The 1-way on-line coupled atmospheric chemistry model system MECO(n) – Part 3: Meteorological evaluation of the on-line coupled system

Hofmann, Christiane; Kerkweg, Astrid; Wernli, Heini; Jöckel, Patrick

doi:10.5194/gmd-5-129-2012

Cited by 17 publications

(24 citation statements)

References 21 publications

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“…By applying the MECO(n) system (Kerkweg and Jöckel, 2012a, b;Hofmann et al, 2012;Mertens et al, 2016), we have increased the horizontal resolution over Europe by roughly a factor of 5, from a resolution of roughly 200 km times 300 km in EMAC to 50 km times 50 km in the nested grid. Figure 10 shows the contributions of the individual emission sectors to the tropospheric ozone column as a mean over Europe for the coarse resolution (top) and the finer resolution (bottom).…”

Section: Higher Resolution: Meco(n)mentioning

confidence: 99%

“…We performed an additional global simulation with EMAC where we reduced the road traffic emissions by 5 %. The simulation set-up hence follows Hoor et al (2009). This means that the chemical composition and the ozone productivity is different from the base simulation, which leads to a roughly 2-3 % reduction in the tagged road traffic ozone (not shown).…”

Section: Emission Changesmentioning

confidence: 99%

“…This perturbation approach (e.g. Hoor et al, 2009;Grewe et al, 2007, and many others), where results from two simulations are compared that differ in the strength of an individual emission source, identify the impact of changes in emissions (e.g. by mitigation options) on the atmospheric composition.…”

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confidence: 99%

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Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

et al. 2017

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Questions such as "what is the contribution of road traffic emissions to climate change?" or "what is the impact of shipping emissions on local air quality?" require a quantification of the contribution of specific emissions sectors to the concentration of radiatively active species and airquality-related species, respectively. Here, we present a diagnostics package, implemented in the Modular Earth Submodel System (MESSy), which keeps track of the contribution of source categories (mainly emission sectors) to various concentrations. The diagnostics package is implemented as a submodel (TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts -Hamburg (ECHAM)/MESSy Atmospheric Chemistry). It determines the contributions of 10 different source categories to the concentration of ozone, nitrogen oxides, peroxyacytyl nitrate, carbon monoxide, non-methane hydrocarbons, hydroxyl, and hydroperoxyl radicals ( = tagged tracers). The source categories are mainly emission sectors and some other sources for completeness. As emission sectors, road traffic, shipping, air traffic, anthropogenic non-traffic, biogenic, biomass burning, and lightning are considered. The submodel obtains information on the chemical reaction rates, online emissions, such as lightning, and wash-out rates. It then solves differential equations for the contribution of a source category to each of the seven tracers. This diagnostics package does not feed back to any other part of the model. For the first time, it takes into account chemically competing effects: for example, the competition between NO x , CO, and non-methane hydrocarbons (NMHCs) in the production and destruction of ozone. We show that the results are in-line with results from other tagging schemes and provide plausibility checks for concentrations of trace gases, such as OH and HO 2 , which have not previously been tagged. The budgets of the tagged tracers, i.e. the contribution from individual source categories (mainly emission sectors) to, e.g., ozone, are only marginally sensitive to changes in model resolution, though the level of detail increases. A reduction in road traffic emissions by 5 % shows that road traffic global tropospheric ozone is reduced by 4 % only, because the net ozone productivity increases. This 4 % reduction in road traffic tropospheric ozone corresponds to a reduction in total tropospheric ozone by ≈ 0.3 %, which is compensated by an increase in tropospheric ozone from other sources by 0.1 %, resulting in a reduction in total tropospheric ozone of ≈ 0.2 %. This compensating effect compares well with previous findings. The computational costs of the TAGGING submodel are low with respect to computing time, but a large number of additional tracers are required. The advantage of the tagging scheme is that in one simulation and at every time step and grid point, information is available on the contribution of different emission sectors to the ozone budget, which then can be further used in upcoming studies to calculate the respective radiative forcing sim...

