Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model
Currently, no aerosol optical thickness (AOT) data set over the Arctic snow/ice-covered regions derived from space-borne passive remote sensing is available. The challenge is to develop an accurate and robust technique to derive AOT above highly variable and bright snow/ice surfaces. To extend data...
Published in: | IEEE Transactions on Geoscience and Remote Sensing |
---|---|
Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
2020
|
Subjects: | |
Online Access: | https://epic.awi.de/id/eprint/53135/ https://epic.awi.de/id/eprint/53135/1/Linlu_2020_retrieval_AOT.pdf https://doi.org/10.1109/TGRS.2020.2972339 https://hdl.handle.net/10013/epic.7ccdd46d-c055-4169-9580-63874ad18ea3 |
id |
ftawi:oai:epic.awi.de:53135 |
---|---|
record_format |
openpolar |
spelling |
ftawi:oai:epic.awi.de:53135 2024-09-15T17:35:14+00:00 Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model Mei, Linlu Rozanov, Vladimir Ritter, Christoph Heinold, Bernd Jiao, Ziti Vountas, Marco Burrows, John P. 2020 application/pdf https://epic.awi.de/id/eprint/53135/ https://epic.awi.de/id/eprint/53135/1/Linlu_2020_retrieval_AOT.pdf https://doi.org/10.1109/TGRS.2020.2972339 https://hdl.handle.net/10013/epic.7ccdd46d-c055-4169-9580-63874ad18ea3 unknown https://epic.awi.de/id/eprint/53135/1/Linlu_2020_retrieval_AOT.pdf Mei, L. , Rozanov, V. , Ritter, C. , Heinold, B. , Jiao, Z. , Vountas, M. and Burrows, J. P. (2020) Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model , IEEE Transactions on Geoscience and Remote Sensing, 58 (7), pp. 5117-5131 . doi:10.1109/TGRS.2020.2972339 <https://doi.org/10.1109/TGRS.2020.2972339> , hdl:10013/epic.7ccdd46d-c055-4169-9580-63874ad18ea3 EPIC3IEEE Transactions on Geoscience and Remote Sensing, 58(7), pp. 5117-5131, ISSN: 0196-2892 Article isiRev 2020 ftawi https://doi.org/10.1109/TGRS.2020.2972339 2024-06-24T04:26:11Z Currently, no aerosol optical thickness (AOT) data set over the Arctic snow/ice-covered regions derived from space-borne passive remote sensing is available. The challenge is to develop an accurate and robust technique to derive AOT above highly variable and bright snow/ice surfaces. To extend data coverage of the eXtensible Bremen Aerosol/cloud and surfacE Retrieval (XBAER) AOT data product in the future, we propose a new algorithm for the retrieval of AOT and surface properties over snow/ice simultaneously. The algorithm utilizes the linear perturbation theory and does not use any simplified atmospheric correction techniques. Key issues like the selection of a proper aerosol type and optimal surface parameterization method for the retrieval of AOT over the Arctic have been investigated. The aerosol type is investigated using the aerosol climatology microphysical properties derived from four Aerosol Robotic Network (AERONET) sites (Barrow, Hornsund, Kangerlussuaq, and Tiksi). The three-parametric Ross-Li linear kernel model is used to describe the snow bidirectional reflectance distribution function (BRDF). The a priori knowledge of wavelength-dependent features of the coefficients in the Ross-Li linear kernel model is derived from Polarization and Directionality of the Earth's Reflectances (POLDER) measurements over the Arctic and utilized as constraints in the retrieval. The studies show that the combination of Ross-Li surface model and weakly absorbing aerosol parameterization provides an optimal way to derive AOT over the Arctic snow/ice-covered regions from passive remote sensing observations. The retrieved AOTs using POLDER show good agreement with AERONET observations. Article in Journal/Newspaper Aerosol Robotic Network Arctic Hornsund Kangerlussuaq Tiksi Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) IEEE Transactions on Geoscience and Remote Sensing 58 7 5117 5131 |
institution |
Open Polar |
collection |
Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
op_collection_id |
ftawi |
language |
unknown |
