Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing
The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effectiv...
Published in: | Atmospheric Measurement Techniques |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2017
|
Subjects: | |
Online Access: | https://doi.org/10.5194/amt-10-3215-2017 https://doaj.org/article/4addfefbe6f24689a1664d331388461f |
_version_ | 1821756591024635904 |
---|---|
author | A. Ehrlich E. Bierwirth L. Istomina M. Wendisch |
author_facet | A. Ehrlich E. Bierwirth L. Istomina M. Wendisch |
author_sort | A. Ehrlich |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 9 |
container_start_page | 3215 |
container_title | Atmospheric Measurement Techniques |
container_volume | 10 |
description | The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius r eff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size r eff, S . Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and r eff, C for liquid water clouds. In general, the impact of uncertainties of r eff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved r eff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for r eff, C . In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters ( τ , r eff, C , r eff, S ) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ 1 = 1040 nm (sensitive to r eff, S ), λ 2 = 1650 nm (sensitive to τ ), and λ 3 = 2100 nm (sensitive to r eff, C ) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ , r eff, C , and r eff, S show a continuous ... |
format | Article in Journal/Newspaper |
genre | albedo Arctic Beaufort Sea Sea ice |
genre_facet | albedo Arctic Beaufort Sea Sea ice |
geographic | Arctic |
geographic_facet | Arctic |
id | ftdoajarticles:oai:doaj.org/article:4addfefbe6f24689a1664d331388461f |
institution | Open Polar |
language | English |
op_collection_id | ftdoajarticles |
op_container_end_page | 3230 |
op_doi | https://doi.org/10.5194/amt-10-3215-2017 |
op_relation | https://www.atmos-meas-tech.net/10/3215/2017/amt-10-3215-2017.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-10-3215-2017 1867-1381 1867-8548 https://doaj.org/article/4addfefbe6f24689a1664d331388461f |
op_source | Atmospheric Measurement Techniques, Vol 10, Pp 3215-3230 (2017) |
publishDate | 2017 |
publisher | Copernicus Publications |
record_format | openpolar |
spelling | ftdoajarticles:oai:doaj.org/article:4addfefbe6f24689a1664d331388461f 2025-01-16T18:43:40+00:00 Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing A. Ehrlich E. Bierwirth L. Istomina M. Wendisch 2017-09-01T00:00:00Z https://doi.org/10.5194/amt-10-3215-2017 https://doaj.org/article/4addfefbe6f24689a1664d331388461f EN eng Copernicus Publications https://www.atmos-meas-tech.net/10/3215/2017/amt-10-3215-2017.pdf https://doaj.org/toc/1867-1381 https://doaj.org/toc/1867-8548 doi:10.5194/amt-10-3215-2017 1867-1381 1867-8548 https://doaj.org/article/4addfefbe6f24689a1664d331388461f Atmospheric Measurement Techniques, Vol 10, Pp 3215-3230 (2017) Environmental engineering TA170-171 Earthwork. Foundations TA715-787 article 2017 ftdoajarticles https://doi.org/10.5194/amt-10-3215-2017 2022-12-30T23:17:08Z The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius r eff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size r eff, S . Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and r eff, C for liquid water clouds. In general, the impact of uncertainties of r eff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved r eff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for r eff, C . In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters ( τ , r eff, C , r eff, S ) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ 1 = 1040 nm (sensitive to r eff, S ), λ 2 = 1650 nm (sensitive to τ ), and λ 3 = 2100 nm (sensitive to r eff, C ) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ , r eff, C , and r eff, S show a continuous ... Article in Journal/Newspaper albedo Arctic Beaufort Sea Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Atmospheric Measurement Techniques 10 9 3215 3230 |
spellingShingle | Environmental engineering TA170-171 Earthwork. Foundations TA715-787 A. Ehrlich E. Bierwirth L. Istomina M. Wendisch Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
title | Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
title_full | Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
title_fullStr | Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
title_full_unstemmed | Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
title_short | Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
title_sort | combined retrieval of arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing |
topic | Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
topic_facet | Environmental engineering TA170-171 Earthwork. Foundations TA715-787 |
url | https://doi.org/10.5194/amt-10-3215-2017 https://doaj.org/article/4addfefbe6f24689a1664d331388461f |