Cloud microphysics parametrizations control the transfer of water between phases and hydrometeor species in numerical weather prediction and climate models. As a fundamental component of weather modelling systems cloud microphysics can determine the intensity and timing of precipitation, the extent and longevity of cloud cover and its impact on radiative balance, and directly influence near surface weather metrics such as temperature and wind. In this paper we introduce and demonstrate the performance of a double moment cloud microphysical scheme (CASIM: Cloud AeroSol Interacting Microphysics) in both midlatitude and tropical settings using the same model configuration. Comparisons are made against a control configuration using the current operational single moment cloud microphysics, and CASIM configurations that use fixed in‐cloud droplet number or compute cloud droplet number concentration from the aerosol environment. We demonstrate that configuring CASIM as a single moment scheme results in precipitation rate histograms that match the operational single moment microphysics. In the midlatitude setting, results indicate that CASIM performs as well as the single moment microphysics configuration, but improves certain aspects of the surface precipitation field such as greater extent of light (1 mm hr) rain around frontal precipitation features. In the tropical setting, CASIM outperforms the single moment cloud microphysics as evident from improved comparison with radar derived precipitation rates.

We perform a model intercomparison of summertime high Arctic ( > 80° N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm⁻³. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts autoconversion rates. Our results therefore suggest that properly estimating aerosol–cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures, and atmospheric stability need to be considered for weather and climate predictions in this region.

Aerosol mixing state significantly affects concentrations of cloud condensation nuclei (CCN), wet removal rates, thermodynamic properties, heterogeneous chemistry, and aerosol optical properties, with implications for human health and climate. Over the last two decades, significant research effort has gone into finding computationally-efficient methods for representing the most important aspects of aerosol mixing state in air pollution, weather prediction, and climate models. In this review, we summarize the interactions between mixing-state and aerosol hygroscopicity, optical properties, equilibrium thermodynamics and heterogeneous chemistry. We focus on the effects of simplified assumptions of aerosol mixing state on CCN concentrations, wet deposition, and aerosol absorption. We also summarize previous approaches for representing aerosol mixing state in atmospheric models, and we make recommendations regarding the representation of aerosol mixing state in future modelling studies.

New-particle formation in the plumes of coal-fired power plants and other anthropogenic sulfur sources may be an important source of particles in the atmosphere. It remains unclear, however, how best to reproduce this formation in global and regional aerosol models with grid-box lengths that are 10s of kilometers and larger. The predictive power of these models is thus limited by the resultant uncertainties in aerosol size distributions. In this paper, we focus on sub-grid sulfate aerosol processes within coal-fired power plant plumes: the sub-grid oxidation of SO₂ with condensation of H₂SO₄ onto newly-formed and pre-existing particles. We have developed a modeling framework with aerosol microphysics in the System for Atmospheric Modelling (SAM), a Large-Eddy Simulation/Cloud-Resolving Model (LES/CRM). The model is evaluated against aircraft observations of new-particle formation in two different power-plant plumes and reproduces the major features of the observations. We show how the downwind plume aerosols can be greatly modified by both meteorological and background aerosol conditions. In general, new-particle formation and growth is greatly reduced during polluted conditions due to the large pre-existing aerosol surface area for H₂SO₄ condensation and particle coagulation. The new-particle formation and growth rates are also a strong function of the amount of sunlight and NO_x since both control OH concentrations. The results of this study highlight the importance for improved sub-grid particle formation schemes in regional and global aerosol models.