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Section: Higher Resolution: Meco(n)mentioning

confidence: 99%

Section: Emission Changesmentioning

confidence: 99%

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Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

et al. 2017

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“…The MECO(n) model couples on-line the global chemistry-climate model EMAC (ECHAM5/MESSy Atmospheric Chemistry) with the regional chemistry-climate model COSMO-CLM/MESSy in order to achieve a regional refinement (details can be found in Hofmann et al, 2012;Jöckel, 2012a and2012b;Mertens et al, 2016). COSMO-CLM (Rockel et al, 2008) During the campaign, simulated wind fields and GHG mixing ratios were available from forecast simulations, and after the campaign from one corresponding analysis simulation.…”

Section: On-line Coupled Atmospheric Chemistry Model Meco(n)mentioning

confidence: 99%

Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018

Klausner¹,

Mertens²,

Huntrieser³

et al. 2020

Elem Sci Anth

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Urban areas are recognised as a significant source of greenhouse gas emissions (GHG), such as carbon dioxide (CO 2 ) and methane (CH 4 ). The total amount of urban GHG emissions, especially for CH 4 , however, is not well quantified. Here we report on airborne in situ measurements using a Picarro G1301-m analyser aboard the DLR Cessna Grand Caravan to study GHG emissions downwind of the German capital Berlin. In total, five aircraft-based mass balance experiments were conducted in July 2018 within the Urban Climate Under Change [UC] 2 project. The detection and isolation of the Berlin plume was often challenging because of comparatively small GHG signals above variable atmospheric background concentrations. However, on July 20 th enhancements of up to 4 ppm CO 2 and 21 ppb CH 4 were observed over a horizontal extent of roughly 45 to 65 km downwind of Berlin. These enhanced mixing ratios are clearly distinguishable from the background and can partly be assigned to city emissions. The estimated CO 2 emission flux of 1.39 ± 0.76 t s -1 is in agreement with current inventories, while the CH 4 emission flux of 5.20 ± 1.70 kg s -1 is almost two times larger than the highest reported value in the inventories. We localized the source area with HYSPLIT trajectory calculations and the global/regional nested chemistry climate model MECO(n) (down to ~1 km), and investigated the contribution from sewage-treatment plants and waste deposition to CH 4 , which are treated differently by the emission inventories. Our work highlights the importance of strong CH 4 sources in the vicinity of Berlin and shows, that there is limited understanding of CH 4 emissions from urban regions, even for major cities in highly developed countries like Germany. Furthermore, we show that a detailed knowledge of GHG inflow mixing ratios is necessary to suitably estimate emission rates for Berlin.

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“…That meteorological situation has already been studied with the MECO(n) system (Hofmann et al, 2012). In this study, the model results have been compared with precipitation measurements and analysis data.…”

Section: Atmospheric Chemistry Set-up and Initialisationmentioning

confidence: 99%

Stratosphere-troposphere exchange in the vicinity of a tropopause fold

Hofmann

Kerkweg

Hoor

et al. 2016

Preprint

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Transport of air masses from the stratosphere to the troposphere along tropopause folds can lead to peaked ozone concentrations at ground level and hereby influence the long-term trend of tropospheric ozone. To improve the understanding of responsible processes and preferred regions of exchange, transient and reversible exchange processes in the vicinity of a tropopause fold are analysed on the basis of a case study. The global and regional atmospheric chemistry model system MECO(n), which couples the limited-area atmospheric chemistry and climate model COSMO-CLM/MESSy to the global model ECHAM5/MESSy for Atmospheric Chemistry (EMAC) is applied. Using similar process parametrisations in both model instances, the system allows for very consistent, simultaneous simulations at different spatial resolutions. Simulated ozone enhancements at ground level, caused by descending stratospheric air masses, are evaluated with observational data. Because of the coarse resolution of the global model, the observed ozone enhancements are not captured by the global model instance. However, the results of the finer resolved, regional model instance coincide well with the measurements. Based on the combination of Eulerian and Lagrangian analysis methods it is shown that stratosphere-troposphere-exchange (STE) in the vicintity of the tropopause fold occurs in regions of turbulence and diabatic processes. Within the framework of a Lagrangian study the efficiency of mixing along a tropopause fold is quantified, showing that almost all (97 %) of the air masses originating in the tropopause fold are transported into the troposphere during the following two days.

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The 1-way on-line coupled atmospheric chemistry model system MECO(n) – Part 3: Meteorological evaluation of the on-line coupled system

Cited by 17 publications

References 21 publications

Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018

Stratosphere-troposphere exchange in the vicinity of a tropopause fold

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