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...

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Published in:Atmospheric Measurement Techniques
Main Authors: Ehrlich, André, Bierwirth, Eike, Istomina, Larysa, Wendisch, Manfred
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:https://doi.org/10.5194/amt-10-3215-2017
https://amt.copernicus.org/articles/10/3215/2017/
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spelling ftcopernicus:oai:publications.copernicus.org:amt57421 2023-05-15T13:12:00+02:00 Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing Ehrlich, André Bierwirth, Eike Istomina, Larysa Wendisch, Manfred 2018-09-07 application/pdf https://doi.org/10.5194/amt-10-3215-2017 https://amt.copernicus.org/articles/10/3215/2017/ eng eng doi:10.5194/amt-10-3215-2017 https://amt.copernicus.org/articles/10/3215/2017/ eISSN: 1867-8548 Text 2018 ftcopernicus https://doi.org/10.5194/amt-10-3215-2017 2020-07-20T16:23:37Z 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 transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ , and low r eff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated. Text albedo Arctic Beaufort Sea Sea ice Copernicus Publications: E-Journals Arctic Atmospheric Measurement Techniques 10 9 3215 3230
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
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 transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ , and low r eff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.
format Text
author Ehrlich, André
Bierwirth, Eike
Istomina, Larysa
Wendisch, Manfred
spellingShingle Ehrlich, André
Bierwirth, Eike
Istomina, Larysa
Wendisch, Manfred
Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing
author_facet Ehrlich, André
Bierwirth, Eike
Istomina, Larysa
Wendisch, Manfred
author_sort Ehrlich, André
title 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_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_sort combined retrieval of arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing
publishDate 2018
url https://doi.org/10.5194/amt-10-3215-2017
https://amt.copernicus.org/articles/10/3215/2017/
geographic Arctic
geographic_facet Arctic
genre albedo
Arctic
Beaufort Sea
Sea ice
genre_facet albedo
Arctic
Beaufort Sea
Sea ice
op_source eISSN: 1867-8548
op_relation doi:10.5194/amt-10-3215-2017
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container_title Atmospheric Measurement Techniques
container_volume 10
container_issue 9
container_start_page 3215
op_container_end_page 3230
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