description |
Currently, no aerosol optical thickness (AOT) data set over the Arctic snow/ice-covered regions derived from space-borne passive remote sensing is available. The challenge is to develop an accurate and robust technique to derive AOT above highly variable and bright snow/ice surfaces. To extend data coverage of the eXtensible Bremen Aerosol/cloud and surfacE Retrieval (XBAER) AOT data product in the future, we propose a new algorithm for the retrieval of AOT and surface properties over snow/ice simultaneously. The algorithm utilizes the linear perturbation theory and does not use any simplified atmospheric correction techniques. Key issues like the selection of a proper aerosol type and optimal surface parameterization method for the retrieval of AOT over the Arctic have been investigated. The aerosol type is investigated using the aerosol climatology microphysical properties derived from four Aerosol Robotic Network (AERONET) sites (Barrow, Hornsund, Kangerlussuaq, and Tiksi). The three-parametric Ross-Li linear kernel model is used to describe the snow bidirectional reflectance distribution function (BRDF). The a priori knowledge of wavelength-dependent features of the coefficients in the Ross-Li linear kernel model is derived from Polarization and Directionality of the Earth's Reflectances (POLDER) measurements over the Arctic and utilized as constraints in the retrieval. The studies show that the combination of Ross-Li surface model and weakly absorbing aerosol parameterization provides an optimal way to derive AOT over the Arctic snow/ice-covered regions from passive remote sensing observations. The retrieved AOTs using POLDER show good agreement with AERONET observations. |
format |
Article in Journal/Newspaper |
author |
Mei, Linlu Rozanov, Vladimir Ritter, Christoph Heinold, Bernd Jiao, Ziti Vountas, Marco Burrows, John P. |
spellingShingle |
Mei, Linlu Rozanov, Vladimir Ritter, Christoph Heinold, Bernd Jiao, Ziti Vountas, Marco Burrows, John P. Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model |
author_facet |
Mei, Linlu Rozanov, Vladimir Ritter, Christoph Heinold, Bernd Jiao, Ziti Vountas, Marco Burrows, John P. |
author_sort |
Mei, Linlu |
title |
Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model |
title_short |
Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model |
title_full |
Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model |
title_fullStr |
Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model |
title_full_unstemmed |
Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model |
title_sort |
retrieval of aerosol optical thickness in the arctic snow-covered regions using passive remote sensing: impact of aerosol typing and surface reflection model |
publishDate |
2020 |
url |
https://epic.awi.de/id/eprint/53135/ https://epic.awi.de/id/eprint/53135/1/Linlu_2020_retrieval_AOT.pdf https://doi.org/10.1109/TGRS.2020.2972339 https://hdl.handle.net/10013/epic.7ccdd46d-c055-4169-9580-63874ad18ea3 |
genre |
Aerosol Robotic Network Arctic Hornsund Kangerlussuaq Tiksi |
genre_facet |
Aerosol Robotic Network Arctic Hornsund Kangerlussuaq Tiksi |
op_source |
EPIC3IEEE Transactions on Geoscience and Remote Sensing, 58(7), pp. 5117-5131, ISSN: 0196-2892 |
op_relation |
https://epic.awi.de/id/eprint/53135/1/Linlu_2020_retrieval_AOT.pdf Mei, L. , Rozanov, V. , Ritter, C. , Heinold, B. , Jiao, Z. , Vountas, M. and Burrows, J. P. (2020) Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model , IEEE Transactions on Geoscience and Remote Sensing, 58 (7), pp. 5117-5131 . doi:10.1109/TGRS.2020.2972339 <https://doi.org/10.1109/TGRS.2020.2972339> , hdl:10013/epic.7ccdd46d-c055-4169-9580-63874ad18ea3 |
op_doi |
https://doi.org/10.1109/TGRS.2020.2972339 |
container_title |
IEEE Transactions on Geoscience and Remote Sensing |
container_volume |
58 |
container_issue |
7 |
container_start_page |
5117 |
op_container_end_page |
5131 |
_version_ |
1810446065632018432 |