Abstract. Most previous modeling studies about black carbon (BC) transport and its impact over the Tibetan Plateau (TP) conducted simulations with horizontal resolutions coarser than 20 km that may not be able to resolve the complex topography of the Himalayas well. In this study, the two experiments covering all of the Himalayas with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) at the horizontal resolution of 4 km but with two different topography datasets (4 km complex topography and 20 km smooth topography) are conducted for pre-monsoon season (April 2016) to investigate the impacts of topography on modeling the transport and distribution of BC over the TP. Both experiments show the evident accumulation of aerosols near the southern Himalayas during the pre-monsoon season, consistent with the satellite retrievals. The observed episode of high surface BC concentration at the station near Mt. Everest due to heavy biomass burning near the southern Himalayas is well captured by the simulations. The simulations indicate that the prevailing upflow across the Himalayas driven by the large-scale westerly and small-scale southerly circulations during the daytime is the dominant transport mechanism of southern Asian BC into the TP, and it is much stronger than that during the nighttime. The simulation with the 4 km topography resolves more valleys and mountain ridges and shows that the BC transport across the Himalayas can overcome the majority of mountain ridges, but the valley transport is more efficient. The complex topography results in stronger overall cross-Himalayan transport during the simulation period primarily due to the strengthened efficiency of near-surface meridional transport towards the TP, enhanced wind speed at some valleys and deeper valley channels associated with larger transported BC mass volume. This results in 50 % higher transport flux of BC across the Himalayas and 30 %–50 % stronger BC radiative heating in the atmosphere up to 10 km over the TP from the simulation with the 4 km complex topography than that with the 20 km smoother topography. The different topography also leads to different distributions of snow cover and BC forcing in snow. This study implies that the relatively smooth topography used by the models with resolutions coarser than 20 km may introduce significant negative biases in estimating light-absorbing aerosol radiative forcing over the TP during the pre-monsoon season. Highlights. The black carbon (BC) transport across the Himalayas can overcome the majority of mountain ridges, but the valley transport is much more efficient during the pre-monsoon season. The complex topography results in stronger overall cross-Himalayan transport during the study period primarily due to the strengthened efficiency of near-surface meridional transport towards the TP, enhanced wind speed at some valleys and deeper valley channels associated with larger transported BC mass volume. The complex topography generates 50 % higher transport flux of BC across the Himalayas and 30 %–50 % stronger BC radiative heating in the atmosphere up to 10 km over the Tibetan Plateau (TP) than the smoother topography, which implies that the smooth topography used by the models with relatively coarse resolution may introduce significant negative biases in estimating BC radiative forcing over the TP during the pre-monsoon season. The different topography also leads to different distributions of snow cover and BC forcing in snow over the TP.

Abstract. Diurnal variation of surface PM2.5 concentration (diurnal PM2.5) could dramatically affect aerosol radiative and health impacts and can also well reflect the physical and chemical mechanisms of air pollution formation and evolution. So far, diurnal PM2.5 and its modeling capability over East China have not been investigated and therefore are examined in this study. Based on the observations, the normalized diurnal amplitude of surface PM2.5 concentrations averaged over East China is weakest (∼1.2) in winter and reaches ∼1.5 in other seasons. The diurnal PM2.5 shows the peak concentration during the night in spring and fall and during the daytime in summer. The simulated diurnal PM2.5 with WRF-Chem and its contributions from multiple physical and chemical processes are examined in the four seasons. The simulated diurnal PM2.5 with WRF-Chem is primarily controlled by planetary boundary layer (PBL) mixing and emission variations and is significantly overestimated against the observation during the night. This modeling bias is likely primarily due to the inefficient PBL mixing of primary PM2.5 during the night. The simulated diurnal PM2.5 is sensitive to the PBL schemes and vertical-layer configurations with WRF-Chem. Besides the PBL height, the PBL mixing coefficient is also found to be the critical factor determining the PBL mixing of pollutants in WRF-Chem. With reasonable PBL height, the increase in the lower limit of the PBL mixing coefficient during the night can significantly reduce the modeling biases in diurnal PM2.5 and also the mean concentrations, particularly in the major cities of East China. It can also reduce the modeling sensitivity to the PBL vertical-layer configurations. The diurnal variation and injection height of anthropogenic emissions also play roles in simulating diurnal PM2.5, but the impact is relatively smaller than that from the PBL mixing. This study underscores that more efforts are needed to improve the boundary mixing process of pollutants in models with observations of PBL structure and mixing fluxes in addition to PBL height, in order to simulate reasonably the diurnal PM2.5 over East China. The diurnal variation and injection height of anthropogenic emissions must also be included to simulate the diurnal PM2.5 over East China.

