Abstract Over the past decade, the number of studies that investigate aerosol–cloud interactions has increased considerably. Although tremendous progress has been made to improve the understanding of ...basic physical mechanisms of aerosol–cloud interactions and reduce their uncertainties in climate forcing, there is still poor understanding of 1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, 2) the feedbacks between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and 3) the significance of cloud–aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol–cloud interactions and discusses the significances of aerosol impacts on radiative forcing and precipitation extremes associated with different cloud systems. The authors summarize the main obstacles preventing the science from making a leap—for example, the lack of concurrent profile measurements of cloud dynamics, microphysics, and aerosols over a wide region on the observation side and the large variability of cloud microphysics parameterizations resulting in a large spread of modeling results on the modeling side. Therefore, large efforts are needed to escalate understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties and cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed.
Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, ...precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ~27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 W m(-2)) and a surface cooling (-5 to -8 W m(-2)). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.
Extreme weather events have become more frequent and are likely linked to increases in greenhouse gases and aerosols, which alter the Earth's radiative balance and cloud processes. On 8–9 July 2013, ...a catastrophic flood devastated the mountainous area to the northwest of the Sichuan Basin. Atmospheric simulations at a convection‐permitting scale with aerosols and chemistry included show that heavy air pollution trapped in the basin significantly enhances the rainfall intensity over the mountainous areas through “aerosol‐enhanced conditional instability.” That is, aerosols suppress convection by absorbing solar radiation and increasing atmospheric stability in the basin during daytime. This allows excess moist air to be transported to the mountainous areas and orographically lifted, generating strong convection and extremely heavy precipitation at night. We show that reducing pollution in the Sichuan Basin can effectively mitigate floods. It is suggested that coupling aerosol with meteorology can be crucial to improve weather forecast in polluted regions.
Key Points
Aerosols contribute to flooding by “aerosol‐enhanced conditional instability”
Reducing pollution (particularly BC) in the Sichuan Basin mitigates floods
Coupling aerosols with meteorology may improve weather forecasts
Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol ...due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron‐sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid‐catalyzed multiphase chemistry of isoprene epoxydiols, particle‐phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process‐related interactions, so that these processes can be accurately represented in atmospheric chemistry‐climate models.
Plain Language Summary
Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, often represents a major fraction of global submicron‐sized atmospheric organic aerosol. Myriad processes affect SOA formation, several of which relate to interactions between natural biogenic emissions and predominantly anthropogenic species such as SO2, NOx, sulfate, nitrate, and ammonium. Many of these key processes are nonlinear and can be synergistic or act to compensate each other in terms of climate forcing. Current atmospheric chemistry‐climate models mostly do not treat these processes. We highlight a number of process‐level mechanisms related to the interactions between anthropogenic and biogenic SOA precursors, for which the corresponding impacts on the radiative effects of SOA need to be investigated in atmospheric chemistry‐climate models. Ultimately, climate models need to capture enough important features of the chemical and dynamic evolution of SOA, in terms of both aerosol number and aerosol mass, as a function of atmospheric variables and anthropogenic perturbations to reasonably predict the spatial and temporal distributions of SOA. A better understanding of SOA formation mechanisms and physical properties is needed to improve estimates of the extent to which anthropogenic emissions and land use changes have modified global aerosol concentrations and size distributions since preindustrial times.
Key Points
We review some important developments in secondary organic aerosol (SOA) that could impact aerosol radiative forcing and response of climate to greenhouse gases
We highlight some of the important processes that involve interactions between natural biogenic emissions and anthropogenic emissions
We discuss fundamental SOA properties volatility and viscosity and their relation to evolution of aerosol mass and number concentrations in the atmosphere
The WRF-Chem model coupled with a single-layer urban canopy model (UCM) is integrated for 5 years at convection-permitting scale to investigate the individual and combined impacts of ...urbanization-induced changes in land cover and pollutant emissions on regional climate in the Yangtze River Delta (YRD) region in eastern China. Simulations with the urbanization effects reasonably reproduced the observed features of temperature and precipitation in the YRD region. Urbanization over the YRD induces an urban heat island (UHI) effect, which increases the surface temperature by 0.53 °C in summer and increases the annual heat wave days at a rate of 3.7 d yr−1 in the major megacities in the YRD, accompanied by intensified heat stress. In winter, the near-surface air temperature increases by approximately 0.7 °C over commercial areas in the cities but decreases in the surrounding areas. Radiative effects of aerosols tend to cool the surface air by reducing net shortwave radiation at the surface. Compared to the more localized UHI effect, aerosol effects on solar radiation and temperature influence a much larger area, especially downwind of the city cluster in the YRD. Results also show that the UHI increases the frequency of extreme summer precipitation by strengthening the convergence and updrafts over urbanized areas in the afternoon, which favor the development of deep convection. In contrast, the radiative forcing of aerosols results in a surface cooling and upper-atmospheric heating, which enhances atmospheric stability and suppresses convection. The combined effects of the UHI and aerosols on precipitation depend on synoptic conditions. Two rainfall events under two typical but different synoptic weather patterns are further analyzed. It is shown that the impact of urban land cover and aerosols on precipitation is not only determined by their influence on local convergence but also modulated by large-scale weather systems. For the case with a strong synoptic forcing associated with stronger winds and larger spatial convergence, the UHI and aerosol effects are relatively weak. When the synoptic forcing is weak, however, the UHI and aerosol effects on local convergence dominate. This suggests that synoptic forcing plays a significant role in modulating the urbanization-induced land-cover and aerosol effects on individual rainfall event. Hence precipitation changes due to urbanization effects may offset each other under different synoptic conditions, resulting in little changes in mean precipitation at longer timescales.
