Sensitivity of liquid cloud optical thickness and effective radius retrievals to cloud bow and glory conditions using two SEVIRI imagers
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Published:2019-05-23
Issue:5
Volume:12
Page:2863-2879
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ISSN:1867-8548
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Container-title:Atmospheric Measurement Techniques
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language:en
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Short-container-title:Atmos. Meas. Tech.
Author:
Benas NikosORCID, Meirink Jan FokkeORCID, Stengel MartinORCID, Stammes Piet
Abstract
Abstract. Retrievals of cloud properties from geostationary
satellite sensors offer extensive spatial and temporal coverage and
resolution. The high temporal resolution allows the observation of diurnally
resolved cloud properties. However, retrievals are sensitive to varying
illumination and viewing geometries, including cloud glory and cloud bow
conditions, which can lead to irregularities in the diurnal data record. In
this study, these conditions and their effects on liquid cloud optical
thickness and effective radius retrievals are analyzed using the Cloud
Physical Properties (CPP) algorithm. This analysis is based on the use of
Spinning Enhanced Visible
and Infrared Imager (SEVIRI) reflectances and products from Meteosat-8 and Meteosat-10, which are located
over the Indian and Atlantic Ocean, respectively, and cover an extensive
common area under different viewing angles. Comparisons of the retrievals
from two full days, over ocean and land, and using different spectral
combinations of visible and shortwave-infrared channels, are performed, to
assess the importance of these factors in the retrieval process. The
sensitivity of the cloud-bow- and cloud-glory-related irregularities to the width
of the assumed droplet size distribution is analyzed by using different
values of the effective variance of the size distribution. The results
suggest for marine stratocumulus clouds an effective variance of around
0.05, which implies a narrower size distribution than typically assumed in
satellite-based retrievals. For the case with continental clouds a broader
size distribution (effective variance around 0.15) is obtained. This
highlights the importance of appropriate size distribution assumptions and
provides a way to improve the quality of cloud products in future climate
data record releases.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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