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Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce ( 1 ) stronger moisture and aerosol transport to the central United States and ( 2 ) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remote wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important. 

Abstract. Aerosol–cloud interactions remain largely uncertain with respect to predicting theirimpacts on weather and climate. Cloud microphysics parameterization is oneof the factors leading to large uncertainty. Here, we investigate the impactsof anthropogenic aerosols on the convective intensity and precipitation of athunderstorm occurring on 19 June 2013 over Houston with the Chemistryversion of Weather Research and Forecast model (WRF-Chem) using the Morrisontwo-moment bulk scheme and spectral bin microphysics (SBM) scheme. We findthat the SBM predicts a deep convective cloud that shows better agreement withobservations in terms of reflectivity and precipitation compared with theMorrison bulk scheme that has been used in many weather and climate models.With the SBM scheme, we see a significant invigoration effect on convectiveintensity and precipitation by anthropogenic aerosols, mainly throughenhanced condensation latent heating. Such an effect is absent withthe Morrison two-moment bulk microphysics, mainly because the saturationadjustment approach for droplet condensation and evaporation calculationlimits the enhancement by aerosols in (1) condensation latent heat byremoving the dependence of condensation on droplets and aerosols and (2) ice-related processes because the approach leads to stronger warm rain andweaker ice processes than the explicit supersaturation approach. 

Abstract. Changes in land cover and aerosols resulting from urbanization may impactconvective clouds and precipitation. Here we investigate how Houstonurbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the WeatherResearch and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with abuilding energy model (BEM-BEP). We find that Houston urbanization (thejoint effect of both urban land and anthropogenic aerosols) notably enhancesstorm intensity (by ∼ 75 % in maximum vertical velocity) andprecipitation intensity (up to 45 %), with the anthropogenic aerosoleffect more significant than the urban land effect. Urban land effectmodifies convective evolution: speed up the transition from the warm cloudto mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effectbecomes evident after the cloud evolves into the mixed-phase cloud,accelerating the development of storm from the mixed-phase cloud to deepcloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activatingnumerous ultrafine particles at the mixed-phase and deep cloud stages. Thiswork shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective cloudsand precipitation. 

Hailstones are a natural hazard that pose a significant threat to property and are responsible for significant economic losses each year in the United States. Detailed understanding of their characteristics is essential to mitigate their impact. Identifying the dynamic and physical factors contributing to hail formation and hailstone sizes is of great importance to weather and climate prediction and policymakers. In this study, we have analyzed the temporal and spatial variabilities of severe hail occurrences over the U.S. southern Great Plains (SGP) states from 2004 to 2016 using two hail datasets: hail reports from the Storm Prediction Center and the newly developed radar-retrieved maximum expected size of hail (MESH). It is found that severe and significant severe hail occurrences have a considerable year-to-year temporal variability in the SGP region. The interannual variabilities have a strong correspondence with sea surface temperature anomalies over the northern Gulf of Mexico and there is no outlier. The year 2016 is identified as an outlier for the correlations with both El Niño–Southern Oscillation (ENSO) and aerosol loading. The correlations with ENSO and aerosol loading are not statistically robust to inclusion of the outlier 2016. Statistical analysis without the outlier 2016 shows that 1) aerosols that may be mainly from northern Mexico have the largest correlation with hail interannual variability among the three factors and 2) meteorological covariation does not significantly contribute to the high correlation. These analyses warrant further investigations of aerosol impacts on hail occurrence.

 

The net radiative effects of tropical clouds are determined by the evolution of thick, freshly detrained anvil clouds into thin anvil clouds. Thick anvil clouds reduce Earth's energy balance and cool the climate, while thin anvil clouds warm the climate. To determine role of these clouds in climate change we need to understand how interactions of their microphysical and macrophysical properties control their radiative properties. We explore anvil cloud evolution using a cloud‐resolving model in three‐simulation setups of increasing complexity to disentangle the impacts of the various components of diabatic heating and their interaction with cloud‐scale motions. The first phase of evolution and rapid cloud spreading is dominated by latent heating within convective updrafts. After the convective detrainment stops, most of the spreading and thinning of the anvil cloud is driven by cloud radiative processes and latent heating. The combination of radiative cooling at cloud top, latent cooling due to sublimation at cloud base, latent heating due to deposition and radiative heating in between leads to a sandwich‐like, cooling‐heating‐cooling structure. The heating sandwich promotes the development of two within‐anvil convective layers and a double cell circulation, dominated by strong outflow at 12‐km altitude with inflow above and below. Our study reveals how small‐scale processes including convective, microphysical processes, latent and radiative heating interact within the anvil cloud system. The absence or a different representation of only one component results in a significantly different cloud evolution with large impacts on cloud radiative effects.

 

Understanding the formation processes of particles and cloud condensation nuclei (CCN) in pristine environments is a major challenge in assessing the anthropogenic impacts on climate change. Using a state‐of‐the‐art model that systematically simulates the new‐particle formation (NPF) from condensable vapors and multi‐scale transport of chemical species, we find that NPF contributes ∼90% of the particle number and ∼80% of the CCN at 0.5% supersaturation (CCN0.5%) in the pristine Amazon boundary layer during the wet season. The corresponding contributions are only ∼30% and ∼20% during the dry season because of prevalent biomass burning. In both seasons, ∼50% of the NPF‐induced particles and ∼85% of the NPF‐induced CCN0.5% in the boundary layer originate from the long‐range transport of new particles formed hundreds to thousands of kilometers away. Moreover, about 50%–65% of the NPF‐induced particles and 35%–50% of the NPF‐induced CCN0.5% originate from the downward transport of new particles formed aloft.

 

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations among seven state-of-the-art cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas, are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced updraft changes. The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5%–15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~−5% to 0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

 

Aerosols have significant and complex impacts on regional climate in East Asia. Cloud‐aerosol‐precipitation interactions (CAPI) remain most challenging in climate studies. The quantitative understanding of CAPI requires good knowledge of aerosols, ranging from their formation, composition, transport, and their radiative, hygroscopic, and microphysical properties. A comprehensive review is presented here centered on the CAPI based chiefly, but not limited to, publications in the special section named EAST‐AIRcpc concerning (1) observations of aerosol loading and properties, (2) relationships between aerosols and meteorological variables affecting CAPI, (3) mechanisms behind CAPI, and (4) quantification of CAPI and their impact on climate. Heavy aerosol loading in East Asia has significant radiative effects by reducing surface radiation, increasing the air temperature, and lowering the boundary layer height. A key factor is aerosol absorption, which is particularly strong in central China. This absorption can have a wide range of impacts such as creating an imbalance of aerosol radiative forcing at the top and bottom of the atmosphere, leading to inconsistent retrievals of cloud variables from space‐borne and ground‐based instruments. Aerosol radiative forcing can delay or suppress the initiation and development of convective clouds whose microphysics can be further altered by the microphysical effect of aerosols. For the same cloud thickness, the likelihood of precipitation is influenced by aerosols: suppressing light rain and enhancing heavy rain, delaying but intensifying thunderstorms, and reducing the onset of isolated showers in most parts of China. Rainfall has become more inhomogeneous and more extreme in the heavily polluted urban regions.