Articles | Volume 25, issue 12
https://doi.org/10.5194/acp-25-6497-2025
https://doi.org/10.5194/acp-25-6497-2025
Research article
 | 
27 Jun 2025
Research article |  | 27 Jun 2025

Data-driven modeling of environmental factors influencing Arctic methanesulfonic acid aerosol concentrations

Jakob Boyd Pernov, William H. Aeberhard, Michele Volpi, Eliza Harris, Benjamin Hohermuth, Sakiko Ishino, Ragnhild B. Skeie, Stephan Henne, Ulas Im, Patricia K. Quinn, Lucia M. Upchurch, and Julia Schmale

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Cited articles

Aalto, J., Pirinen, P., Heikkinen, J., and Venäläinen, A.: Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models, Theor. Appl. Climatol., 112, 99–111, https://doi.org/10.1007/s00704-012-0716-9, 2013. 
Andreae, M. O.: Ocean-atmosphere interactions in the global biogeochemical sulfur cycle, Mar. Chem., 30, 1–29, https://doi.org/10.1016/0304-4203(90)90059-L, 1990. 
Andronache, C.: Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions, Atmos. Chem. Phys., 3, 131–143, https://doi.org/10.5194/acp-3-131-2003, 2003. 
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Particulate methanesulfonic acid (MSAp) is vital for the Arctic climate system. Numerical models struggle to reproduce the MSAp seasonal cycle. We evaluate three numerical models and one reanalysis product’s ability to simulate MSAp. We develop data-driven models for MSAp at four Arctic stations. The data-driven models outperform the numerical models and reanalysis product and identified precursor source-, chemical-processing-, and removal-related features as being important for modeling MSAp.
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