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  1. Free, publicly-accessible full text available July 13, 2023
  2. 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.
  3. 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 themore »urban land and anthropogenic aerosol effects for understanding urbanization effects on convective cloudsand precipitation.« less
  4. Free, publicly-accessible full text available November 14, 2023
  5. 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 thatmore »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.

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