AbstractThe prediction skill of the regional aerosol–climate model REMO-HAM was assessed against the black carbon (BC) concentration measurements from five locations in Finland, with focus on Hyytiälä station for the year 2005. We examined to what extent the model is able to reproduce the measurements using several statistical tools: median comparison, overlap coefficient (OVL; the common area under two probability distributions curves) and Z score (a measure of standard deviation, shape and spread of the distributions). The results of the statistics showed that the model is biased low. The local and regional emissions of BC have a significant contribution, and the model tendency to flatten the observed BC is most likely dominated by the lack of domestic burning of biofuel in the emission inventories. A further examination of the precipitation data from both measurements and model showed that there is no correlation between REMO's excessive precipitation and BC underestimation. This suggests that the excessive wet removal is not the main cause of the low black carbon concentration output. In addition, a comparison of wind directions in relation with high black carbon concentrations shows that REMO-HAM is able to predict the BC source directions relatively well. Cumulative black carbon deposition fluxes over Finland were estimated, including the deposition on snow.