This modeling study investigates the impact of the 2023 Canadian wildfire aerosols (primarily black carbon and organic aerosol) on weather forecasts, concluding that incorporating real-time aerosol forcing improves model performance over using climatology. Experiments without real-time data severely underestimated aerosol optical depth (AOD), an error mitigated by including the forcing or using the coupled atmosphere–chemistry model. The aerosols exerted a strong direct radiative effect, reducing surface downward shortwave (SW) flux and generating corresponding surface cooling over the wildfire region. Furthermore, including aerosol–cloud interactions amplified this cooling and led to an increase in the overall cloud fraction and precipitation, illustrating complex indirect effects. While these physical improvements enhanced the representation of the atmosphere, the positive impact on overall medium-range forecasting performance (5–10 days) was modest, suggesting that the benefits of accurately representing wildfire feedback on the coupled Earth system are achieved through relatively slow processes, such as radiation feedback.
Cheng et al. (2026) studied this question.