Abstract. Biogenic volatile organic compounds (BVOCs) simulated by current air quality and climate models still have large uncertainties, which can influence atmospheric chemistry and secondary pollutant formation. These modeling sensitivities are primarily due to two sources. One originates from different treatments in the physical and chemical processes associated with the emission rates of BVOCs. The other is errors in the specification of vegetation types and their distribution over a specific region. In this study, the version of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) updated by the University of Science and Technology of China (USTC version of WRF-Chem) from the public WRF-Chem(v3.6) is used. The modeling results over eastern China with different versions (v1.0, v2.0, v3.0) of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) in WRF-Chem are examined or documented. Sensitivity experiments with these three versions of MEGAN and two vegetation datasets are conducted to investigate the difference of three MEGAN versions in modeling BVOCs and its dependence on the vegetation distributions. The experiments are also conducted for spring (April) and summer (July) to examine the seasonality of the modeling results. The results indicate that MEGAN v3.0 simulates the largest amount of biogenic isoprene emissions over eastern China. The different performance among MEGAN versions is primarily due to their different treatments of applying emission factors and vegetation types. In particular, the results highlight the importance of considering the sub-grid vegetation fraction in estimating BVOC emissions over eastern China, which has a large area of urbanization. Among all activity factors, the temperature-dependent factor dominates the seasonal change of activity factor in all three versions of MEGAN, while the different response to the leaf area index (LAI) change determines the difference among the three versions in seasonal variation of BVOC emissions. The simulated surface ozone concentration due to BVOCs can be significantly different (ranging from 1 to more than 10 ppbv in some regions) among the experiments with three versions of MEGAN, which is mainly due to their impacts on surface VOCs and NOx concentrations. Theoretically MEGAN v3.0 that is coupled with the land surface scheme and considers the sub-grid vegetation effect should overcome previous versions of MEGAN in WRF-Chem. However, considering uncertainties of retrievals and anthropogenic emissions over eastern China, it is still difficult to apply satellite retrievals of formaldehyde and/or limited sparse in situ observations to constrain the uncertain parameters or functions in BVOC emission schemes and their impacts on photochemistry and ozone production. More accurate vegetation distribution and measurements of biogenic emission fluxes and species concentrations are still needed to better evaluate and optimize models.

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Two 5‐year (2010–2014) quasi‐global simulations using the Weather Research and Forecasting model coupled with Chemistry have been analyzed to quantify the impacts of atmospheric rivers (ARs) on aerosols in the western United States (U.S.). We find that AR days have reduced trans‐Pacific as well as U.S. aerosol mass because of enhanced rainfall and hence, wet removal of aerosols, compared to non‐AR days. ARs reduce trans‐Pacific aerosol mass through the cyclonic circulation that shifts the aerosol transport pathway southward and brings cleaner air from the north. However, ARs have larger impact on aerosols that originate over the U.S., which are concentrated closer to the surface compared to trans‐Pacific aerosols that are distributed more uniformly with altitude. While dust and sulfates dominate the mass for both trans‐Pacific and U.S. aerosols, ARs reduce dust composition fractions of trans‐Pacific aerosols but the AR impacts on composition fractions of U.S. aerosols are more variable.