Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)

<p>Methane is the second most important greenhouse gas in terms of anthropogenic radiative forcing. Since pre-industrial times, the globally averaged dry mole fraction of methane in the atmosphere has increased considerably. Emissions from coal mining are one of the primary anthropogenic metha...

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Main Authors: A.-L. Nickl, M. Mertens, A. Roiger, A. Fix, A. Amediek, A. Fiehn, C. Gerbig, M. Galkowski, A. Kerkweg, T. Klausner, M. Eckl, P. Jöckel
Format: Article
Language:English
Published: Copernicus Publications 2020-04-01
Series:Geoscientific Model Development
Online Access:https://www.geosci-model-dev.net/13/1925/2020/gmd-13-1925-2020.pdf
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spelling doaj-f4b0753a02944893ba4c9433f91f6b262020-11-25T02:48:15ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032020-04-01131925194310.5194/gmd-13-1925-2020Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)A.-L. Nickl0M. Mertens1A. Roiger2A. Fix3A. Amediek4A. Fiehn5C. Gerbig6M. Galkowski7M. Galkowski8A. Kerkweg9A. Kerkweg10T. Klausner11M. Eckl12P. Jöckel13Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyMax Planck Institute for Biogeochemistry, Jena, GermanyMax Planck Institute for Biogeochemistry, Jena, GermanyAGH University of Science and Technology, Krakow, PolandInstitute of Geosciences and Meteorology, University of Bonn, Bonn, Germanynow at: Research Center Jülich, Institute of Energy and Climate Research, Jülich, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany<p>Methane is the second most important greenhouse gas in terms of anthropogenic radiative forcing. Since pre-industrial times, the globally averaged dry mole fraction of methane in the atmosphere has increased considerably. Emissions from coal mining are one of the primary anthropogenic methane sources. However, our knowledge about different sources and sinks of methane is still subject to great uncertainties. Comprehensive measurement campaigns and reliable chemistry–climate models, are required to fully understand the global methane budget and to further develop future climate mitigation strategies. The CoMet 1.0 campaign (May to June 2018) combined airborne in situ, as well as passive and active remote sensing measurements to quantify the emissions from coal mining in the Upper Silesian Coal Basin (USCB, Poland). Roughly 502&thinsp;kt of methane is emitted from the ventilation shafts per year. In order to help with the flight planning during the campaigns, we performed 6&thinsp;d forecasts using the online coupled, three-time nested global and regional chemistry–climate model MECO(n). We applied three-nested COSMO/MESSy instances going down to a spatial resolution of 2.8&thinsp;km over the USCB. The nested global–regional model system allows for the separation of local emission contributions from fluctuations in the background methane. Here, we introduce the forecast set-up and assess the impact of the model's spatial resolution on the simulation of methane plumes from the ventilation shafts. Uncertainties in simulated methane mixing ratios are estimated by comparing different airborne measurements to the simulations. Results show that MECO(3) is able to simulate the observed methane plumes and the large-scale patterns (including vertically integrated values) reasonably well. Furthermore, we obtain reasonable forecast results up to forecast day four.</p>https://www.geosci-model-dev.net/13/1925/2020/gmd-13-1925-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author A.-L. Nickl
M. Mertens
A. Roiger
A. Fix
A. Amediek
A. Fiehn
C. Gerbig
M. Galkowski
M. Galkowski
A. Kerkweg
A. Kerkweg
T. Klausner
M. Eckl
P. Jöckel
spellingShingle A.-L. Nickl
M. Mertens
A. Roiger
A. Fix
A. Amediek
A. Fiehn
C. Gerbig
M. Galkowski
M. Galkowski
A. Kerkweg
A. Kerkweg
T. Klausner
M. Eckl
P. Jöckel
Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
Geoscientific Model Development
author_facet A.-L. Nickl
M. Mertens
A. Roiger
A. Fix
A. Amediek
A. Fiehn
C. Gerbig
M. Galkowski
M. Galkowski
A. Kerkweg
A. Kerkweg
T. Klausner
M. Eckl
P. Jöckel
author_sort A.-L. Nickl
title Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
title_short Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
title_full Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
title_fullStr Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
title_full_unstemmed Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)
title_sort hindcasting and forecasting of regional methane from coal mine emissions in the upper silesian coal basin using the online nested global regional chemistry–climate model meco(n) (messy v2.53)
publisher Copernicus Publications
series Geoscientific Model Development
issn 1991-959X
1991-9603
publishDate 2020-04-01
description <p>Methane is the second most important greenhouse gas in terms of anthropogenic radiative forcing. Since pre-industrial times, the globally averaged dry mole fraction of methane in the atmosphere has increased considerably. Emissions from coal mining are one of the primary anthropogenic methane sources. However, our knowledge about different sources and sinks of methane is still subject to great uncertainties. Comprehensive measurement campaigns and reliable chemistry–climate models, are required to fully understand the global methane budget and to further develop future climate mitigation strategies. The CoMet 1.0 campaign (May to June 2018) combined airborne in situ, as well as passive and active remote sensing measurements to quantify the emissions from coal mining in the Upper Silesian Coal Basin (USCB, Poland). Roughly 502&thinsp;kt of methane is emitted from the ventilation shafts per year. In order to help with the flight planning during the campaigns, we performed 6&thinsp;d forecasts using the online coupled, three-time nested global and regional chemistry–climate model MECO(n). We applied three-nested COSMO/MESSy instances going down to a spatial resolution of 2.8&thinsp;km over the USCB. The nested global–regional model system allows for the separation of local emission contributions from fluctuations in the background methane. Here, we introduce the forecast set-up and assess the impact of the model's spatial resolution on the simulation of methane plumes from the ventilation shafts. Uncertainties in simulated methane mixing ratios are estimated by comparing different airborne measurements to the simulations. Results show that MECO(3) is able to simulate the observed methane plumes and the large-scale patterns (including vertically integrated values) reasonably well. Furthermore, we obtain reasonable forecast results up to forecast day four.</p>
url https://www.geosci-model-dev.net/13/1925/2020/gmd-13-1925-2020.pdf
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