Evaluating the assimilation of S5P/TROPOMI near real-time SO<sub>2</sub> columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption
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Published:2022-02-02
Issue:3
Volume:15
Page:971-994
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Inness AntjeORCID, Ades Melanie, Balis DimitrisORCID, Efremenko DmitryORCID, Flemming JohannesORCID, Hedelt PascalORCID, Koukouli Maria-ElissavetORCID, Loyola DiegoORCID, Ribas Roberto
Abstract
Abstract. The Copernicus Atmosphere Monitoring Service (CAMS), operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European
Commission, 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 SO2 products 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 SO2 increments in the vertical. In the current operational CAMS
configuration, the SO2 increments 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 SO2 at very different altitudes, in particular
exceptional events where part of the SO2 plume 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–SO2 Layer
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 SO2 column. CAMS is testing the assimilation of these products, making use of the NRT layer height information to place the
SO2 increments at a retrieved altitude. Assimilation tests with the TROPOMI SO2 layer height data for the Raikoke eruption in
June 2019 show that the resulting CAMS SO2 plume heights agree better with IASI plume height data than operational CAMS runs without the
TROPOMI SO2 layer 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 SO2 values
in better agreement with the satellite observations. However, the plume area and SO2 burden 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 SO2 layer height data, the CAMS system can predict the overall location of the Raikoke SO2 plume up to
5 d in advance for about 20 d after 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.
Publisher
Copernicus GmbH
Reference63 articles.
1. AERIS: IASI SO2 plume height data, https://en.aeris-data.fr/, last access: 30 January 2022. 2. Albert, M. F. M. A., Anguelova, M. D., Manders, A. M. M., Schaap, M., and de Leeuw, G.: Parameterization of oceanic whitecap fraction based on satellite observations, Atmos. Chem. Phys., 16, 13725–13751, https://doi.org/10.5194/acp-16-13725-2016, 2016. 3. Brenot, H., Theys, N., Clarisse, L., van Geffen, J., van Gent, J., Van Roozendael, M., van der A, R., Hurtmans, D., Coheur, P.-F., Clerbaux, C., Valks, P., Hedelt, P., Prata, F., Rasson, O., Sievers, K., and Zehner, C.: Support to Aviation Control Service (SACS): an online service for near-real-time satellite monitoring of volcanic plumes, Nat. Hazards Earth Syst. Sci., 14, 1099–1123, https://doi.org/10.5194/nhess-14-1099-2014, 2014. 4. Brenot, H., Theys, N., Clarisse, L., van Gent, J., Hurtmans, D. R., Vandenbussche, S., Papagiannopoulos, N., Mona, L., Virtanen, T., Uppstu, A., Sofiev, M., Bugliaro, L., Vázquez-Navarro, M., Hedelt, P., Parks, M. M., Barsotti, S., Coltelli, M., Moreland, W., Scollo, S., Salerno, G., Arnold-Arias, D., Hirtl, M., Peltonen, T., Lahtinen, J., Sievers, K., Lipok, F., Rüfenacht, R., Haefele, A., Hervo, M., Wagenaar, S., Som de Cerff, W., de Laat, J., Apituley, A., Stammes, P., Laffineur, Q., Delcloo, A., Lennart, R., Rokitansky, C.-H., Vargas, A., Kerschbaum, M., Resch, C., Zopp, R., Plu, M., Peuch, V.-H., Van Roozendael, M., and Wotawa, G.: EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds, Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, 2021. 5. Carn, S. A., Clarisse, L., and Prata, A. J.:
Multi-decadal Satellite Measurements of Global Volcanic Degassing,
J. Volcanol. Geoth. Res.,
311, 99–134. https://doi.org/10.1016/j.jvolgeores.2016.01.002, 2016.
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