Chemical cloud processing has the potential to substantially modify atmospheric aerosol properties and influence air pollutant lifetimes, yet these processes remain challenging to empirically quantify from observations. Previous observational evidence have largely relied on short-term aircraft campaigns, providing only episodic snapshots of cloud–aerosol interactions. Here, we demonstrate that continuous ground-based observations at the SMEAR II boreal forest station enable the identification and characterization of cloud-processed aerosols over multi-year timescales. We show that bimodal aerosol number size distributions exhibiting a pronounced local minimum between the Aitken and accumulation modes –commonly referred to as the Hoppel minimum– are closely linked to the presence of clouds over the boreal forest. These bimodal distributions serve as efficient proxies for cloud-processed aerosols, allowing their physicochemical properties to be examined using long-term in-situ data. This approach provides a novel framework for studying cloud processing effects as an important, long-term complement to aircraft-based observations. Our analysis reveals that cloud processing leads to a clear enrichment of sulfate aerosol mass in the accumulation mode, while impacts on organic aerosol mass concentration and chemical composition remain insignificant. The observed impacts of cloud processing on aerosol composition are consistent with previous estimates derived from trajectory-based analyses, while extending them to a statistically robust, long-term observational context.