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    Aerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany
    (Katlenburg-Lindau : EGU, 2022) Wang, Yuan; Henning, Silvia; Poulain, Laurent; Lu, Chunsong; Stratmann, Frank; Wang, Yuying; Niu, Shengjie; Pöhlker, Mira L.; Herrmann, Hartmut; Wiedensohler, Alfred
    Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, NCCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1% to 0.7%, the median NCCN increases from 399 to 2144cm-3, which represents 10% to 48% of the total particle number concentration with a diameter range of 10-800nm, while the median hygroscopicity factor (κ) and critical diameter (Dc) decrease from 0.27 to 0.19 and from 176 to 54nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SSCombining double low line0.1%, the median NCCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (Dp) increases, κ increases at Dp of 1/440 to 100nm and almost stays constant at Dp of 100 to 200nm, whereas the degree of the external mixture keeps decreasing at Dp of 1/440 to 200nm. The relationships of κ vs. Dp and degree of mixing vs. Dp were both fitted well by a power-law function. (4) Size-resolved κ improves the NCCN prediction. We recommend applying the κ-Dp power-law fit for NCCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the NCCN (AR) vs. SS relationships. The κ-Dp power-law fit measured at Melpitz could be applied to predict NCCN for other rural regions. For the purpose of improving the prediction of NCCN, long-term monodisperse CCN measurements are still needed to obtain the κ-Dp relationships for different regions and their seasonal variations.
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    Status and future of numerical atmospheric aerosol prediction with a focus on data requirements
    (Katlenburg-Lindau : EGU, 2018) Benedetti, Angela; Reid, Jeffrey S.; Knippertz, Peter; Marsham, John H.; Di Giuseppe, Francesca; Rémy, Samuel; Basart, Sara; Boucher, Olivier; Brooks, Ian M.; Menut, Laurent; Mona, Lucia; Laj, Paolo; Pappalardo, Gelsomina; Wiedensohler, Alfred; Baklanov, Alexander; Brooks, Malcolm; Colarco, Peter R.; Cuevas, Emilio; da Silva, Arlindo; Escribano, Jeronimo; Flemming, Johannes; Huneeus, Nicolas; Jorba, Oriol; Kazadzis, Stelios; Kinne, Stefan; Popp, Thomas; Quinn, Patricia K.; Sekiyama, Thomas T.; Tanaka, Taichu; Terradellas, Enric
    Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol-climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term "requirements" is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of "bin" and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.
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    A parameterization of the heterogeneous hydrolysis of N2O5 for mass-based aerosol models: Improvement of particulate nitrate prediction
    (Katlenburg-Lindau : EGU, 2018) Chen, Ying; Wolke, Ralf; Ran, Liang; Birmili, Wolfram; Spindler, Gerald; Schröder, Wolfram; Su, Hang; Cheng, Yafang; Tegen, Ina; Wiedensohler, Alfred
    The heterogeneous hydrolysis of N2O5 on the surface of deliquescent aerosol leads to HNO3 formation and acts as a major sink of NOx in the atmosphere during night-time. The reaction constant of this heterogeneous hydrolysis is determined by temperature (T), relative humidity (RH), aerosol particle composition, and the surface area concentration (S). However, these parameters were not comprehensively considered in the parameterization of the heterogeneous hydrolysis of N2O5 in previous mass-based 3-D aerosol modelling studies. In this investigation, we propose a sophisticated parameterization (NewN2O5) of N2O5 heterogeneous hydrolysis with respect to T, RH, aerosol particle compositions, and S based on laboratory experiments. We evaluated closure between NewN2O5 and a state-of-the-art parameterization based on a sectional aerosol treatment. The comparison showed a good linear relationship (R Combining double low line 0.91) between these two parameterizations. NewN2O5 was incorporated into a 3-D fully online coupled model, COSMO-Muscat, with the mass-based aerosol treatment. As a case study, we used the data from the HOPE Melpitz campaign (10-25 September 2013) to validate model performance. Here, we investigated the improvement of nitrate prediction over western and central Europe. The modelled particulate nitrate mass concentrations ([NO3-]) were validated by filter measurements over Germany (Neuglobsow, Schmücke, Zingst, and Melpitz). The modelled [NO3-] was significantly overestimated for this period by a factor of 5-19, with the corrected NH3 emissions (reduced by 50 %) and the original parameterization of N2O5 heterogeneous hydrolysis. The NewN2O5 significantly reduces the overestimation of [NO3-] by ∼ 35 %. Particularly, the overestimation factor was reduced to approximately 1.4 in our case study (12, 17-18 and 25 September 2013) when [NO3-] was dominated by local chemical formations. In our case, the suppression of organic coating was negligible over western and central Europe, with an influence on [NO3-] of less than 2 % on average and 20 % at the most significant moment. To obtain a significant impact of the organic coating effect, N2O5, SOA, and NH3 need to be present when RH is high and T is low. However, those conditions were rarely fulfilled simultaneously over western and central Europe. Hence, the organic coating effect on the reaction probability of N2O5 may not be as significant as expected over western and central Europe.