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DOE OSTI2023

ShadeLab/PAPER_Howe_2023_switchgrass_MetaT

The raw data (metagenomes and metatranscriptomes) for this study are available in the Joint Genomes Institute Genome Portal (https://genome.jgi.doe.gov/portal/ Project ID 503249) with projects designated by year and product type. The MAG genomes analyzed in this paper are available on NCBI, as bioproject PRJNA800073. Plants and microorganisms form beneficial associations. Understanding plant-microbe interactions will inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on field-grown switchgrass and miscanthus and to quantify their activities for switchgrass over two growing seasons. We integrate metagenome and metatranscriptome sequencing from 192 leaf samples collected over representative time points in crop phenology. We curated 40 medium- and high-quality metagenome-assembled-genomes (MAGs) and focused analysis on seasonal transcript recruitment to them. Classes represented by these focal MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) were active and had increases in transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase in the late season. The majority of MAGs had activated stress-associated pathways, including trehalose metabolism, indole acetic acid degradation, betaine biosynthesis, and reactive oxygen species degradation, suggesting direct engagement with the host environment. We also detected seasonally activated biosynthetic pathways for terpenes (carotenoids and isoprenoids) and for various non-ribosomal peptide pathways that were poorly annotated. Overall, this study overcame laboratory and bioinformatic challenges associated with field-based leaf metatranscriptome analysis to inform both general and likely specialized activities of these phyllosphere populations. These activities collectively support that leaf-associated bacterial populations are seasonally dynamic, responsive to host cues, and interactively engage in feedback with the plant. This analysis represented quality filtering of metagenomes and metatranscriptomes (data-preparation folder), metagenome assemblies (metagenome-assembly folder) and metagenome-assembled genome binning, curation, refinement, annotation (mag-evaluation folder). Abundances of sequencing libraries were calculated based on reads mapped (mapping folder). Additionallly, analysis of our annotated results are also included (analysis folder).

Howe, Adina↗

DOE OSTI2022

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Turbulence in The Marine Boundary Layer and Air Motions Below Stratocumulus Clouds at the ARM Eastern North Atlantic Site

Marine stratocumulus clouds are intimately coupled to the turbulence in the boundary layer and drizzle is known to be ubiquitous within them. Six years of data collected at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic site are utilized to characterize turbulence in the marine boundary layer and air motions below stratocumulus clouds. Profiles of variance of vertical velocity binned by wind direction (wdir) yielded that the boundary layer measurements are affected by the island when the wdir is between 90° and 310° (measured clockwise from North where air is coming from). Data collected during the marine conditions (wdir<90 or wdir>310) showed that the variance of vertical velocity was higher during the winter months than during the summer months due to higher cloudiness, wind speeds, and surface fluxes. Furthermore, during marine conditions the variance of vertical velocity and cloud fraction exhibited a distinct diurnal cycle with higher values during the nighttime than during the daytime. Detailed analysis of 32 cases of drizzling marine stratocumulus clouds showed that for a similar amount of radiative cooling at the cloud top, within the sub-cloud layer 1) drizzle increasingly falls within downdrafts with increasing rain rates, 2) the strength of the downdrafts increases with increasing rain rates, and 3) the correlation between vertical air motion and rain rate is highest in the middle of the sub-cloud layer. The results presented herein have implications for climatological and model evaluation studies conducted at the ENA site, along with efforts of accurately representing drizzle-turbulence interactions in a range of atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Urbanization-induced land and aerosol impacts on storm propagation and hail characteristics

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from such storms such as hail and tornado. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban-rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~ 20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is much notable than either of the individual effects, emphasizing the importance to consider both effects in evaluating urbanization effects.

