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Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption

Inness, Antje and Ades, Melanie and Balis, Dimitris and Efremenko, Dmitry S. and Flemming, Johannes and Hedelt, Pascal and Koukouli, Maria-Elissavet and Loyola, Diego and Ribas, Roberto (2022) Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption. Geoscientific Model Development, 15 (3), pp. 971-994. Copernicus Publications. doi: 10.5194/gmd-15-971-2022. ISSN 1991-959X.

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Official URL: https://dx.doi.org/10.5194/gmd-15-971-2022

Abstract

The Copernicus Atmosphere Monitoring Service(CAMS), operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Com-mission, provides daily analyses and 5 d forecasts of atmospheric composition, including forecasts of volcanic sulfur dioxide (SO2) in near real time. CAMS currently assimilates total column SO2products from the GOME-2 instruments on MetOp-B and MetOp-C and the TROPOMI instrument on Sentinel-5P, which give information about the location and strength of volcanic plumes. However, the operational TROPOMI and GOME-2 data do not provide any information about the height of the volcanic plumes, and therefore some prior assumptions need to be made in the CAMS data assimilation system about where to place the resulting SO2increments in the vertical. In the current operational CAMS configuration, the SO2increments are placed in the mid-troposphere, around 550 hPa or 5 km. While this gives good results for the majority of volcanic emissions, it will clearly be wrong for eruptions that inject SO2at very different altitudes, in particular exceptional events where part of the SO2plume reaches the stratosphere.A new algorithm, developed by the German Aerospace Centre (DLR) for GOME-2 and TROPOMI, optimized in the frame of the ESA-funded Sentinel-5P Innovation–SO2Layer Height Project, and known as the Full-Physics Inverse Learning Machine (FP_ILM) algorithm, retrieves SO2 layer height from TROPOMI in near real time (NRT) in addition to the SO2column. CAMS is testing the assimilation of these products, making use of the NRT layer height information to place the SO2increments at a retrieved altitude. Assimilation tests with the TROPOMI SO2layer height data for the Raikoke eruption in June 2019 show that the resulting CAMSSO2plume heights agree better with IASI plume height data than operational CAMS runs without the TROPOMI SO2layer height information and show that making use of the additional layer height information leads to improved SO2 forecasts. Including the layer height information leads to higher modelled total column SO2values in better agreement with the satellite observations. However, the plume area and SO2burden are generally also overestimated in the CAMS analysis when layer height data are used. The main reason for this overestimation is the coarse horizontal resolution used in the minimizations. By assimilating the SO2layer height data, the CAMS system can predict the overall location of the Raikoke SO2plume up to 5 d in advance for about 20 dafter the initial eruption, which is better than with the operational CAMS configuration (without prior knowledge of the plume height) where the forecast skill is much more reduced for longer forecast lead times.

Item URL in elib:https://elib.dlr.de/186062/
Document Type:Article
Title:Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Inness, AntjeEuropean Centre for Medium-Range Weather Forecasts (ECMWF)UNSPECIFIED
Ades, MelanieEuropean Centre for Medium-Range Weather Forecasts (ECMWF)UNSPECIFIED
Balis, DimitrisLaboratory of Atmospheric Physics, Aristotle University of Thessaloniki,UNSPECIFIED
Efremenko, Dmitry S.dmitry.efremenko (at) dlr.dehttps://orcid.org/0000-0002-7449-5072
Flemming, JohannesEuropean Centre for Medium-Range Weather Forecasts (ECMWF)UNSPECIFIED
Hedelt, PascalPascal.Hedelt (at) dlr.dehttps://orcid.org/0000-0002-1752-0040
Koukouli, Maria-ElissavetLaboratory of Atmospheric Physics, Aristotle University of Thessaloniki,UNSPECIFIED
Loyola, DiegoDiego.Loyola (at) dlr.dehttps://orcid.org/0000-0002-8547-9350
Ribas, RobertoEuropean Centre for Medium-Range Weather Forecasts (ECMWF)UNSPECIFIED
Date:2022
Journal or Publication Title:Geoscientific Model Development
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:15
DOI :10.5194/gmd-15-971-2022
Page Range:pp. 971-994
Publisher:Copernicus Publications
ISSN:1991-959X
Status:Published
Keywords:SO2 retrieval; TROPOMI
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 - Spectroscopic methods of the atmosphere
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Efremenko, Dr Dmitry
Deposited On:12 Apr 2022 08:56
Last Modified:13 Apr 2022 17:12

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