<p><strong>Abstract.</strong> We quantify the effective radiative forcing (ERF) of anthropogenic aerosols modelled by the aerosol&#8211;climate model CAM5.3-MARC-ARG. CAM5.3-MARC-ARG is a new configuration of the Community Atmosphere Model version 5.3 (CAM5.3) in which the default aerosol module has been replaced by the two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC). CAM5.3-MARC-ARG uses the default ARG aerosol activation scheme, consistent with the default configuration of CAM5.3. We compute differences between simulations using year-1850 aerosol emissions and simulations using year-2000 aerosol emissions in order to assess the radiative effects of anthropogenic aerosols. We compare the aerosol column burdens, cloud properties, and radiative effects produced by CAM5.3-MARC-ARG with those produced by the default configuration of CAM5.3, which uses the modal aerosol module with three log-normal modes (MAM3). Compared with MAM3, we find that MARC produces stronger cooling via the direct radiative effect, stronger cooling via the surface albedo radiative effect, and stronger warming via the cloud longwave radiative effect. The global mean cloud shortwave radiative effect is similar between MARC and MAM3, although the regional distributions differ. Overall, MARC produces a global mean net ERF of &#8722;1.75&#8201;&#177;&#8201;0.04&#8201;W&#8201;m<sup>&#8722;2</sup>, which is stronger than the global mean net ERF of &#8722;1.57&#8201;&#177;&#8201;0.04&#8201;W&#8201;m<sup>&#8722;2</sup> produced by MAM3. The regional distribution of ERF also differs between MARC and MAM3, largely due to differences in the regional distribution of the cloud shortwave radiative effect. We conclude that the specific representation of aerosols in global climate models, including aerosol mixing state, has important implications for climate modelling.</p>
<p><strong>Abstract.</strong> Fires including peatland burning in Southeast Asia have become a major concern of general public as well as governments in the region. This is because that aerosols emitted from such fires can cause persistent haze events under favorite weather conditions in downwind locations, degrading visibility and causing human health issues. In order to improve our understanding of the spatial-temporal coverage and influence of biomass burning aerosols in Southeast Asia, we have used surface visibility and particulate matter concentration observations, added by decadal long (2002 to 2014) simulations using the Weather Research and Forecasting (WRF) model with a fire aerosol module, driven by high-resolution biomass burning emission inventories. We find that in the past decade, fire aerosols are responsible for nearly all the events with very low visibility (< 7 km), and a substantial fraction of the low visibility events (visibility < 10 km) in the major metropolitan areas of Southeast Asia: 38 % in Bangkok, 35 % in Kuala Lumpur, and 34 % in Singapore. Biomass burnings in Mainland Southeast Asia account for the largest contributor to total fire produced PM<sub>2.5</sub> in Bangkok (99.1 %), while biomass burning in Sumatra is the major contributor to fire produced PM<sub>2.5</sub> in Kuala Lumpur (49 %) and Singapore (41 %). To examine the general situation across the region, we have further defined and derived a new integrated metric for 50 cities of the Association of Southeast Asian Nations, i.e., Haze Exposure Days (HEDs) that measures the annual exposure days of these cities to low visibility (< 10 km) caused by particulate matter pollution. It is shown that HEDs have increased steadily in the past decade across cities with both high and low populations. Fire events are found to be responsible for about half of the total HEDs. Therefore, our result suggests that in order to improve the overall air quality in Southeast Asia, mitigation policies targeting at both biomass and fossil fuel burning sources need to be put in effect.</p>
Abstract. Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNC). However, different activation schemes can exhibit different sensitivities 5 to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC. Although the model produces a reasonable present day CDNC climatology when compared with observations regardless of the scheme used, ∆CDNC between the present and pre-industrial era regionally increase by over 100% in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity lead to a spread of over 0.8 Wm −2 in global average 10 shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom inter-comparison. Model-derived AIE strongly scales with the simulated pre-industrial CDNC burden, and those models with the greatest pre-industrial CDNC tend to have the smallest AIE, regardless of their ∆CDNC. This suggests that present day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of AIE, which will arise from differences in model estimates of the pre-industrial aerosol and cloud climatology.
