Sensitivity of mesoscale modeling of smoke direct radiative effect to the emission inventory: a case study in northern sub-Saharan African region

Feng Zhang,Zhifeng Yang,Charles Ichoku,Cui Ge,Shenjian Su,Christine Wiedinmyer,Edward J Hyer,Arlindo Da Silva,Jun Wang,Johannes W Kaiser,Xiaoyang Zhang,Shobha Kondragunta

doi:10.1088/1748-9326/9/7/075002

Abstract

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15°W–42°E, 13°S–17°N) and monthly averages of column PM2.5 loading, surface PM2.5 concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA.

Highlights

Biomass burning is one of the largest contributors of both gaseous and particulate emissions to the atmosphere, accounting for about 34–38% and 40% of the total global loadings of carbonaceous aerosols and black carbon (BC), respectively (Forster et al 2007)
Meteorology and emission location and amount are significantly different between February and November, the results obtained for February apply to November
The atmospheric diffusion and deposition in the model significantly dampen the large difference in smoke emissions, and large

Summary

Introduction

Biomass burning is one of the largest contributors of both gaseous and particulate emissions to the atmosphere, accounting for about 34–38% and 40% of the total global loadings of carbonaceous aerosols and black carbon (BC), respectively (Forster et al 2007). Despite the enormous progress achieved in satellite remote sensing and atmospheric modeling during the last couple of decades, the overall atmospheric impacts of aerosols originating from biomass burning such as BC and OC (organic carbon) continue to be one of the largest uncertainties in climate research (IPCC 2013). This is partly due to the modeling uncertainties. Another major reason is that fire emissions are often poorly constrained mainly due to their rather sporadic and transient characteristics that cannot all be measured in situ (e.g., IPCC 2013, Ichoku et al 2012)

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Conclusion