Matthew Boyer, Diego Aliaga, Jakob Boyd Pernov, Hélène Angot, Lauriane L. J. Quéléver, Lubna Dada, Benjamin Heutte, Manuel Dall'Osto, David C. S. Beddows, Zoé Brasseur, Ivo Beck, Silvia Bucci, Marina Duetsch, Andreas Stohl, Tiia Laurila, Eija Asmi, Andreas Massling, Daniel Charles Thomas, Jakob Klenø Nøjgaard, Tak Chan, Sangeeta Sharma, Peter Tunved, Radovan Krejci, Hans Christen Hansson, Federico Bianchi, Katrianne Lehtipalo, Alfred Wiedensohler, Kay Weinhold, Markku Kulmala, Tuukka Petäjä, Mikko Sipilä, Julia Schmale, Tuija Jokinen, European Commission, Academy of Finland, Department of Energy (US), Swiss Polar Institute, Agencia Estatal de Investigación (España), Institute for Atmospheric and Earth System Research (INAR), and Polar and arctic atmospheric research (PANDA)
27 pages, 12 figures, supplement https://doi.org/10.5194/acp-23-389-2023.-- Data availability: All data sets used in this work that were obtained during the MOSAiC campaign will be made publicly available by 1 January 2023 via PANGAEA (https://www.pangaea.de/, last access: June 2022) or are already publicly available in the Department of Energy Atmospheric Radiation Measurement program (ARM) user facility data discovery tool (https://adc.arm.gov/discovery/#/, last access: March 2022). Data from the PANGAEA archive include the following. Meteorological observations from Polarstern: Schmithüsen, H.: Continuous meteorological surface measurement during POLARSTERN cruise PS122/1. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.935221, 2021a. Schmithüsen, H.: Continuous meteorological surface measurement during POLARSTERN cruise PS122/2. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.935222, 2021b. Schmithüsen, H.: Continuous meteorological surface measurement during POLARSTERN cruise PS122/3. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.935223, 2021c. Schmithüsen, H.: Continuous meteorological surface measurement during POLARSTERN cruise PS122/4. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.935224, 2021d. Schmithüsen, H.: Continuous meteorological surface measurement during POLARSTERN cruise PS122/5. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.935225, 2021e. Black carbon (BC): Heutte, B., Beck, I., Quéléver, L., Jokinen, T., Laurila, T., Dada, L., Schmale, J.: Equivalent black carbon concentration in 10 minutes time resolution, measured in the Swiss container during MOSAiC 2019/2020, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.952251, 2022. Particle number concentration (CPC3025): Beck, I., Quéléver, L., Laurila, T., Jokinen, T., and Schmale, J.: Continuous corrected particle number concentration data in 10 sec resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.941886, 2022b. The ARM data include the following: Kuang, C., Singh, A., and Howie, J.: Scanning mobility particle sizer (AOSSMPS), ARM [data set], https://doi.org/10.5439/1476898, 2022. Kuang, C., Salwen, C., Boyer, M., and Singh, A.: Condensation Particle Counter (AOSCPCF), ARM [data set], https://doi.org/10.5439/1046184, 2022. The land-based PNSD data: Alert: Personal communication from Tak Chan and Sangeeta Sharma, 2022 (for details, see Croft et al., 2016). Villum: Personal communication from Jakob Boyd Pernov, 2022 (for details, see Nguyen et al., 2016). Zeppelin: Personal communication from Peter Tunved, 2022 (for details, see Tunved et al., 2013). Tiksi: Personal communication from Eija Asmi, 2022 (for details, see Asmi et al., 2016). Utqiaġvik: Freud, E., Krejci, R., Tunved, P., Leaitch, W. R., Nguyen, Q. T., Massling, A., Skov, H., and Barrie, L.: Hourly mean homogenised (dry diameter range 20 to 500 nm) observations of aerosol number size distributions from station Barrow, 2007-09-20 to 2015-07-09, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.877329, 2017b. The land-based BC data: Villum: Personal communications from Daniel Thomas, Jakob Klenø Nøjgaard, and Andreas Massling, 2022 (for details, see Thomas et al., 2022). NOAA Barrow Atmospheric Baseline Observatory (Utqiaġvik) during 2020: personal communication from Elisabeth Andrews, 2022 (for processing details, see Schmale et al., 2022). Gruvebadet. The PSAP data are accessible at the Italian Arctic Data Center operated by the National Research Council of Italy: https://data.iadc.cnr.it/erddap/tabledap/ebc_2010_2020.html (last access: December 2021, refer to Schmale et al., 2022, for additional details). All other BC data sets used in this work will be made publicly available on EBAS (http://ebas-data.nilu.no/, last access: December 2021, refer to Schmale et al., 2022, for additional details). The Arctic Oscillation (AO) data are publicly available from the NOAA and the National Weather Service: https://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ao.shtml (last access: June 2022). An archive of the FLEXPART model output and quick looks for the whole campaign can be found at https://img.univie.ac.at/webdata/mosaic (last access: March 2022), The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019–2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January–March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding link, This research has been supported by the Academy of Finland (grant no. 337552), Horizon 2020 (EMME-CARE, grant no. 856612), the US Department of Energy (grant no. DE-SC0022046), and the Swiss Polar Institute (grant no. 188478), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)