Search

Aqueous-phase chemical processes in clouds, fog, and deliquescent aerosols are known to alter atmospheric composition and acidity significantly. Traditionally, global and regional models predict aerosol composition by relying on thermodynamic equilibrium models and neglect non-equilibrium processes. Here, we present the AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel developed for the Modular Earth Submodel System (MESSy) as an add-on to the thermodynamic equilibrium model (i.e. ISORROPIA-II) used by MESSy's Global Modal-aerosol eXtension (GMXe) submodel. AERCHEM allows the representation of non-equilibrium aqueous-phase chemistry of varying complexity in deliquescent fine aerosols. We perform a global simulation for the year 2010 by using the available detailed kinetic model for the chemistry of inorganic and small oxygenated organics. We evaluate AERCHEM's performance by comparing the simulated concentrations of sulfate, nitrate, ammonium, and chloride to in situ measurements of three monitoring networks. Overall, AERCHEM reproduces observed concentrations reasonably well. We find that, especially in the USA, the consideration of non-equilibrium chemistry in deliquescent aerosols reduces the model bias for sulfate, nitrate, and ammonium when compared to simulated concentrations by ISORROPIA-II. Over most continental regions, fine-aerosol acidity simulated by AERCHEM is similar to the predictions by ISORROPIA-II, but simulated aerosol acidity tends to be slightly lower in most regions. The consideration of non-equilibrium chemistry in deliquescent aerosols leads to a significantly higher aerosol acidity in the marine boundary layer, which is in line with observations and recent literature. AERCHEM allows an investigation of the global-scale impact of aerosol non-equilibrium chemistry on atmospheric composition. This will aid in the exploration of key multiphase processes and improve the model predictions for oxidation capacity and aerosols in the troposphere.

The columnar approach of gravity wave (GW) parameterisations in weather and climate models has been identified as a potential reason for dynamical biases in middle-atmospheric dynamics. For example, GW momentum flux (GWMF) discrepancies between models and observations at 60∘ S arising through the lack of horizontal orographic GW propagation are suspected to cause deficiencies in representing the Antarctic polar vortex. However, due to the decomposition of the model domains onto different computing tasks for parallelisation, communication between horizontal grid boxes is computationally extremely expensive, making horizontal propagation of GWs unfeasible for global chemistry–climate simulations. To overcome this issue, we present a simplified solution to approximate horizontal GW propagation through redistribution of the GWMF at one single altitude by means of tailor-made redistribution maps. To generate the global redistribution maps averaged for each grid box, we use a parameterisation describing orography as a set of mountain ridges with specified location, orientation and height combined with a ray-tracing model describing lateral propagation of so-generated mountain waves. In the global chemistry–climate model (CCM) EMAC (ECHAM MESSy Atmospheric Chemistry), these maps then allow us to redistribute the GW momentum flux horizontally at one level, obtaining an affordable overhead of computing resources. The results of our simulations show GWMF and drag patterns that are horizontally more spread out than with the purely columnar approach; GWs are now also present above the ocean and regions without mountains. In this paper, we provide a detailed description of how the redistribution maps are computed and how the GWMF redistribution is implemented in the CCM. Moreover, an analysis shows why 15 km is the ideal altitude for the redistribution. First results with the redistributed orographic GWMF provide clear evidence that the redistributed GW drag in the Southern Hemisphere has the potential to modify and improve Antarctic polar vortex dynamics, thereby paving the way for enhanced credibility of CCM simulations and projections of polar stratospheric ozone.

