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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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doi:10.5194/amt-2017-50
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
14 Mar 2017
Review status
This discussion paper is under review for the journal Atmospheric Measurement Techniques (AMT).
Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing
André Ehrlich1, Eike Bierwirth1,a, Larysa Istomina2, and Manfred Wendisch1 1Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
2Institute of Environmental Physics, University of Bremen, Bremen, Germany
anow at: PIER-ELECTRONIC GmbH, Nassaustr. 33-35, 65719 Hofheim-Wallau, Germany
Abstract. In the Arctic, the passive solar remote sensing of cloud properties over highly reflecting ground is challenging due to the low contrast between the clouds and underlying surfaces (sea ice and snow). Uncertainties in retrieved cloud optical thickness τ and cloud droplet effective radius reff,C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the commonly unknown snow effective grain size reff,S. Therefore, in a first step this snow grain size effect is quantified systematically for a conventional bi-spectral retrieval of τ and reff,C for liquid water clouds. The largest impact of reff,S of up to 83 % on τ and 62 % on reff,C was found in case of small reff,S and optically thin clouds.

In the second part of the paper a retrieval method is presented that simultaneously retrieves all three parameters (τ, reff,C, reff,S) in order to account for changes of the snow grain size in the cloud retrieval algorithm. Spectral cloud reflectivities at the three wavelength λ1 = 1040 nm (sensitive to reff,S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff,C) were normalized to reflectivity ratios and combined in a tri-spectral retrieval algorithm. Measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART-Albedometer) 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 sea ice edge were analyzed. The retrieved values of τ, reff,C, and reff,S consistently represented the cloud properties across this transition from snow-covered sea ice to the open water and were comparable to estimates based on satellite data. Analysis showed, that the uncertainties of the tri-spectral retrieval increase for high τ, and low reff,S, but nevertheless allows a simultaneous retrieval of cloud and surface snow properties providing snow effective grain size estimates in cloud-covered areas.


Citation: Ehrlich, A., Bierwirth, E., Istomina, L., and Wendisch, M.: Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2017-50, in review, 2017.
André Ehrlich et al.
André Ehrlich et al.
André Ehrlich et al.

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Short summary
In the Arctic, uncertainties in passive solar remote sensing of cloud properties arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the commonly unknown snow effective grain size. Therefore, a retrieval method is presented that simultaneously retrieves liquid water cloud and snow surface parameters, including cloud optical thickness, droplet effective radius and snow effective grain size. Airborne measurements were used to test the retrieval procedure.
In the Arctic, uncertainties in passive solar remote sensing of cloud properties arise from...
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