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At least 19 records

Beirut Explosion Yield and Mushroom Cloud Height - Effects of the Source Environment

I use crater dimensions to estimate the yield of the August 4th, 2020 Beirut explosion to be equivalent to approximately 1.4 kilotons of TNT with a lower bound of about 0.7 kilotons. Based on the amount of ammonium nitrate reported to have been stored at the Beirut harbor, I assume an upper bound for the yield of 2.75 kilotons. However, it is highly likely that the yield was less than 2.75 kilotons, since reported values for TNT equivalence of ammonium nitrate are typically much less than one hundred percent. The crater-size based yield estimates are based on crater radius estimates from satellite imagery and empirical curves and data for scaled crater radius from past chemical and nuclear explosions. I present evidence that suggests that the relatively large crater radius is due to a high degree of coupling of shock wave energy to the surrounding medium and a reduction of the effective stress because of a high level of saturation of the geologic media beneath the explosion. I provide yield estimates based on seismic body-wave magnitude and crater depth as corroborating evidence. I compare preliminary estimates for the maximum debris cloud height, based on cell phone videos/images, with predicted maximum heights for this yield range from empirical formulas and numerical cloud-rise models. Based on a preliminary analysis of cell phone footage, the observed maximum cloud height appears to be approximately 1600 m. This is much lower than that predicted using standard empirical formulas and buoyant cloud rise models. I present results from a modified buoyant cloud rise model that more accurately predicts the maximum cloud height by allowing for the inclusion of a fixed amount of air and/or water into the fireball at the start of cloud rise. The amount of mass that needs to be added at the start, to reproduce the observed maximum cloud height, is relatively small compared to the total mass entrained during cloud rise. A much greater amount of dry air or debris is required, relative to water, for an equivalent reduction in maximum cloud height. The ammonium nitrate is one possible source for water in the fireball since it was being stored in a very humid environment and ammonium nitrate is known to be hygroscopic. The ground beneath the explosion, especially if it were saturated, and the nearby harbor could also have been sources for water or debris in the fireball.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Parallax-corrected VISST-derived pixel-level products from satellite GOES-16

The NASA Langley group led by William Smith produced GOES-16 satellite cloud retrievals over an approximate 10 by 10 degree region over the CACTI field campaign location. These retrievals are described here: https://www.arm.gov/capabilities/vaps/visst and are available for download here . They use algorithms historically called VISST that are now referred to as SatCORPS. More information can be found in Trepte et al. (2019), Minnis et al. (2021), and Yost et al. (2021). If using this dataset, please cite these references, the CACTI VISST dataset DOI found at the download link above, and this dataset’s DOI. The CACTI VISST pixel-level retrievals are on a 2 km spatial grid and available every 15 minutes (every 10 minutes late in the campaign), producing 21,765 files for the entire field campaign between October 2018 and April 2019. They are not corrected for parallax error, which is an offset in the actual geographical location of a cloud above the surface due to the satellite viewing the cloud partly from the side off nadir. This dataset applies a correction for parallax using the location relative to the satellite and the retrieved cloud top height above the surface, which allows the dataset to be geo-located with surface-based observations. The parallax correction for each location depends on the longitude, latitude and cloud top height above ground level (AGL) for that longitude and latitude in the original VISST files. The cloud top height AGL requires first computing the surface elevation at each VISST grid point. Data from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Map Version 3 at 30-m resolution is projected onto the VISST grid using conservative coarsening (conserving surface elevation) in the xESMF Python package. The surface elevation is then subtracted from the VISST-retrieved cloud top height above mean sea level. These cloud top heights AGL are then combined with longitude and latitude to estimate the latitude and longitude corrections. Due to variability in cloud top height, the parallax shifts produce an irregular grid of values since higher cloud tops are shifted further than lower cloud tops. A ball tree-based neighbor search with Haversine distance is performed using the Python-based scikit-learn library to find the nearest VISST grid point to each parallax correction-shifted point. The data value of the shifted point is then assigned to that VISST grid point. In this manner, the irregular geographical shifts to correct for parallax are projected back to the rectilinear VISST grid. Because relatively higher clouds should obscure lower clouds, the variable values for the highest cloud top are preferentially chosen if two or more values are assigned to a grid point. The parallax correction should be viewed as an improved but still imperfect estimation of the cloud top locations, largely because the cloud top height is an imperfect retrieval. Please see the attached README document for further information. Users are encouraged to contact the authors with any additional questions.