We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

Dry deposition to vegetation is a major sink of ground-level ozone and is responsible for about 20 % of the total tropospheric ozone loss. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for the global tropospheric ozone budget and might account for the mismatch with observations. The model used in this study, the Modular Earth Submodel System version 2 (MESSy2) linked to the fifth-generation European Centre Hamburg general circulation model (ECHAM5) as an atmospheric circulation model (EMAC), is no exception. Like many global models, EMAC employs a “resistance in series” scheme with the major surface deposition via plant stomata which is hardly sensitive to meteorology, depending only on solar radiation. Unlike many global models, however, EMAC uses a simplified high resistance for non-stomatal deposition which makes this pathway negligible in the model. However, several studies have shown this process to be comparable in magnitude to the stomatal uptake, especially during the night over moist surfaces. Hence, we present here a revised dry deposition in EMAC including meteorological adjustment factors for stomatal closure and an explicit cuticular pathway. These modifications for the three stomatal stress functions have been included in the newly developed MESSy VERTEX submodel, i.e. a process model describing the vertical exchange in the atmospheric boundary layer, which will be evaluated for the first time here. The scheme is limited by a small number of different surface types and generalized parameters. The MESSy submodel describing the dry deposition of trace gases and aerosols (DDEP) has been revised accordingly. The comparison of the simulation results with measurement data at four sites shows that the new scheme enables a more realistic representation of dry deposition. However, the representation is strongly limited by the local meteorology. In total, the changes increase the dry deposition velocity of ozone up to a factor of 2 globally, whereby the highest impact arises from the inclusion of cuticular uptake, especially over moist surfaces. This corresponds to a 6 % increase of global annual dry deposition loss of ozone resulting globally in a slight decrease of ground-level ozone but a regional decrease of up to 25 %. The change of ozone dry deposition is also reasoned by the altered loss of ozone precursors. Thus, the revision of the process parameterization as documented here has, among others, the potential to significantly reduce the overestimation of tropospheric ozone in global models.

Land transport is an important emission source of nitrogen oxides, carbon monoxide, and volatile organic compounds. The emissions of nitrogen oxides affect air quality directly. Further, all of these emissions serve as a precursor for the formation of tropospheric ozone, thus leading to an indirect influence on air quality. In addition, ozone is radiatively active and its increase leads to a positive radiative forcing. Due to the strong non-linearity of the ozone chemistry, the contribution of emission sources to ozone cannot be calculated or measured directly. Instead, atmospheric chemistry models equipped with specific source attribution methods (e.g. tagging methods) are required. In this study we investigate the contribution of land transport emissions to ozone and ozone precursors using the MECO(n) model system (MESSy-fied ECHAM and COSMO models nested n times). This model system couples a global and a regional chemistry climate model and is equipped with a tagging diagnostic. We investigate the combined effect of long-range-transported ozone and ozone which is produced by European emissions by applying the tagging diagnostic simultaneously and consistently on the global and regional scale. We performed two simulations each covering 3 years with different anthropogenic emission inventories for Europe. We applied two regional refinements, i.e. one refinement covering Europe (50 km resolution) and one covering Germany (12 km resolution). The diagnosed absolute contributions of land transport emissions to reactive nitrogen (NOy) near ground level are in the range of 5 to 10 nmol mol−1. This corresponds to relative contributions of 50 % to 70 %. The largest absolute contributions appear around Paris, southern England, Moscow, the Po Valley, and western Germany. The absolute contributions to carbon monoxide range from 30 nmol mol−1 to more than 75 nmol mol−1 near emission hot-spots such as Paris or Moscow. The ozone which is attributed to land transport emissions shows a strong seasonal cycle with absolute contributions of 3 nmol mol−1 during winter and 5 to 10 nmol mol−1 during summer. This corresponds to relative contributions of 8 % to 10 % during winter and up to 16 % during summer. The largest values during summer are confined to the Po Valley, while the contributions in western Europe range from 12 % to 14 %. Only during summer are the ozone contributions slightly influenced by the anthropogenic emission inventory, but these differences are smaller than the range of the seasonal cycle of the contribution to land transport emissions. This cycle is caused by a complex interplay of seasonal cycles of other emissions (e.g. biogenic) and seasonal variations of the ozone regimes. In addition, our results suggest that during events with large ozone values the ozone contributions of land transport and biogenic emissions increase strongly. Here, the contribution of land transport emissions peaks up to 28 %. Hence, our model results suggest that land transport emissions are an important contributor during periods with large ozone values.

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 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 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 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.

