2019
DOI: 10.1029/2018jd029900
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Sensitivity of Simulated Aerosol Properties Over Eastern North America to WRF‐Chem Parameterizations

Abstract: Aerosol properties and their climatic feedbacks are characterized by high uncertainty in both global and regional model simulations. We explore sources of uncertainty in the representation of aerosol properties using an ensemble of simulations performed at 24‐km resolution with WRF‐Chem over eastern North America. The sensitivity of aerosol optical depth (AOD) and near‐surface fine particle concentrations (PM2.5) to planetary boundary layer (PBL) and aerosol schemes (modal with secondary organic aerosol versus… Show more

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Cited by 23 publications
(31 citation statements)
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References 147 publications
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“…This negative bias in these simulations of extreme AOD events with the MOSAIC‐sectional aerosol scheme is consistent with the negative bias in mean AOD from a long‐term simulation by Crippa et al. (2019). For five of the six cases the bias is larger in the time‐averaged, spatially averaged median AOD than the mean AOD.…”
Section: Resultssupporting
confidence: 89%
“…This negative bias in these simulations of extreme AOD events with the MOSAIC‐sectional aerosol scheme is consistent with the negative bias in mean AOD from a long‐term simulation by Crippa et al. (2019). For five of the six cases the bias is larger in the time‐averaged, spatially averaged median AOD than the mean AOD.…”
Section: Resultssupporting
confidence: 89%
“…Consistent with prior research, near‐surface PM 2.5 concentrations exhibit higher sensitivity to emission changes between 2005 and 2015 (Crippa et al., 2019). More grid cells exhibit significantly different PM 2.5 concentrations in simulations with all EF applied than are manifest in the AOD results (cf.…”
Section: Resultssupporting
confidence: 88%
“…This overprediction could lead to mismatches between AOD and PM 2.5 in models using this code. Curci et al (2019) evaluated black carbon absorption for an ensemble of models over Europe and North America, finding that biases were driven by the mixing state assumptions in the optical properties computations.…”
Section: Introductionmentioning
confidence: 99%