54 ENVIRONMENTAL SCIENCES↗

Mesofluidic Oil-Water Separation

Separating flowing multiphase solutions in process at industrial scale is challenging. A rapid continuous approach is desired. These mesofluidic oil-water separation tests were motivated by reports by Dijkshoorn et al [1] who reported separating droplets and particles using displacement with regularly spaced channels using a cross-flow microsieve.. Droplets, including deformable particles, larger than the channel migrate in one direction and thereby deplete in the other direction. Test flowrates were motivated by Burns et al. [4] who showed that separation could occur under laminar conditions, and Pease et al [8, 9] who extended the range to turbulent flow. Testing was conducted using two two-component oil-water mixtures at room temperature. Analysis showed separation of both mineral oils from their oil water mixtures at flowrates from 1-2 L/min and concentrations from 2-10 wt% oil in water.

cloud height, effective cleaning radius, effective↗

Estimating Scaled Cloud Height in Pulse Jet Mixed Vessels

To suspend and mix radioactive slurries without pumps or impellers, the performance of pulsed jet mixed vessels has been investigated. The slurry in the pulse tubes is expelled impinging upon the vessel floor and lifting solids to a “cloud height” in a cyclic process. Experiments measuring cloud height for a variety of waste simulants have been conducted for vessel configurations that varied vessel diameter, fill height and pulse tube number, volume, and nozzle diameter. The elevation to which suspended particles rise is termed the cloud height and derives from a balance between the fluid forces of the jet and the gravitational forces acting on the particle ensemble. Here we use scaling to estimate the cloud height based on conservation of mass and momentum and jet similarity. We find that the cloud height varies with the nozzle exit velocity to the 2/3 power in agreement with observations.

cloud height, effective cleaning radius, effective↗

VISSTPX2DRECTG16V4MINNIS (c1)

Satellite-based retrievals of cloud and radiation properties are available in this value-added product provided by Bill Smith’s group at NASA/Langley using the VISST (Visible Infrared Solar-Infrared Split Window Technique) algorithm. This product contains VISST-derived pixel-level products from the GOES-16 satellite, rectilinear projection 2-D array.

broadband LW flux↗

Comparison of scattering ratio profiles retrieved from ALADIN/Aeolus and CALIOP/CALIPSO observations and preliminary estimates of cloud fraction profiles

The space-borne active sounders have been contributing invaluable vertically resolved information of atmospheric optical properties since the launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006. To build long-term records from space-borne lidars useful for climate studies, one has to understand the differences between successive space lidars operating at different wavelengths, flying on different orbits, and using different viewing geometries, receiving paths, and detectors. In this article, we compare the results of Atmospheric Laser Doppler INstrument (ALADIN) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidars for the period from 28 June to 31 December 2019. First, we build a dataset of ALADIN–CALIOP collocated profiles (Δdist<1°; Δtime<6 h). Then we convert ALADIN's 355 nm particulate backscatter and extinction profiles into the scattering ratio vertical profiles SR(z) at 532 nm using molecular density profiles from Goddard Earth Observing System Data Assimilation System, version 5 (GEOS-5 DAS). And finally, we build the CALIOP and ALADIN globally gridded cloud fraction profiles CF(z) by applying the same cloud detection threshold to the SR(z) profiles of both lidars at the same spatial resolution. Before comparing the SR(z) and CF(z) profiles retrieved from the two analyzed lidar missions, we performed a numerical experiment to estimate the best achievable cloud detection agreement CDA norm (z) considering the differences between the instruments. We define CDA norm (z) in each latitude–altitude bin as the occurrence frequency of cloud layers detected by both lidars, divided by a cloud fraction value for the same latitude–altitude bin. We simulated the SR(z) and CF(z) profiles that would be observed by these two lidars if they were flying over the same atmosphere predicted by a global model. By analyzing these simulations, we show that the theoretical limit for CDA$_{norm}^{theor}$(z) for a combination of ALADIN and CALIOP instruments is equal to 0.81±0.07 at all altitudes. In other words, 19 % of the clouds cannot be detected simultaneously by two instruments due to said differences. The analyses of the actual observed CALIOP–ALADIN collocated dataset containing ~78 000 pairs of nighttime SR(z) profiles revealed the following points: (a) the values of SR(z) agree well up to ~3 km height. (b) The CF(z) profiles show agreement below ~3 km, where ~80 % of the clouds detected by CALIOP are detected by ALADIN as expected from the numerical experiment. (c) Above this height, the CDA$_{norm}^{obs}$(z) reduces to ~50 %. (d) On average, better sensitivity to lower clouds skews ALADIN's cloud peak height in pairs of ALADIN–CALIOP profiles by ~0.5±0.6 km downwards, but this effect does not alter the heights of polar stratospheric clouds and high tropical clouds thanks to their strong backscatter signals. (e) The temporal evolution of the observed CDA$_{norm}^{obs}$(z) does not reveal any statistically significant change during the considered period. This indicates that the instrument-related issues in ALADIN L0/L1 have been mitigated, at least down to the uncertainties of the following CDA$_{norm}^{obs}$(z) values: 68±12 %, 55±14 %, 34±14 %, 39±13 %, and 42±14 % estimated at 0.75, 2.25, 6.75, 8.75, and 10.25 km, respectively.