Anthropogenic and natural emissions influence the tropospheric ozone budget, thereby affecting air quality and climate. To study the influence of different emission sources on the ozone budget, often source apportionment studies with a tagged tracer approach are performed. Studies investigating air quality issues usually rely on regional models with a fine spatial resolution, while studies focusing on climate-related questions often use coarsely resolved global models. It is well known that simulated ozone mixing ratios depend on the resolution of the model and the resolution of the emission inventory. Whether the contributions simulated using source apportionment approaches also depend on the model resolution, however, is still unclear. Therefore, this study attempts for the first time to analyse the impact of the model, the model resolution, and the emission inventory resolution on simulated ozone contributions using a diagnostic tagging method. The differences in the ozone contributions caused by these factors are compared with differences that arise from the usage of different emission inventories. To do so, we apply the MECO(n) (MESSy-fied ECHAM and COSMO models nested n times) model system which couples online a global chemistry-climate model with a regional chemistry-climate model equipped with a tagging scheme for source apportionment. The results of the global model (at 300 km horizontal resolution) are compared with the results of the regional model at 50 km (Europe) and 12 km (Germany) resolutions. Besides model-specific differences and biases that are discussed in detail, our results have important implications for other modelling studies and modellers applying source apportionment methods. First, contributions from anthropogenic emissions averaged over the continental scale are quite robust with respect to the model, model resolution, and emission inventory resolution. Second, differences on the regional scale caused by different models and model resolutions can be quite large, and regional models are indispensable for source apportionment studies on the subcontinental scale. Third, contributions from stratospheric ozone transported to the surface differ strongly between the models, mainly caused by differences in the efficiency of the vertical mixing. As stratospheric ozone plays an important role for ground level ozone, but the models show large differences in the amount of downward transported ozone, source apportionment methods should account for this source explicitly to better understand inter-model differences.

As part of the Modular Earth Submodel System (MESSy), the Multi-Model-Driver (MMD v1.0) was developed to couple online the regional Consortium for Small-scale Modeling (COSMO) model into a driving model, which can be either the regional COSMO model or the global European Centre Hamburg general circulation model (ECHAM) (see Part 2 of the model documentation). The coupled system is called MECO(n), i.e., MESSy-fied ECHAM and COSMO models nested n times. In this article, which is part of the model documentation of the MECO(n) system, the second generation of MMD is introduced. MMD comprises the message-passing infrastructure required for the parallel execution (multiple programme multiple data, MPMD) of different models and the communication of the individual model instances, i.e. between the driving and the driven models. Initially, the MMD library was developed for a one-way coupling between the global chemistry–climate ECHAM/MESSy atmospheric chemistry (EMAC) model and an arbitrary number of (optionally cascaded) instances of the regional chemistry–climate model COSMO/MESSy. Thus, MMD (v1.0) provided only functions for unidirectional data transfer, i.e. from the larger-scale to the smaller-scale models.Soon, extended applications requiring data transfer from the small-scale model back to the larger-scale model became of interest. For instance, the original fields of the larger-scale model can directly be compared to the upscaled small-scale fields to analyse the improvements gained through the small-scale calculations, after the results are upscaled. Moreover, the fields originating from the two different models might be fed into the same diagnostic tool, e.g. the online calculation of the radiative forcing calculated consistently with the same radiation scheme. Last but not least, enabling the two-way data transfer between two models is the first important step on the way to a fully dynamical and chemical two-way coupling of the various model instances.In MMD (v1.0), interpolation between the base model grids is performed via the COSMO preprocessing tool INT2LM, which was implemented into the MMD submodel for online interpolation, specifically for mapping onto the rotated COSMO grid. A more flexible algorithm is required for the backward mapping. Thus, MMD (v2.0) uses the new MESSy submodel GRID for the generalised definition of arbitrary grids and for the transformation of data between them.In this article, we explain the basics of the MMD expansion and the newly developed generic MESSy submodel GRID (v1.0) and show some examples of the abovementioned applications.