Lin, Yun↗

DOE OSTI2021

Convective and turbulent motions in non-precipitating Cu. Part 1: Method of separation of convective and turbulent motions

Atmospheric motions in clouds and cloud surroundings have a wide range of scales, from several kilometers to centimeters. These motions have different impacts on cloud dynamics and microphysics. Larger-scale motions (hereafter referred to as convective motions) are responsible for mass transport over distances comparable with cloud scale, while motions of smaller scales (hereafter referred to as turbulent motions) are stochastic and responsible for mixing and cloud dilution. This distinction substantially simplifies the analysis of dynamic and microphysical processes in clouds. The present research is Part I of the study aimed at describing the method for separating the motion scale into a convective component and a turbulent component. An idealized flow is constructed, which is a sum of an initially prescribed field of the convective velocity with updrafts in the cloud core and downdrafts outside the core, and a stochastic turbulent velocity field obeying the turbulent properties, including the -5/3 law and the 2/3 structure function law. A wavelet method is developed allowing separation of the velocity field into the convective and turbulent components, with parameter values being in a good agreement with those prescribed initially. The efficiency of the method is demonstrated by an example of a vertical velocity field of a cumulus cloud simulated using the System for Atmospheric Modeling (SAM) with bin microphysics and resolution of 10 m. It is shown that vertical velocity in clouds indeed can be represented as a sum of convective velocity (forming zone of cloud updrafts and subsiding shell) and a stochastic velocity obeying laws of homogeneous and isotropic turbulence.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

An evaluation of size-resolved cloud microphysics scheme numerics for use with radar observations Part II: Condensation and evaporation

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part I of this study addressed collision–coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision–coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Here, large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Comments on 'Do ultrafine cloud condensation nuclei invigorate deep convection?'

Here we elaborated on the deficiencies associated with the theoretical arguments and model simulations in Grawbowski and Morrison (2020; GM20), and showed that the concept of convective invigoration by aerosols can be supported by both accurate theoretical analysis and explicit physics modeling with prognostic aerosols and supersaturation. Above the freezing level, droplet freezing itself does not change mass loading and the latent heat release resulting from freezing leads to an increase in the buoyancy. The derivation in GM20 is erroneous because of omitting the liquid water sink term. They also ignored the effect of enhanced latent heating from the subsequent growth processes (deposition and riming) after freezing. Regarding aerosol effect on condensational growth, the quasi-steady assumption for supersaturation as adopted in GM20 is invalidated especially when droplet number concentration is low and updraft is strong from both theoretical analysis and our bin microphysics modeling results. The quasi-steady assumption makes condensation independent of droplet number and size and therefore reduces the overall aerosol effects on cloud dynamics. Studying aerosol effects on clouds particularly deep convective clouds requires the exact solution of supersaturation. Any assumption imposed to supersaturation such as saturation adjustment and quasi-steady approximation leads to incorrect aerosol effects on diffusional growth. The exact supersaturation equation clearly shows that condensation depends on droplet number and size, and more droplets in the polluted clouds increase condensation (thus lower supersaturation), leading to enhanced buoyancy and updraft speeds.

Convective invigoration, deep convective clouds, a↗

DOE OSTI2022

New Empirical Formulation for the Sublimational Breakup of Graupel and Dendritic Snow

Abstract Ice fragments are generated by sublimation of ice particles in subsaturated conditions in natural clouds. Conceivably, such sublimational breakup would be expected to cause ice multiplication in natural clouds. Any fragment that survives will grow to become ice precipitation that may sublimate and fragment further. As a first step toward assessing this overlooked process, a formulation is proposed for the number of ice fragments from sublimation of ice particles for an atmospheric model. This is done by amalgamating laboratory observations from previously published studies. The concept of a “sublimated mass activity spectrum” for the breakup is applied to the dataset. The number of ice fragments is determined by the relative humidity over ice and the initial size of the parent ice particles. The new formulation applies to dendritic crystals and heavily rimed particles only. Finally, a thought experiment is performed for an idealized scenario of subsaturation with in-cloud descent. Scaling analysis yields an estimate of an ice enhancement ratio of about 5 (10) within a weak deep convective downdraft of about 2 m s −1 , for an initial monodisperse population of dendritic snow (graupel) particles of 3 L −1 and 2 mm. During descent, there is a dynamic equilibrium between continual emission of fragments and their depletion by sublimation. A simplified bin microphysics parcel model exhibits this dynamical quasi equilibrium, consistent with the thought experiment. The fragments have average lifetimes of around 90 and 70 s for dendrites and graupel, respectively. Sublimational breakup is predicted to cause significant secondary ice production.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Revisiting the Hail Radar Reflectivity–Kinetic Energy Flux Relation by Combining T-Matrix and Discrete Dipole Approximation Calculations to Size Distribution Observations