Biomass-burning aerosols have a significant effect on global and regional aerosol climate forcings. To model the magnitude of these effects accurately requires knowledge of the size distribution of the emitted and evolving aerosol particles. Current biomass-burning inventories do not include size distributions, and global and regional models generally assume a fixed size distribution from all biomass-burning emissions. However, biomass-burning size distributions evolve in the plume due to coagulation and net organic aerosol (OA) evaporation or formation, and the plume processes occur on spacial scales smaller than global/regional-model grid boxes. The extent of this size-distribution evolution is dependent on a variety of factors relating to the emission source and atmospheric conditions. Therefore, accurately accounting for biomass-burning aerosol size in global models requires an effective aerosol size distribution that accounts for this sub-grid evolution and can be derived from available emission-inventory and meteorological parameters. In this paper, we perform a detailed investigation of the effects of coagulation on the aerosol size distribution in biomass-burning plumes. We compare the effect of coagulation to that of OA evaporation and formation. We develop coagulation-only parameterizations for effective biomass-burning size distributions using the SAM-TOMAS large-eddy simulation plume model. For the most-sophisticated parameterization, we use the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) to build a parameterization of the aged size distribution based on the SAM-TOMAS output and seven inputs: emission median dry diameter, emission distribution modal width, mass emissions flux, fire area, mean boundary-layer wind speed, plume mixing depth, and time/distance since emission. This parameterization was tested against an independent set of SAM-TOMAS simulations and yields R² values of 0.83 and 0.89 for D_pm and modal width, respectively. The size distribution is particularly sensitive to the mass emissions flux, fire area, wind speed, and time, and we provide simplified fits of the aged size distribution to just these input variables. The simplified fits were tested against 11 aged biomass-burning size distributions observed at the Mt. Bachelor Observatory in August 2015. The simple fits captured over half of the variability in observed D_pm and modal width even though the freshly emitted D_pm and modal widths were unknown. These fits may be used in global and regional aerosol models. Finally, we show that coagulation generally leads to greater changes in the particle size distribution than OA evaporation/formation does, using estimates of OA production/loss from the literature.

Nucleation in coal-fired power-plant plumes can greatly contribute to particle number concentrations near source regions. The changing emissions rates of SO₂ and NO_x due to pollution-control technologies over recent decades may have had a significant effect on aerosol formation and growth in the plumes with ultimate implications for climate and human health. We use the System for Atmospheric Modeling (SAM) large-eddy simulation model with the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm to model the nucleation in plumes of coal-fired plants. We test a range of cases with varying emissions to simulate the implementation of emissions-control technologies between 1997 and 2010. We start by simulating the W. A. Parish power plant (near Houston, TX) during this time period, when NO_x emissions were reduced by ~90% and SO₂ emissions decreased by ~30%. Increases in plume OH (due to the reduced NO_x) produced enhanced SO₂ oxidation and an order-of-magnitude increase in particle nucleation in the plume despite the reduction in SO₂ emissions. These results suggest that NO_x emissions could strongly regulate particle nucleation and growth in power-plant plumes. Next, we test a range of cases with varying emissions to simulate the implementation of SO₂ and NO_x emissions-control technologies. Particle formation generally increases with SO₂ emission, while NO_x shows two different regimes: increasing particle formation with increasing NO_x under low-NO_x emissions and decreasing particle formation with increasing NO_x under high-NO_x emissions. Next, we compare model results with airborne measurements made in the W. A. Parish power-plant plume in 2000 and 2006, confirming the importance of NO_x emissions on new particle formation and highlighting the substantial effect of background aerosol loadings on this process (the more polluted background of the 2006 case caused more than an order-of-magnitude reduction in particle formation in the plume compared to the cleaner test day in 2000). Finally, we calculate particle-formation statistics of 330 coal-fired power plants in the US in 1997 and 2010, and the model results show a median decrease of 19% in particle formation rates from 1997 to 2010 (whereas the W. A. Parish case study showed an increase). Thus, the US power plants, on average, show a different result than was found for the W. A. Parish plant specifically, and it shows that the strong NO_x controls (90% reduction) implemented at the W. A. Parish plant (with relatively weak SO₂ emissions reductions, 30%) are not representative of most power plants in the US during the past 15 yr. These results suggest that there may be important climate implications of power-plant controls due to changes in plume chemistry and microphysics, but the magnitude and sign of the aerosol changes depend greatly on the relative reductions in NO_x and SO₂ emissions in each plant. More extensive plume measurements for a range of emissions of SO₂ and NO_x and in varying background aerosol conditions are needed, however, to better quantify these effects.