54 ENVIRONMENTAL SCIENCES↗

Convective and Turbulent Motions in Nonprecipitating Cu. Part III: Characteristics of Turbulence Motions

Velocity field in a nonprecipitating Cu under BOMEX conditions, simulated by SAM with 10-m resolution and spectral bin microphysics is separated into the convective part and the turbulent part, using a wavelet filtering. In Part II of the study properties of convective motions of this Cu were investigated. Here in Part III of the study, the parameters of cloud turbulence are calculated in the cloud updraft zone at different stages of cloud development. The main points of this study are (i) application of a fine-scale LES model of a single convective cloud allowed a direct estimation of turbulence parameters using the resolved flow in the cloud and (ii) the separation of the resolved flow into the turbulence flow and the nonturbulence flow allowed us to estimate different turbulent parameters with sufficient statistical accuracy. We calculated height and time dependences of the main turbulent parameters such as turbulence kinetic energy (TKE), spectra of TKE, dissipation rate, and the turbulent coefficient. It was found that the main source of turbulence in the cloud is buoyancy whose contribution is described by the buoyancy production term (BPT). The shear production term (SPT) increases with height and reaches its maximum near cloud top, and so does BPT. In agreement with the behavior of BPT and SPT, turbulence in the lower cloud part (below the inversion level) is weak and hardly affects the processes of mixing and entrainment. The fact that BPT is larger than SPT determines many properties of cloud turbulence. For instance, the turbulence is nonisotropic, so the vertical component of TKE is substantially larger than the horizontal components. Another consequence of the fact that BPT is larger than STP manifests itself in the finding that the turbulence spectrum largely obeys the -11/5 Bolgiano–Obukhov scaling. The classical Kolmogorov -5/3 scaling dominates for the low part of a cloud largely at the dissolving stage of cloud evolution. Using the spectra obtained we evaluated an “effective” dissipation rate which increases with height from nearly zero at cloud base up to 20 cm 2 s -3 near cloud top. The coefficient of turbulent diffusion was found to increase with height and ranged from 5 m 2 s -1 near cloud base to 25 m 2 s -1 near cloud top. In conclusion, the possible role of turbulence in the process of lateral entrainment and mixing is discussed.

54 ENVIRONMENTAL SCIENCES↗

Indications of a Decrease in the Depth of Deep Convective Cores with Increasing Aerosol Concentration during the CACTI Campaign