The retrieval of hail kinetic energy with weather radars or its simulation in numerical models is challenging because of the shape complexity and variable density of hailstones. We combine 3D scans of individual hailstones with measurements of the particle size distributions (PSD) and T-matrix calculations to understand how hail reflectivity Z changes when approximating hailstones as spheroids, as compared to the realistic shapes obtained by 3D scanning technology. Additionally, recent terminal velocity relations are used to compare Z to the hail kinetic energy flux E ˙ . We parameterize the hail backscattering cross sections at L, S, C, and X bands as a function of size between 0.5 and 5.0 cm, matching the range of the observed PSDs. The scattering calculations use the T-matrix method for size parameters below 1.0 and the discrete dipole approximation (DDA) method otherwise. The DDA calculations are done for 48 digital models of realistic hailstones of sizes between 1 and 5 cm. The DDA cross sections are calculated for multiple orientations and averaged assuming a fully random orientation distribution to provide a single value per hailstone. The T-matrix reflectivity assuming solid ice spheres presents negligible differences to DDA results for size parameters below 1.0. Therefore, T matrix was used to fill in the gaps left by the DDA calculations. The results are mapped to the same size bins of the observed PSDs, allowing the calculation of the radar reflectivity. This is then correlated to E ˙ , allowing a potential improvement of past retrieval methods of E ˙ from Z in multiple wavelengths.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Convective and Turbulent Motions in Nonprecipitating Cu. Part II: LES Simulated Cloud Represented by a Starting Plume

The dynamic structure of a small trade wind cumulus (Cu) is analyzed using a novel approach. Cu developing in a shear-free environment is simulated by 10-m-resolution LES model with spectral bin microphysics. The aim is to clarify the dynamical nature of cloud updraft zone (CUZ) including entrainment and mixing in growing Cu. The validity of concept stating that a cloud at developing state can be represented by a parcel or a jet is tested. To investigate dynamical entrainment in CUZ performed by motions with scales larger than the turbulence scales, the modeled fields of air velocity were filtered by wavelet filter that separated convective motions from turbulent ones. Two types of objects in developing cloud were investigated: small volume ascending at maximal velocity (point parcel) and CUZ. It was found that the point parcel representing the upper part of cloud core is adiabatic. The motion of the air in this parcel ascending from cloud base determines cloud-top height. The top-hat (i.e., averaged) values of updraft velocity and adiabatic fraction in CUZ are substantially lower than those in the point parcel. Evaluation of the terms in the dynamical equation typically used in 1D cloud parcel models show that this equation can be applied for calculation of vertical velocities at the developing stage of small Cu, at least up to the heights of the inversion layer. Dynamically, the CUZ of developing cloud resembles the starting plume with the tail of nonstationary jet. Both the top-hat vertical velocity and buoyancy acceleration linearly increase with the height, at least up to the inversion layer. An important finding is that lateral entrainment of convective (nonturbulent) nature has a little effect on the top-hat CUZ velocity and cannot explain the vertical changes of conservative variables qt and θl. In contrast, entrained air lifting inside CUZ substantially decreases top-hat liquid water content and its adiabatic fraction. Possible reasons of these effects are discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

