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The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution

Beirle, S. and Hörmann, Christoph and Jöckel, Patrick and Liu, Song and Penning de Vries, M. and Pozzer, A. and Sihler, H. and Valks, Pieter and Wagner, T. (2016) The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution. Atmospheric Measurement Techniques (AMT), 9, pp. 2753-2779. Copernicus Publications. DOI: 10.5194/amt-9-2753-2016 ISSN 1867-1381

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Official URL: http://www.atmos-meas-tech.net/9/2753/2016/amt-9-2753-2016.pdf

Abstract

The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as verification algorithm for the upcoming satellite instrument TROPOMI, as complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artefacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g. related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1–0.2 × 1015 molecules cm−2, in accordance to the typical deviations between stratospheric estimates from different algorithms compared in this study.

Item URL in elib:https://elib.dlr.de/103673/
Document Type:Article
Title:The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Beirle, S.Max-Planck-Institut für Chemie, MainzUNSPECIFIED
Hörmann, ChristophMax-Planck-Institut für Chemie, MainzUNSPECIFIED
Jöckel, PatrickDLR, IPAhttps://orcid.org/0000-0002-8964-1394
Liu, Songsong.liu (at) dlr.deUNSPECIFIED
Penning de Vries, M.Max-Planck-Institut für Chemie, MainzUNSPECIFIED
Pozzer, A.Max-Planck-Institut für Chemie, MainzUNSPECIFIED
Sihler, H.Max-Planck-Institut für Chemie, MainzUNSPECIFIED
Valks, PieterDLR, IMFUNSPECIFIED
Wagner, T.Max-Planck-Institut für Chemie, MainzUNSPECIFIED
Date:July 2016
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:9
DOI :10.5194/amt-9-2753-2016
Page Range:pp. 2753-2779
Publisher:Copernicus Publications
ISSN:1867-1381
Status:Published
Keywords:satellite, stratosphere, NO2, TROPOMI
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 Ozon-SAF (old), R - Vorhaben Atmosphären- und Klimaforschung
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Institute of Atmospheric Physics > Earth System Modelling
Deposited By: Valks, Dr. Pieter
Deposited On:31 Mar 2016 14:34
Last Modified:08 Mar 2018 18:10

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