Abstract An aerosol indirect effect on deep convective cores (DCCs), by which increasing aerosol concentration increases cloud-top height via enhanced latent heating and updraft velocity, has been proposed in many studies. However, the magnitude of this effect remains uncertain due to aerosol measurement limitations, modulation of the effect by meteorological conditions, and difficulties untangling meteorological and aerosol effects on DCCs. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in 2018–19 produced concentrated aerosol and cloud observations in a location with frequent DCCs, providing an opportunity to examine the proposed aerosol indirect effect on DCC depth in a rigorous and robust manner. For periods throughout the campaign with well-mixed boundary layers, we analyze relationships that exist between aerosol variables (condensation nuclei concentration > 10 nm, 0.4% cloud condensation nuclei concentration, 55–1000-nm aerosol concentration, and aerosol optical depth) and meteorological variables [level of neutral buoyancy (LNB), convective available potential energy, midlevel relative humidity, and deep-layer vertical wind shear] with the maximum radar-echo-top height and cloud-top temperature (CTT) of DCCs. Meteorological variables such as LNB and deep-layer shear are strongly correlated with DCC depth. LNB is also highly correlated with three of the aerosol variables. After accounting for meteorological correlations, increasing values of the aerosol variables [with the exception of one formulation of aerosol optical depth (AOD)] are generally correlated at a statistically significant level with a warmer CTT of DCCs. Therefore, for the study region and period considered, increasing aerosol concentration is mostly associated with a decrease in DCC depth.

54 ENVIRONMENTAL SCIENCES↗

Impacts of long-range-transported mineral dust on summertime convective cloud and precipitation: a case study over the Taiwan region

As one of the most abundant atmospheric aerosols and effective ice nuclei, mineral dust affects clouds and precipitation in the Earth system. Here numerical experiments are carried out to investigate the impacts of dust aerosols on summertime convective clouds and precipitation over the mountainous region of Taiwan by acting as ice-nucleating particles. We run the Weather Research and Forecasting model (WRF) with the Morrison two-moment and spectral-bin microphysics (SBM) schemes at 3 km resolution, using dust number concentrations from a global chemical transport model (GEOS-Chem-APM). The case study indicates that the long-range-transported mineral dust, with relatively low number concentrations, can notably affect the properties of convective clouds (ice and liquid water contents, cloud top height, and cloud coverage) and precipitation (spatial pattern and intensity). The effects of dust are evident during strong convective periods, with significantly increased ice water contents in the mixed-phase regime via the enhanced heterogeneous freezing. With both the Morrison and SBM schemes, we see the invigoration effects of dust aerosols on the convective intensity through enhanced condensation and deposition latent heating. The low-altitude dust particles are uplifted to the freezing level by updrafts, which, in turn, enhance the convective cloud development through immersion freezing and convective invigoration. Compared to the Morrison scheme, the SBM scheme predicts more realistic precipitation and different invigoration effects of dust. The differences are partially attributed to the saturation adjustment approach utilized in the bulk scheme, which leads to a stronger enhancement of condensation at midlatitudes to low altitudes and a weaker deposition increase at the upper level.

54 ENVIRONMENTAL SCIENCES↗

Updraft Width Implications for Cumulonimbus Growth in a Moist Marine Environment

Abstract An idealized large-eddy simulation of a tropical marine cloud population was performed. At any time, it contained hundreds of clouds, and updraft width in shallow convection emerging from a subcloud layer appeared to be an important indicator of whether specific convective elements deepened. In an environment with 80%–90% relative humidity below the 0°C level, updrafts that penetrated the 0°C level were larger at and above cloud base, which occurred at the lifting condensation level near 600 m. Parcels rising in these updrafts appeared to emerge from boundary layer eddies that averaged ∼200 m wider than those in clouds that only reached 1.5–3 km height. The deeply ascending parcels (growers) possessed statistically similar values of effective buoyancy below the level of free convection (LFC) as parcels that began to ascend in a cloud but stopped before reaching 3000 m (nongrowers). The growers also experienced less dilution above the LFC. Nongrowers were characterized by negative effective buoyancy and rapid deceleration above the LFC, while growers continued to accelerate well above the LFC. Growers occurred in areas with a greater magnitude of background convergence (or weaker divergence) in the subcloud layer, especially between 300 m and cloud base, but whether the convergence actually led to eddy widening is unclear. Significance Statement Cumulonimbus clouds are responsible for many extreme weather phenomena and are important contributors to Earth’s energy balance. However, the processes leading to the growth of individual clouds are not completely understood nor well-represented in weather prediction models. We find that the clouds containing updrafts that start out wider at early stages of their life cycles grow taller, possibly because they are protected more from drier air outside the cloud than narrow clouds. In addition, this work shows how the initial width of clouds might be related to convergence in the lowest part of the atmosphere, at heights where clouds initially develop. However, meteorologists must be careful not to overinterpret these results because numerical simulations inherently include assumptions that may not reflect reality. This reinforces the need to also observe processes occurring at the scales of individual clouds.

