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Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI

Strandgren, Johan and Fricker, Jennifer and Bugliaro Goggia, Luca (2017) Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI. Atmospheric Measurement Techniques (AMT), 10 (11), pp. 4317-4339. Copernicus Publications. DOI: 10.5194/amt-10-4317-2017 ISSN 1867-1381

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Official URL: http://dx.doi.org/10.5194/amt-10-4317-2017

Abstract

We characterise the the performance of a set of artificial neural networks used for the remote sensing of cirrus clouds from the geostationary Meteosat Second Generation satellites. The retrievals show little interference with the underlying land surface type as well as with possible liquid water clouds or aerosol layers below the cirrus cloud. We also characterise the retrievals as a funtion of optical thickness and top height and gain better understanding of the retrival uncertainties of CiPS

Item URL in elib:https://elib.dlr.de/115377/
Document Type:Article
Title:Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Strandgren, Johandlr, ipahttps://orcid.org/0000-0001-7876-5845
Fricker, JenniferDLR, IPAUNSPECIFIED
Bugliaro Goggia, LucaDLR, IPAhttps://orcid.org/0000-0003-4793-0101
Date:14 November 2017
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:10
DOI :10.5194/amt-10-4317-2017
Page Range:pp. 4317-4339
Publisher:Copernicus Publications
ISSN:1867-1381
Status:Published
Keywords:Cirrus clouds, remote sensing, characterisation, neural networks, MSG/SEVIRI
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Atmosphären- und Klimaforschung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Atmospheric Remote Sensing
Deposited By: Strandgren, Johan
Deposited On:15 Nov 2017 09:57
Last Modified:08 Mar 2018 18:10

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