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Inversion Models for the Retrieval of Total and Tropospheric NO2 Columns

Liu, Song (2019) Inversion Models for the Retrieval of Total and Tropospheric NO2 Columns. Atmosphere, 10 (10), pp. 1-21. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/atmos10100607. ISSN 2073-4433.

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Official URL: https://doi.org/10.3390/atmos10100607


Inversion models for retrieving the total and tropospheric nitrogen dioxide ( NO2 ) columns from spaceborne remote sensing data are presented. For total column retrieval, we propose the so-called differential radiance models with internal and external closure and solve the underlying nonlinear equations by using the method of Tikhonov regularization and the iteratively regularized Gauss–Newton method. For tropospheric column retrieval, we design a nonlinear and a linear model by using the results of the total column retrieval and the value of the stratospheric NO2 column delivered by a stratosphere–troposphere separation method. We also analyze the fundamentals of the commonly used differential optical absorption spectroscopy (DOAS) model and outline its relationship to the proposed inversion models. By a numerical analysis, we analyze the accuracy of the inversion models to retrieve total and tropospheric NO2 columns.

Item URL in elib:https://elib.dlr.de/134297/
Document Type:Article
Title:Inversion Models for the Retrieval of Total and Tropospheric NO2 Columns
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Date:October 2019
Journal or Publication Title:Atmosphere
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:pp. 1-21
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:satellite retrieval, inversion model, NO2
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 - Project Climatic relevance of atmospheric tracer gases, aerosols and clouds
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Liu, Song
Deposited On:05 Mar 2020 12:38
Last Modified:30 Oct 2023 14:03

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