Cloud droplet effective radius (DER) is generally negatively correlated with aerosol optical depth (AOD) as a proxy of cloud condensation nuclei. In this study, cases of positive correlation were ...found over certain portions of the world by analyzing the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products, together with a general finding that DER may increase or decrease with aerosol loading depending on environmental conditions. The slope of the correlation between DER and AOD is driven primarily by water vapor amount, which explains 70% of the variance in our study. Various potential artifacts that may cause the positive relation are investigated including the effects of aerosol swelling, partially cloudy, atmospheric dynamics, cloud three‐dimensional (3‐D) and surface influence effects. None seems to be the primary cause for the observed phenomenon, although a certain degree of influence exists for some of the factors. Analyses are conducted over seven regions around the world representing different types of aerosols and clouds. Only two regions show positive dependence of DER on AOD, near coasts of the Gulf of Mexico and South China Sea, which implies physical processes may at work. Using a 2‐D Goddard Cumulus Ensemble model (GCE) with spectral‐bin microphysics which incorporated a reformulation of the Köhler theory, two possible physical mechanisms are hypothesized. They are related to the effects of slightly soluble organics (SSO) particles and giant cloud condensation nuclei (CCN). Model simulations show a positive correlation between DER and AOD, due to a decrease in activated aerosols with an increasing SSO content. Addition of a few giant CCNs also increases the DER. Further investigations are needed to fully understand and clarify the observed phenomenon.
To better understand the impacts of dust aerosols on deep convective cloud (DCC) systems reported by previous observational studies, a case study in the tropical eastern Atlantic was investigated ...using the Weather Research and Forecasting (WRF) model coupled with a spectral bin microphysics (SBM) model. A detailed set of ice nucleation parameterizations linking ice formation with aerosol particles has been implemented in the SBM. Increasing ice nuclei (IN) concentration in the dust cases results in the formation of more numerous small ice particles in the heterogeneous nucleation regime (between −5 and −38 ∘C) compared to the background (“Clean”) case. Convective updrafts are invigorated by increased latent heat release due to depositional growth and riming of these more numerous particles, which results in increased overshooting and higher convective core top heights. Competition between the more numerous particles for available water vapor during diffusional growth and available smaller crystals and/or drops during collection reduces particle growth rates and shifts precipitation formation to higher altitudes in the heterogeneous nucleation regime. A greater number of large snow particles form in the dust cases, which are transported from the core into the stratiform regime and sediment out quickly. Together with reduced homogeneous ice formation, the stratiform and/or anvil cloud occurrence shifts frequency to warmer temperatures and reduces anvil cloud extents. Total surface precipitation accumulation is reduced proportionally as IN concentration is increased; though the stratiform precipitation accumulation is increased due to greater snow formation and growth, it does not counteract the reduced convective accumulation due to less efficient graupel formation. Radar reflectivity values are increased in the dust cases at temperatures below 0 ∘C in both the convective and stratiform regimes due to more large snow particles, and reduced in the convective core near the surface due to melt of small ice or graupel particles, consistent with case study observations.