<p><strong>Abstract.</strong> The Surface PARTiculate mAtter Network (SPARTAN) is a long-term project designed to maximize the chemical and physical information obtained from filter samples collected worldwide. This manuscript discusses the ongoing efforts of SPARTAN to define and quantify major ions and trace metals found in aerosols. Our methods infer the spatial and temporal variability of PM<sub>2.5</sub> in a cost-effective manner; single filters represent multi-day averaged fine particulate matter (PM<sub>2.5</sub>), while an adjacent nephelometer samples air continuously. SPARTAN instruments are collocated with AERONET to better understand the relationship between ground-level PM<sub>2.5</sub> and columnar aerosol optical depth (AOD). <br><br> We have examined the chemical composition of PM<sub>2.5</sub> at 12 globally dispersed, densely populated urban locations and a site at Mammoth Cave (US) National Park used as a baseline comparison. Each SPARTAN location has so far been active between the years 2013 and 2015 over 2 to 22 month periods. These sites have collectively gathered over 10 years of quality aerosol data. The major PM<sub>2.5</sub> constituents across all sites (relative contribution &#177; SD) were ammonium sulfate (20 % &#177; 10 %), crustal material (12 % &#177; 6.2 %), black carbon (11 % &#177; 8.4 %), ammonium nitrate (4.0 % &#177; 2.8 %), sea salt (2.2 % &#177; 1.5 %), trace element oxides (0.9 % &#177; 0.6 %), water (7.2 % &#177; 3.1 %) and residue materials (43 % &#177; 25 %). <br><br> Analysis of filter samples revealed that several PM<sub>2.5</sub> chemical components varied by more than an order of magnitude between sites. Ammonium sulfate ranged from 1.1 &#956;g m<sup>&#8722;3</sup> (Buenos Aires, Argentina) to 17 &#956;g m<sup>&#8722;3</sup> (Kanpur, India [dry season]). Ammonium nitrate ranged from 0.2 &#956;g m<sup>&#8722;3</sup> (Mammoth Cave, in summer) to 6.7 &#956;g m<sup>&#8722;3</sup> (Kanpur, dry season). Equivalent black carbon ranged from 0.7 &#956;g m<sup>&#8722;3</sup> (Mammoth Cave) to 8 &#956;g m<sup>&#8722;3</sup> (Dhaka, Bangladesh and Kanpur). Comparison with coincident measurements from the IMPROVE network at Mammoth Cave yielded a high degree of consistency for daily PM<sub>2.5</sub> (<i>r</i><sup>2</sup> = 0.76, slope = 1.12), daily sulfate (<i>r</i><sup>2</sup> = 0.86, slope = 1.03) and mean fractions of all major PM<sub>2.5</sub> components (within 6 %). Major ions generally agree well with previous studies at the same urban locations (e.g. sulfate fractions agree within 4 % for eight out of 11 collocation comparisons). Enhanced anthropogenic dust fractions in large urban areas (e.g. Singapore, Kanpur, Hanoi and Dhaka) were apparent from high Zn : Al ratios. <br><br> The expected water contribution to aerosols was calculated via the hygroscopicity parameter &#954;<sub>v</sub> for each filter. Mean aggregate values ranged from 0.15 (Manila and Ilorin) to 0.31 (Rehovot); with the latter included a major sulfate event. The all-site parameter mean is 0.19. Chemical composition and water retention in each filter measurement allowed inference of hourly PM<sub>2.5</sub> at 35 % relative humidity by merging with nephelometer measurements. These hourly PM<sub>2.5</sub> estimates compare favorably with a beta attenuation monitor (MetOne) at the nearby US embassy in Beijing, with a coefficient of variation <i>r</i><sup>2</sup> = 0.67 (<i>n</i> = 3167), compared to <i>r</i><sup>2</sup> = 0.62 when &#954;<sub>v</sub> was not considered. SPARTAN continues to provide an open-access database of PM<sub>2.5</sub> compositional filter information and hourly mass collected from a global federation of instruments.</p>
Abstract. The year of 2015 was an extremely dry year for Southeast Asia where the direct impact of a strong El Niño was in play. As a result of this dryness and the relative lack of rainfall, an extraordinary quantity of aerosol particles from biomass burning remained in the atmosphere over the Maritime Continent during the fire season. This study uses the Weather Research and Forecasting model coupled with Chemistry to understand the impacts of these fire particles on cloud microphysics and radiation during the peak biomass burning season in September. Our simulations, one with fire particles and the other without them, cover the entire Maritime Continent region at a cloud-resolving resolution (4 km) for the entire month of September in 2015. The comparison of the simulations shows a clear sign of precipitation enhancement by fire particles through microphysical effects; smaller cloud droplets remain longer in the atmosphere to later form ice crystals, and/or they are more easily collected by ice-phase hydrometeors in comparison to droplets under no fire influences. As a result, the mass of ice-phase hydrometeors increases in the simulation with fire particles, and so does rainfall. On the other hand, the aerosol radiative effect weakly counteracts the invigoration of convection. Clouds are more reflective in the simulation with fire particles as ice mass increases. Combined with the direct scattering of sunlight by aerosols, the simulation with fire particles shows higher albedo over the simulation domain on average. The simulated response of clouds to fire particles in our simulations clearly differs from what was presented by two previous studies that modeled aerosol–cloud interaction in years with different phases of El Niño–Southern Oscillation (ENSO), suggesting a further need for an investigation on the possible modulation of fire–aerosol–convection interaction by ENSO.
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