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Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides - Part 1: Retrieval development and characterization

Ewald, Florian and Zinner, Tobias and Kölling, Tobias and Mayer, Bernhard (2019) Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides - Part 1: Retrieval development and characterization. Atmospheric Measurement Techniques (AMT), 12 (2), pp. 1183-1206. Copernicus Publications. doi: 10.5194/amt-12-1183-2019. ISSN 1867-1381.

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Official URL: http://dx.doi.org/10.5194/amt-12-1183-2019

Abstract

Convective clouds play an essential role for Earth's climate as well as for regional weather events since they have a large influence on the radiation budget and the water cycle. In particular, cloud albedo and the formation of precipitation are influenced by aerosol particles within clouds. In order to improve the understanding of processes from aerosol activation, from cloud droplet growth to changes in cloud radiative properties, remote sensing techniques become more and more important. While passive retrievals for spaceborne observations have become sophisticated and commonplace for inferring cloud optical thickness and droplet size from cloud tops, profiles of droplet size have remained largely uncharted territory for passive remote sensing. In principle they could be derived from observations of cloud sides, but faced with the small-scale heterogeneity of cloud sides, "classical" passive remote sensing techniques are rendered inappropriate. In this work the feasibility is demonstrated to gain new insights into the vertical evolution of cloud droplet effective radius by using reflected solar radiation from cloud sides. Central aspect of this work on its path to a working cloud side retrieval is the analysis of the impact unknown cloud surface geometry has on effective radius retrievals. This study examines the sensitivity of reflected solar radiation to cloud droplet size, using extensive 3-D radiative transfer calculations on the basis of realistic droplet size resolving cloud simulations. Furthermore, it explores a further technique to resolve ambiguities caused by illumination and cloud geometry by considering the surroundings of each pixel. Based on these findings, a statistical approach is used to provide an effective radius retrieval. This statistical effective radius retrieval is focused on the liquid part of convective water clouds, e.g., cumulus mediocris, cumulus congestus, and trade-wind cumulus, which exhibit well-developed cloud sides. Finally, the developed retrieval is tested using known and unknown cloud side scenes to analyze its performance.

Item URL in elib:https://elib.dlr.de/127117/
Document Type:Article
Title:Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides - Part 1: Retrieval development and characterization
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Ewald, FlorianDLR, IPAhttps://orcid.org/0000-0002-5899-0890UNSPECIFIED
Zinner, TobiasLMU, MünchenUNSPECIFIEDUNSPECIFIED
Kölling, TobiasLMU MünchenUNSPECIFIEDUNSPECIFIED
Mayer, BernhardLMU, MünchenUNSPECIFIEDUNSPECIFIED
Date:25 February 2019
Journal or Publication Title:Atmospheric Measurement Techniques (AMT)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:12
DOI:10.5194/amt-12-1183-2019
Page Range:pp. 1183-1206
Editors:
EditorsEmailEditor's ORCID iDORCID Put Code
Kokhanovsky, AlexanderUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Publisher:Copernicus Publications
ISSN:1867-1381
Status:Published
Keywords:Cloud side remote sensing, effective radius retrieval, 3D radiative effects
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Atmospheric and climate research
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Lidar
Deposited By: Ewald, Dr. Florian
Deposited On:09 Apr 2019 12:23
Last Modified:21 Nov 2023 13:39

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