54 ENVIRONMENTAL SCIENCES↗

Causal machine learning uncovers conditions for convective intensification driven by organic and sulfate aerosols

Aerosols are often hypothesized to invigorate deep convective clouds (DCCs), but observational evidence remains limited and inconclusive. Clarifying this hypothesis is critical for regions vulnerable to thunderstorms and flooding, particularly highly polluted coastal cities. Leveraging a novel causal discovery–inference pipeline and high-resolution observations near Houston, TX, we identify multiple causal pathways among aerosols (mostly organic and sulfate), DCCs, and meteorological factors. However, a direct causal link from aerosols to DCCs is found to be uncommon, occurring in less than 35% of analyzed scenarios, and is characterized by strong conditionality and nonlinearity. When aerosol impacts on DCCs do occur, they can be substantial, enhancing DCC core heights by approximately 1.7 km, with 92% of this effect concentrated in warmer-phase cloud regions. Notably, the presence of sea breezes and the inclusion of all measured aerosol particles each enhance DCCs in over 95% of aerosol-sensitive cases.

54 ENVIRONMENTAL SCIENCES↗

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

54 ENVIRONMENTAL SCIENCES↗

Prediction for cloud spacing confirmed using stereo cameras

Using three years of the Clouds Optically Gridded by Stereo (COGS) product, the mean cloud base, cloud top, cloud width, and cloud spacing are described with respect to their seasonal and/or diurnal evolution at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. In addition to confirming and extending prior results, the data show that the effective diameter of shallow cumuli are approximately equal to the height above ground of the lifting condensation level (LCL). Furthermore, the cloud spacing is found to closely match a prediction by Thuburn and Efstathiou for the horizontal scale of the largest unstable eddies in an unsheared convective boundary layer.

54 ENVIRONMENTAL SCIENCES↗

ShupeTurner cloud microphysics

This product is the ShupeTurner cloud microphysics product derived for the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic. The product includes time-height derivations of the cloud type (phase type) and the condensed water content and characteristic effective particle size for liquid and ice hydrometeor populations. Additionally, it includes the vertical integral of the condensed water content for liquid and ice, i.e., the liquid water path and ice water path. These are derived using a combination of sensors, including: cloud radar, depolarization lidar, microwave radiometer, ceilometer, and radiosondes. During MOSAiC, these sensors were installed and operated onboard the Polarstern icebreaker while within the Arctic sea ice. Most data were obtained while Polarstern was moored to the MOSAiC sea ice floe, passively drifting through the Arctic. However, the data from 16 May 2020 - 17 June 2020 and 31 July 2020 - 21 August 2020 were obtained while Polarstern was underway transiting through the sea ice during relocations of the expedition. General details of the retrieval algorithm, its application, and uncertainties are provided in Shupe et al. (2015), with the cloud classification being described in more detail in Shupe (2007). General details about the MOSAiC expedition including instruments, locations, and meteorological context is provided in Shupe et al. (2022).

54 ENVIRONMENTAL SCIENCES↗

Incorporating an Interactive Fire Plume-Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect

The vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume-rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume-rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling-FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model-observation comparison demonstrates the importance of the plume-rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m –2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no-linear nature in the BBA-induced radiative effect.

54 ENVIRONMENTAL SCIENCES↗

Adiabatic Evolution of Cloud Droplet Spectral Width: A New Look at an Old Problem

Abstract Spectral width of the cloud droplet spectrum is important for radiative properties and drizzle/rain development in warm ice‐free clouds. We use an adiabatic rising parcel model to study activation and diffusional growth of cloud droplets, focusing on the spectral width evolution, and contrasting clean and polluted environments. A comprehensive droplet growth equation is used that includes kinetic, solute, and surface tension effects. We show that those effects have an appreciable impact on the spectral width evolution above the cloud base. Without those effects, the droplet area standard deviation should not change once activation is completed. In contrast, simulation results show that the area standard deviation does increase with height, especially for weak updrafts and polluted environments. Implications of those results for cloud modeling, especially applying conventional bin microphysics, are discussed.

54 ENVIRONMENTAL SCIENCES↗