Year: 2026
Type: article
Abstract: The modeling study investigated the impact of the 2023 Canadian wildfire aerosols (primarily black carbon and organic aerosol) on weather forecasts, concluding that incorporating real-time aerosol forcing improved model skill over using a climatology. Experiments without real-time data severely underestimated the Aerosol Optical Depth (AOD), an error mitigated by including the forcing or by using the coupled atmosphere-chemistry model. The aerosols exerted a strong direct radiative effect, reducing the surface downward shortwave (SW) flux and causing a corresponding surface cooling over the wildfire region. Furthermore, including aerosol-cloud interactions amplified this cooling and led to an increase in 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 forecast skill (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.
Source: Atmosphere
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7141561117
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