Aqueous-phase chemical processes in clouds, fog, and deliquescent aerosols are known to alter atmospheric composition and acidity significantly. Traditionally, global and regional models predict aerosol composition by relying on thermodynamic equilibrium models and neglect non-equilibrium processes. Here, we present the AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel developed for the Modular Earth Submodel System (MESSy) as an add-on to the thermodynamic equilibrium model (i.e., ISORROPIA-II) used by MESSy's Global Modal-aerosol eXtension (GMXe) submodel. AERCHEM allows the representation of non-equilibrium aqueous-phase chemistry of varying complexity in deliquescent fine aerosols. We perform a global simulation for the year 2010 by using the available detailed kinetic model for the chemistry of inorganic and small oxygenated organics. We evaluate AERCHEM's performance by comparing the simulated concentrations of sulfate, nitrate, ammonium, and chloride to in situ measurements of three monitoring networks. Overall, AERCHEM reproduces observed concentrations reasonably well. We find that especially in the USA, the consideration of non-equilibrium chemistry in deliquescent aerosols reduces the model bias for sulfate, nitrate, and ammonium, when compared to simulated concentrations by ISORROPIA-II. Over most continental regions, fine aerosol acidity simulated by AERCHEM is similar to the predictions by ISORROPIA-II but tends to simulate slightly lower aerosol acidity in most regions. The consideration of non-equilibrium chemistry in deliquescent aerosols leads to a significant higher aerosol acidity in the marine boundary layer, which is in line with observations and recent literature. AERCHEM allows investigating the global-scale impact of aerosol non-equilibrium chemistry on atmospheric composition. This will aid the exploration of key multiphase processes and improve the model predictions for oxidation capacity and aerosols in the troposphere. [ABSTRACT FROM AUTHOR]

For the first time, a simulation incorporating tropospheric and stratospheric chemistry using the newly developed MECO(n) model system is performed. MECO(n) is short for MESSy-fied ECHAM and COSMO models nested n times. It features an online coupling of the COSMO-CLM model, equipped with the Modular Earth Submodel System (MESSy) interface (called COSMO/MESSy), with the global atmospheric chemistry model ECHAM5/MESSy for Atmospheric Chemistry (EMAC). This online coupling allows a consistent model chain with respect to chemical and meteorological boundary conditions from the global scale down to the regional kilometre scale. A MECO(2) simulation incorporating one regional instance over Europe with 50 km resolution and one instance over Germany with 12 km resolution is conducted for the evaluation of MECO(n) with respect to tropospheric gas-phase chemistry. The main goal of this evaluation is to ensure that the chemistry-related MESSy submodels and the online coupling with respect to the chemistry are correctly implemented. This evaluation is a prerequisite for the further usage of MECO(n) in atmospheric chemistry-related studies. Results of EMAC and the two COSMO/MESSy instances are compared with satellite, ground-based and aircraft in situ observations, focusing on ozone, carbon monoxide and nitrogen dioxide. Further, the methane lifetimes in EMAC and the two COSMO/MESSy instances are analysed in view of the tropospheric oxidation capacity. From this evaluation, we conclude that the chemistry-related submodels and the online coupling with respect to the chemistry are correctly implemented. In comparison with observations, both EMAC and COSMO/MESSy show strengths and weaknesses. Especially in comparison to aircraft in situ observations, COSMO/MESSy shows very promising results. However, the amplitude of the diurnal cycle of ground-level ozone measurements is underestimated. Most of the differences between COSMO/MESSy and EMAC can be attributed to differences in the dynamics of both models, which are subject to further model developments.