The large concentrations of ultrafine particles consistently observed at high altitudes over the tropics represent one of the world’s largest aerosol reservoirs, which may be providing a globally ...important source of cloud condensation nuclei. However, the sources and chemical processes contributing to the formation of these particles remain unclear. Here we investigate new particle formation (NPF) mechanisms in the Amazon free troposphere by integrating insights from laboratory measurements, chemical transport modeling, and field measurements. To account for organic NPF, we develop a comprehensive model representation of the temperature-dependent formation chemistry and thermodynamics of extremely low volatility organic compounds as well as their roles in NPF processes. We find that pure-organic NPF driven by natural biogenic emissions dominates in the uppermost troposphere above 13 km and accounts for 65 to 83% of the column total NPF rate under relatively pristine conditions, while ternary NPF involving organics and sulfuric acid dominates between 8 and 13 km. The large organic NPF rates at high altitudes mainly result from decreased volatility of organics and increased NPF efficiency at low temperatures, somewhat counterbalanced by a reduced chemical formation rate of extremely low volatility organic compounds. These findings imply a key role of naturally occurring organic NPF in high-altitude preindustrial environments and will help better quantify anthropogenic aerosol forcing from preindustrial times to the present day.
Regional climate simulations over the continental United States were conducted for the 2011 warm season using the Weather Research and Forecasting model at convection‐permitting resolution (4 km) ...with two commonly used microphysics parameterizations (Thompson and Morrison). Sensitivities of the simulated mesoscale convective system (MCS) properties and feedbacks to large‐scale environments are systematically examined against high‐resolution geostationary satellite and 3‐D mosaic radar observations. MCS precipitation including precipitation amount, diurnal cycle, and distribution of hourly precipitation intensity are reasonably captured by the two simulations despite significant differences in their simulated MCS properties. In general, the Thompson simulation produces better agreement with observations for MCS upper level cloud shield and precipitation area, convective feature horizontal and vertical extents, and partitioning between convective and stratiform precipitation. More importantly, Thompson simulates more stratiform rainfall, which agrees better with observations and results in top‐heavier heating profiles from robust MCSs compared to Morrison. A stronger dynamical feedback to the large‐scale environment is therefore seen in Thompson, wherein an enhanced mesoscale vortex behind the MCS strengthens the synoptic‐scale trough and promotes advection of cool and dry air into the rear of the MCS region. The latter prolongs the MCS lifetimes in the Thompson relative to the Morrison simulations. Hence, different treatment of cloud microphysics not only alters MCS convective‐scale dynamics but also has significant impacts on their macrophysical properties such as lifetime and precipitation. As long‐lived MCSs produced 2–3 times the amount of rainfall compared to short‐lived ones, cloud microphysics parameterizations have profound impact in simulating extreme precipitation and the hydrologic cycle.
Plain Language Summary
Massive thunderstorms over the Great Plains of the United States have become more frequent and more intense in the past decades. As Earth continues to warm, changes in the characteristics of these massive thunderstorms, which often cause flooding and severe wind damage, have major societal implications. Climate models with spatial resolution comparable to weather forecasting models can now be used to simulate the complex physics in storms and reproduce their climatological properties. However, details of how to represent the cloud microphysical processes remain uncertain, with potential implications for long‐term simulation of climate in regions of convective storms. This study examines the uncertainties associated with cloud microphysics of convective storms in the central United States by using two different microphysical representations and comparing results with a warm‐season satellite and radar observations. Microphysical processes leading to a broader and more realistic storm rainfall areas favor prolonged lifetime of the storms and thus have greater effects on the evolution of the large‐scale circulation and greater potential for storms producing floods, factors important for evaluating the effects of convective storms in a changing climate.
Key Points
Warm season convection‐permitting climate simulations reproduced the observed characteristics of mesoscale convective systems
Macrophysical properties of simulated mesoscale convective systems are sensitive to microphysics parameterizations
Microphysics parameterizations that produce more stratiform rainfall favor longer‐lived convection through stronger dynamical feedbacks
Fires, including wildfires, harm air quality and essential public services like transportation, communication, and utilities. These fires can also influence atmospheric conditions, including ...temperature and aerosols, potentially affecting severe convective storms. Here, we investigate the remote impacts of fires in the western United States (WUS) on the occurrence of large hail (size: ⩾ 2.54 cm) in the central US (CUS) over the 20-year period of 2001–20 using the machine learning (ML), Random Forest (RF), and Extreme Gradient Boosting (XGB) methods. The developed RF and XGB models demonstrate high accuracy (> 90%) and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide, particularly in four states (Wyoming, South Dakota, Nebraska, and Kansas). The key contributing variables identified from both ML models include the meteorological variables in the fire region (temperature and moisture), the westerly wind over the plume transport path, and the fire features (i.e., the maximum fire power and burned area). The results confirm a linkage between WUS fires and severe weather in the CUS, corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.
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