Abstract. An accurate representation of biomass burning aerosol emissions is essential in Earth System Models to capture aerosol properties and reduce uncertainties in their interactions with radiation and climate. Sources of wildfire smoke include both widespread prevalence of numerous small fires and more extreme episodic events, such as the unprecedented Californian wildfires of September 2020. Our global modelling study evaluates how well aerosol emissions from extreme wildfires are captured in the UK Earth System Model (UKESM), alongside those from other fires. Running with daily emissions from Global Fire Emission Database v.4.1s (GFED4.1s) enables a realistic simulation of the thick smoke plumes from the Californian fires and large boreal fires more generally, with little overall mean bias error (−0.08) in aerosol optical depths (AODs) between UKESM and collocated VIIRS observations (Western US, September 2020). Modelled AODs were biased low across other regions in 2020 (e.g. savannah, mean bias error = −0.48) dominated by fires with lower fuel consumption, unless emissions were scaled up by a factor of 2 (mean bias error = −0.15). We therefore develop a means of selectively scaling up aerosol emissions from GFED4.1s pixels with lower area-averaged daily dry matter consumption (DM) and not scaling those with higher daily DM, associated with extremely large or intense fires. Applying daily rather than monthly-mean emissions was also found crucial in capturing the spatial and temporal variability of AOD and instantaneous radiative forcing (IRF) during extreme events. These approaches ensure both means and extremes in biomass burning smoke are well represented.
Quaye et al. (Mon,) studied this question.