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- ItemDetection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model(Katlenburg-Lindau : EGU, 2020) Costa-Surós, Montserrat; Sourdeval, Odran; Acquistapace, Claudia; Baars, Holger; Carbajal Henken, Cintia; Genz, Christa; Hesemann, Jonas; Jimenez, Cristofer; König, Marcel; Kretzschmar, Jan; Madenach, Nils; Meyer, Catrin I.; Schrödner, Roland; Seifert, Patric; Senf, Fabian; Brueck, Matthias; Cioni, Guido; Engels, Jan Frederik; Fieg, Kerstin; Gorges, Ksenia; Heinze, Rieke; Kumar Siligam, Pavan; Burkhardt, Ulrike; Crewell, Susanne; Hoose, Corinna; Seifert, Axel; Tegen, Ina; Quaas, JohannesClouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth's changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from groundbased lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural vari ability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m-2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol-cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol-cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation-2:6 W m-2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of-0:8 W m-2 © 2020 Author(s).
- ItemCAPRAM reduction towards an operational multiphase halogen and dimethyl sulfide chemistry treatment in the chemistry transport model COSMO-Muscat(5.04e)(Katlenburg-Lindau : Copernicus, 2020) Hoffmann, Erik H.; Schrödner, Roland; Tilgner, Andreas; Wolke, Ralf; Herrmann, HartmutA condensed multiphase halogen and dimethyl sulfide (DMS) chemistry mechanism for application in chemistry transport models is developed by reducing the CAPRAM DMS module 1.0 (CAPRAM-DM1.0) and the CAPRAM halogen module 3.0 (CAPRAM-HM3.0). The reduction is achieved by determining the main oxidation pathways from analysing the mass fluxes of complex multiphase chemistry simulations with the air parcel model SPACCIM (SPectral Aerosol Cloud Chemistry Interaction Model). These simulations are designed to cover both pristine and polluted marine boundary layer conditions. Overall, the reduced CAPRAM-DM1.0 contains 32 gas-phase reactions, 5 phase transfers, and 12 aqueous-phase reactions, of which two processes are described as equilibrium reactions. The reduced CAPRAM-HM3.0 contains 199 gas-phase reactions, 23 phase transfers, and 87 aqueous-phase reactions. For the aqueous-phase chemistry, 39 processes are described as chemical equilibrium reactions. A comparison of simulations using the complete CAPRAM-DM1.0 and CAPRAM-HM3.0 mechanisms against the reduced ones indicates that the relative deviations are below 5 % for important inorganic and organic air pollutants and key reactive species under pristine ocean and polluted conditions. The reduced mechanism has been implemented into the chemical transport model COSMO-MUSCAT and tested by performing 2D simulations under prescribed meteorological conditions that investigate the effect of stable (stratiform cloud) and more unstable meteorological conditions (convective clouds) on marine multiphase chemistry. The simulated maximum concentration of HCl is of the order of 109 molecules cm−3 and that of BrO is around 1×107 molecules cm−3, reproducing the range of ambient measurements. Afterwards, the oxidation pathways of DMS in a cloudy marine atmosphere have been investigated in detail. The simulations demonstrate that clouds have both a direct and an indirect photochemical effect on the multiphase processing of DMS and its oxidation products. The direct photochemical effect is related to in-cloud chemistry that leads to high dimethyl sulfoxide (DMSO) oxidation rates and a subsequently enhanced formation of methane sulfonic acid compared to aerosol chemistry. The indirect photochemical effect is characterized by cloud shading, which occurs particularly in the case of stratiform clouds. The lower photolysis rate affects the activation of Br atoms and consequently lowers the formation of BrO radicals. The corresponding DMS oxidation flux is lowered by up to 30 % under thick optical clouds. Moreover, high updraught velocities lead to a strong vertical mixing of DMS into the free troposphere predominately under cloudy conditions. The photolysis of hypohalous acids (HOX, X = Cl, Br, or I) is reduced as well, resulting in higher HOX-driven sulfite-to-sulfate oxidation in aerosol particles below stratiform clouds. Altogether, the present model simulations have demonstrated the ability of the reduced mechanism to be applied in studying marine aerosol–cloud processing effects in regional models such as COSMO-MUSCAT. The reduced mechanism can be used also by other regional models for more adequate interpretations of complex marine field measurement data.
- ItemLarge difference in aerosol radiative effects from BVOC-SOA treatment in three Earth system models(Katlenburg-Lindau : EGU, 2020) Sporre, Moa K.; Blichner, Sara M.; Schrödner, Roland; Karset, Inger H.H.; Berntsen, Terje K.; van Noije, Twan; Bergman, Tommi; O’Donnell, Declan; Makkonen, RistoBiogenic volatile organic compounds (BVOCs) emitted from vegetation are oxidised in the atmosphere and can form aerosol particles either by contributing to new particle formation or by condensing onto existing aerosol particles. As the understanding of the importance of BVOCs for aerosol formation has increased over the years, these processes have made their way into Earth system models (ESMs). In this study, sensitivity experiments are run with three different ESMs (the Norwegian Earth System Model (NorESM), EC-Earth and ECHAM) to investigate how the direct and indirect aerosol radiative effects are affected by changes in the formation of secondary organic aerosol (SOA) from BVOCs. In the first two sensitivity model experiments, the yields of SOA precursors from oxidation of BVOCs are changed by ±50 %. For the third sensitivity test, the formed oxidation products do not participate in the formation of new particles but are only allowed to condense onto existing aerosols. In the last two sensitivity experiments, the emissions of BVOC compounds (isoprene and monoterpenes) are turned off, one at a time. The goal of the study is to investigate whether it is of importance to treat SOA formation processes correctly in the models rather than to evaluate the correctness of the current treatment in the models. The results show that the impact on the direct radiative effect (DRE) is linked to the changes in the SOA production in the models, where more SOA leads to a stronger DRE and vice versa. However, the magnitude by which the DRE changes (maximally 0.15 W m-2 globally averaged) in response to the SOA changes varies between the models, with EC-Earth displaying the largest changes. The results for the cloud radiative effects (CREs) are more complicated than for the DRE. The changes in CRE differ more among the ESMs, and for some sensitivity experiments they even have different signs. The most sensitive models are NorESM and EC-Earth, which have CRE changes of up to 0.82 W m-2. The varying responses in the different models are connected to where in the aerosol size distributions the changes in mass and number due to SOA formation occur, in combination with the aerosol number concentration levels in the models. We also find that interactive gas-phase chemistry as well as the new particle formation parameterisation has important implications for the DRE and CRE in some of the sensitivity experiments. The results from this study indicate that BVOC-SOA treatment in ESMs can have a substantial impact on the modelled climate but that the sensitivity varies greatly between the models. Since BVOC emissions have changed historically and will continue to change in the future, the spread in model results found in this study implies uncertainty into ESM estimates of aerosol forcing from land-use change and BVOC feedback strengths. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.