Three types of reference simulations, as recommended by the Chemistry–Climate Model Initiative (CCMI), have been performed with version 2.51 of the European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model: hindcast simulations (1950–2011), hindcast simulations with specified dynamics (1979–2013), i.e. nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations (1950–2100). The manuscript summarizes the updates of the model system and details the different model set-ups used, including the on-line calculated diagnostics. Simulations have been performed with two different nudging set-ups, with and without interactive tropospheric aerosol, and with and without a coupled ocean model. Two different vertical resolutions have been applied. The on-line calculated sources and sinks of reactive species are quantified and a first evaluation of the simulation results from a global perspective is provided as a quality check of the data. The focus is on the intercomparison of the different model set-ups. The simulation data will become publicly available via CCMI and the Climate and Environmental Retrieval and Archive (CERA) database of the German Climate Computing Centre (DKRZ). This manuscript is intended to serve as an extensive reference for further analyses of the Earth System Chemistry integrated Modelling (ESCiMo) simulations.

The Community Earth System Model (CESM1), maintained by the United States National Centre for Atmospheric Research (NCAR) is connected with the Modular Earth Submodel System (MESSy). For the MESSy user community, this offers many new possibilities. The option to use the Community Atmosphere Model (CAM) atmospheric dynamical cores, especially the state-of-the-art spectral element (SE) core, as an alternative to the ECHAM5 spectral transform dynamical core will provide scientific and computational advances for atmospheric chemistry and climate modelling with MESSy. The well-established finite volume core from CESM1(CAM) is also made available. This offers the possibility to compare three different atmospheric dynamical cores within MESSy. Additionally, the CESM1 land, river, sea ice, glaciers and ocean component models can be used in CESM1/MESSy simulations, allowing the use of MESSy as a comprehensive Earth system model (ESM). For CESM1/MESSy set-ups, the MESSy process and diagnostic submodels for atmospheric physics and chemistry are used together with one of the CESM1(CAM) dynamical cores; the generic (infrastructure) submodels support the atmospheric model component. The other CESM1 component models, as well as the coupling between them, use the original CESM1 infrastructure code and libraries; moreover, in future developments these can also be replaced by the MESSy framework. Here, we describe the structure and capabilities of CESM1/MESSy, document the code changes in CESM1 and MESSy, and introduce several simulations as example applications of the system. The Supplements provide further comparisons with the ECHAM5/MESSy atmospheric chemistry (EMAC) model and document the technical aspects of the connection in detail.

Observations and model calculations indicate that highly non-linear multiphase atmospheric processes involving inorganic Cl and Br significantly impact tropospheric chemistry and composition, aerosol evolution, and radiative transfer. The sensitivity of global atmospheric chemistry to the production of marine aerosol and the associated activation and cycling of inorganic Cl and Br was investigated using a size-resolved multiphase coupled chemistry–global climate model (National Center for Atmospheric Research's Community Atmosphere Model (CAM) v3.6.33). Simulated results revealed strong meridional and vertical gradients in Cl and Br species. They also point to possible physicochemical mechanisms that may account for several previously unexplained phenomena, including the enrichment of Br- in submicron aerosol and the presence of a BrO maximum in the polar free troposphere. However, simulated total volatile inorganic Br mixing ratios in the troposphere were generally higher than observed, due in part to the overly efficient net production of BrCl. In addition, the emission scheme for marine aerosol and associated Br−, which is the only source for Br in the model, overestimates emission fluxes from the high-latitude Southern Ocean. Br in the stratosphere was lower than observed due to the lack of long-lived precursor organobromine species in the simulation. Comparing simulations using chemical mechanisms with and without reactive Cl and Br species demonstrates a significant temporal and spatial sensitivity of primary atmospheric oxidants (O3, HOx, NOx), CH4, non-methane hydrocarbons (NMHCs), and dimethyl sulfide (DMS) to halogen cycling. Globally, halogen chemistry had relatively less impact on SO2 and non-sea-salt (nss) SO42− although significant regional differences were evident. Although variable geographically, much of this sensitivity is attributable to either over-vigorous activation of Br (primarily BrCl) via the chemical mechanism or overproduction of sea-salt aerosol simulated under higher-wind regimes. In regions where simulated mixing ratios of reactive Br and Cl fell within observed ranges, though, halogen chemistry drove large changes in oxidant fields and associated chemical processes relative to simulations with no halogens. However, the overall simulated impacts of Br chemistry globally are overestimated and thus caution is warranted in their interpretation.