjconf_ilrc2016_25004A New Approach to Inverting and De-Noising Backscatter from Lidar ObservationsMarais Willem0Hu Yu Hen1Holz Robert2Eloranta Edwin3Department of Electrical and Computer Engineering, University of Wisconsin-MadisonDepartment of Electrical and Computer Engineering, University of Wisconsin-MadisonCooperative Institute for Meteorological Satellite Studies, University of Wisconsin-MadisonSpace Science Engineering Center, University of Wisconsin-MadisonAtmospheric lidar observations provide a unique capability to directly observe the vertical profile of cloud and aerosol scattering properties and have proven to be an important capability for the atmospheric science community. For this reason NASA and ESA have put a major emphasis on developing both space and ground based lidar instruments. Measurement noise (solar background and detector noise) has proven to be a significant limitation and is typically reduced by temporal and vertical averaging. This approach has significant limitations as it results in significant reduction in the spatial information and can introduce biases due to the non-linear relationship between the signal and the retrieved scattering properties. This paper investigates a new approach to de-noising and retrieving cloud and aerosol backscatter properties from lidar observations that leverages a technique developed for medical imaging to de-blur and de-noise images; the accuracy is defined as the error between the true and inverted photon rates. Hence non-linear bias errors can be mitigated and spatial information can be preserved.http://dx.doi.org/10.1051/epjconf/201611925004 |
| spellingShingle | Marais Willem Hu Yu Hen Holz Robert Eloranta Edwin A New Approach to Inverting and De-Noising Backscatter from Lidar Observations EPJ Web of Conferences |
| title | A New Approach to Inverting and De-Noising Backscatter from Lidar Observations |
| title_full | A New Approach to Inverting and De-Noising Backscatter from Lidar Observations |
| title_fullStr | A New Approach to Inverting and De-Noising Backscatter from Lidar Observations |
| title_full_unstemmed | A New Approach to Inverting and De-Noising Backscatter from Lidar Observations |
| title_short | A New Approach to Inverting and De-Noising Backscatter from Lidar Observations |
| title_sort | new approach to inverting and de noising backscatter from lidar observations |
| url | http://dx.doi.org/10.1051/epjconf/201611925004 |
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