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Retrieval of cloud properties from EPIC/DSCOVR

Molina García, Víctor (2023) Retrieval of cloud properties from EPIC/DSCOVR. Dissertation, Technical University of Munich.

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Official URL: https://mediatum.ub.tum.de/1662361

Abstract

This dissertation provides a framework for retrieving cloud macrophysical properties from radiance measurements acquired by the EPIC instrument. It analyses the involved pre-processing steps (registration and degradation correction), speed-up improvements in the radiative transfer model, the determination of the cloud fraction with the OCRA algorithm, and the sensitivity analysis of the ROCINN algorithm to obtain cloud optical thickness and cloud-top height under several sources of uncertainty.

Item URL in elib:https://elib.dlr.de/194303/
Document Type:Thesis (Dissertation)
Title:Retrieval of cloud properties from EPIC/DSCOVR
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Molina García, VíctorVictor.MolinaGarcia (at) dlr.dehttps://orcid.org/0000-0002-2564-5396UNSPECIFIED
Date:5 January 2023
Journal or Publication Title:mediaTUM
Refereed publication:No
Open Access:Yes
Number of Pages:185
Status:Published
Keywords:radiative transfer, neural networks, machine learning, OCRA, ROCINN
Institution:Technical University of Munich
Department:School of Engineering and Design
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, R - Optical remote sensing, R - Artificial Intelligence
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Molina García, Víctor
Deposited On:15 Mar 2023 10:32
Last Modified:15 Mar 2023 10:32

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