A methodology for simultaneous retrieval ...
Document type :
Article dans une revue scientifique: Article original
DOI :
Permalink :
Title :
A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part I: Information content and case study
Author(s) :
Sourdeval, Odran [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Leipziger Institut für Meteorologie [LIM]
Couillard Labonnotte, Laurent [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Baran, Anthony J. [Auteur]
Brogniez, Gerard [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Leipziger Institut für Meteorologie [LIM]
Couillard Labonnotte, Laurent [Auteur]

Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Baran, Anthony J. [Auteur]
Brogniez, Gerard [Auteur]

Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Journal title :
Quarterly Journal of the Royal Meteorological Society
Abbreviated title :
Q.J.R. Meteorol. Soc.
Volume number :
141
Pages :
870-882
Publisher :
Wiley
Publication date :
2014-08-11
ISSN :
0035-9009
English keyword(s) :
ice cloud
information content
liquid water cloud
microphysics
multilayer
optimal estimation
remote sensing
satellite retrievals
information content
liquid water cloud
microphysics
multilayer
optimal estimation
remote sensing
satellite retrievals
HAL domain(s) :
Planète et Univers [physics]/Océan, Atmosphère
Planète et Univers [physics]/Sciences de la Terre/Climatologie
Planète et Univers [physics]/Sciences de la Terre/Météorologie
Physique [physics]/Physique [physics]/Physique Atmosphérique et Océanique [physics.ao-ph]
Planète et Univers [physics]/Sciences de la Terre/Climatologie
Planète et Univers [physics]/Sciences de la Terre/Météorologie
Physique [physics]/Physique [physics]/Physique Atmosphérique et Océanique [physics.ao-ph]
English abstract : [en]
This article presents a novel methodology dedicated to retrieving the optical and microphysical properties of ice and liquid water clouds simultaneously. An optimal estimation method is used to retrieve the ice water path ...
Show more >This article presents a novel methodology dedicated to retrieving the optical and microphysical properties of ice and liquid water clouds simultaneously. An optimal estimation method is used to retrieve the ice water path of one ice-cloud layer and the optical thickness and droplet effective radius of up to two liquid-water cloud layers, along with rigorous uncertainties. In order to perform the retrievals, radiometric measurements in five channels ranging from the visible to the thermal infrared are utilized. The position of cloud layers is currently provided by lidar information, which narrows the retrievals to its track. In the first part of this article, theoretical information content analyses are performed under different atmospheric conditions, over an oceanic surface. This type of analysis quantifies prior to the retrievals the amount of information that should be available regarding each parameter to be retrieved and helps to identify which set of channels provides this information. It is observed that strong information can be expected for retrieving each parameter in double-layer cases, while yet stronger limitations appear in triple-layer cases. In the second part of this article, our methodology is applied to a case study. In agreement with a priori expectations, accurate retrievals of ice and liquid cloud properties are obtained. These results are later compared with the products of a single-layer retrieval method, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) operational products and in situ estimates. We show that a much better consistency with the latter two is found when retrieving the properties of each layer simultaneously. However, further statistical analyses and comparisons with various operational products should be undertaken for validation of the methodology. Such results will be presented in the second part of this study.Show less >
Show more >This article presents a novel methodology dedicated to retrieving the optical and microphysical properties of ice and liquid water clouds simultaneously. An optimal estimation method is used to retrieve the ice water path of one ice-cloud layer and the optical thickness and droplet effective radius of up to two liquid-water cloud layers, along with rigorous uncertainties. In order to perform the retrievals, radiometric measurements in five channels ranging from the visible to the thermal infrared are utilized. The position of cloud layers is currently provided by lidar information, which narrows the retrievals to its track. In the first part of this article, theoretical information content analyses are performed under different atmospheric conditions, over an oceanic surface. This type of analysis quantifies prior to the retrievals the amount of information that should be available regarding each parameter to be retrieved and helps to identify which set of channels provides this information. It is observed that strong information can be expected for retrieving each parameter in double-layer cases, while yet stronger limitations appear in triple-layer cases. In the second part of this article, our methodology is applied to a case study. In agreement with a priori expectations, accurate retrievals of ice and liquid cloud properties are obtained. These results are later compared with the products of a single-layer retrieval method, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) operational products and in situ estimates. We show that a much better consistency with the latter two is found when retrieving the properties of each layer simultaneously. However, further statistical analyses and comparisons with various operational products should be undertaken for validation of the methodology. Such results will be presented in the second part of this study.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CNRS
CNRS
Collections :
Research team(s) :
Interactions Rayonnement Nuages (IRN)
Submission date :
2023-01-06T14:19:14Z
2023-01-12T17:21:01Z
2023-01-12T17:21:01Z
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