Absorbing aerosols uniquely impact radiation, aerosol transport, and meteorology. This paper quantifies black carbon core and sulphate shell size and mass using decadal measurements of multi-spectral aerosol optical depth, single scattering albedo, and angstrom exponent from Aerosol Robotic Network stations located throughout East, Southeast, and South Asia, in connection with a MIE model. All sites are uniquely characterized into four types: urban, biomass burning, long-range transport, and clean. Unique size and mass probability distributions of both the core and shell are calculated within each classification. Well known urban, biomass burning, and clean sites are all properly identified. Furthermore, two unique sites previously thought to not have multiple characteristics are identified, with urban and biomass burning significant in Beijing and long-range transport significant in the otherwise clean South China Sea at Taiping Island. It is hoped that these results will allow for advances in attribution and radiative forcing studies. Plain Language Summary Black Carbon strongly absorbs visible radiation, leading to unique impacts on atmospheric radiation, climate, the water cycle, and PM2.5. This work attributes different aerosol source characteristics, and further specifies the size distribution and concentration of aerosol black carbon cores and refractive shells. This work uses measurements of aerosol optical depth, single scatter albedo, and angstrom exponent, across multiple different wavelengths of light, in combination with statistics and a MIE model (physical model of aerosol/radiation interaction) using a Core-Shell approximation. The results show that aerosols observed in East, Southeast, and South Asia can be uniquely classified into four types: urban, biomass burning, long-range transport, and clean. These results are consistent in terms of aerosol size and mass at each site within each type of characterization. Furthermore, two unique sites are identified in which a second characteristic occurs some significant fraction of every year, which otherwise was not known or previously identified in the literature. These results are expected to help enhance the understanding of attribution of aerosols, as well as provide specific size and mass details of the aerosols useful to improve radiative forcing models and aerosol impacts on climate change. Key Points Aerosols are categorized into biomass burning, urban, and long-range types over Asia using decadal long multi-spectral measurements Based on multiple Aerosol Robotic Network Single Scatter Albedo measurements and a MIE model, physical characteristics of different aerosol types are deduced Most aerosols are found to be mixed, with two sites having different characteristics during different times of the year

Source attribution of Arctic sulfate and its radiative forcing due to aerosol-radiation interactions (RFari) for 2010-2014 are quantified in this study using the Community Earth System Model equipped with an explicit sulfur source-tagging technique. The model roughly reproduces the seasonal pattern of sulfate but has biases in simulating the magnitude of near-surface concentrations and vertical distribution. Regions that have high emissions and/or are near/within the Arctic present relatively large contributions to Arctic sulfate burden, with the largest contribution from sources in East Asia (27%). Seasonal variations of the contribution to Arctic sulfate burden from remote sources are strongly influenced by meteorology. The mean RFari of anthropogenic sulfate offsets one third of the positive top of the atmosphere (TOA) RFari from black carbon. A 20% global reduction in anthropogenic SO2 emissions leads to a net Arctic TOA forcing increase of +0.019Wm(-2). These results indicate that a joint reduction in BC and SO2 emissions could prevent at least some of the Arctic warming from any future SO2 emission reductions. Sulfate RFari efficiency calculations suggest that source regions with short transport pathways and meteorology favoring longer lifetimes are more efficient in influencing the Arctic sulfate RFari. Based on Arctic climate sensitivity factors, about -0.19K of the Arctic surface temperature cooling is attributed to anthropogenic sulfate, with -0.05K of that from sources in East Asia, relative to preindustrial conditions.

During 19-21 June 2013 a heavy precipitation event affected southern Alberta and adjoining regions, leading to severe flood damage in numerous communities and resulting in the costliest natural disaster in Canadian history. This flood was caused by a combination of meteorological and hydrological factors, which are investigated from weather and climate perspectives with the fifth generation Canadian Regional Climate Model. Results show that the contribution of orographic ascent to precipitation was important, exceeding 30 % over the foothills of the Rocky Mountains. Another contributing factor was evapotranspiration from the land surface, which is found to have acted as an important moisture source and was likely enhanced by antecedent rainfall that increased soil moisture over the northern Great Plains. Event attribution analysis suggests that human induced greenhouse gas increases may also have contributed by causing evapotranspiration rates to be higher than they would have been under pre-industrial conditions. Frozen and snow-covered soils at high elevations are likely to have played an important role in generating record streamflows. Results point to a doubling of surface runoff due to the frozen conditions, while 25 % of the modelled runoff originated from snowmelt. The estimated return time of the 3-day precipitation event exceeds 50 years over a large region, and an increase in the occurrence of similar extreme precipitation events is projected by the end of the 21st century. Event attribution analysis suggests that greenhouse gas increases may have increased 1-day and 3-day return levels of May-June precipitation with respect to pre-industrial climate conditions. However, no anthropogenic influence can be detected for 1-day and 3-day surface runoff, as increases in extreme precipitation in the present-day climate are offset by decreased snow cover and lower frozen water content in soils during the May-June transition months, compared to pre-industrial climate.