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↗

DOE OSTI2022

Assessing Raindrop Breakup Parameterizations Using Disdrometer Observations

In this work, an intercomparison of raindrop mean diameter frequency distribution (RDFD) is performed for numerical simulations of precipitating cloud systems using an array of models and microphysics schemes. This includes results from the Regional Atmospheric Modeling System (RAMS) double-moment microphysics, the Hebrew University Cloud Model bin microphysics (HUCM) interfaced to the RAMS parent model, and the Weather Research and Forecasting (WRF) Model with the Thompson, Morrison, double-moment 6-class (WDM6), and National Severe Storms Laboratory (NSSL) double-moment schemes. Simulations are examined with respect to the raindrop size distribution (DSD) volume-number mean diameter (D m ) and intercept parameter (N w ). When compared to a suite of disdrometer observations, the RDFD resulting from each microphysics scheme exhibits varying degrees of mean drop size constraints and peaks in the frequency distribution of D m . A more detailed investigation of the peaked RDFD from the RAMS simulations suggests that the parameterization of raindrop collisional breakup can impose strong limitations on the evolution of simulated drop growth. As such, a summary and comparison of the drop breakup parameterizations among the aforementioned microphysics schemes is presented. While some drop breakup parameterizations are adjusted toward the observations by modifying the threshold diameter for the onset of breakup, this study explores the use of a modified maximum breakup efficiency. This method permits the parameterization to retain its threshold breakup diameter, while limiting the strength of drop breakup and permitting a broader range of drop sizes. As a result, the simulated mean drop sizes are in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Impact of Cloud-Base Turbulence on CCN Activation: CCN Distribution

Abstract Following our previous investigation of the turbulence impact on cloud-base single-size CCN activation, this study considers a similar problem assuming CCN size distribution obtained from field measurements. The total CNN concentration is taken as either 200 cm −3 to represent clean conditions, or as 2000 cm −3 to represent polluted conditions. CCN is assumed to be sodium chloride. The CCN activation in the rising nonturbulent adiabatic parcel is contrasted with the activation within a rising adiabatic parcel filled with inertial-range homogeneous isotropic turbulence. The turbulent parcel of 64 3 m 3 and the turbulent kinetic energy dissipation rate of 10 −3 m −2 s −3 are used in most of the simulations. Results for a range of mean parcel ascent rates, between 0.125 and 8 m s −1 , are discussed. Overall, the adiabatic turbulent parcel simulations show results consistent with the adiabatic nonturbulent parcel, with higher activated CCN concentrations for stronger parcel ascent rates. The key difference is a blurriness of the separation between dry CCN size bins featuring activated and nonactivated (haze) CCN, especially for weak mean ascent rates. The blurriness comes from CCN getting activated and subsequently deactivated in the fluctuating supersaturation field, instead of all becoming cloud droplets above the cloud base. This leads to significantly larger spectral widths in turbulent parcel simulations compared to the nonturbulent parcel when activation is completed. Modeling results are discussed in the context of the impact of turbulent fluctuations on CCN activation documented in laboratory experiments using the Pi chamber.

Meteorology & Atmospheric Sciences↗

DOE OSTI2023

Vortex Structure of Head Bubble in Convective Cloud Starting Plume

Abstract A developing cumulus cloud (Cu) was modeled, and dynamic, thermodynamic, and microphysical properties of an ascending head bubble reproducing the upper part of a developing Cu were investigated. The data for analysis are taken from 10-m-resolution LES of trade wind Cu under BOMEX conditions. The detection of a rising bubble is carried out using wavelet filtering of the velocity fields and microphysical fields, while a low-frequency signal of the filtering is associated with the convective-scale structure of cloud. We substantiate and discuss the representation of the bubble as a vortex ring, and estimate the parameters of this vortex ring. The simplest Hill’s vortex was chosen as a model of a vortex ring inside cloud. Analytical approximations of the radial profiles of the vertical velocity and of conservative quantities (such as total water mixing ratio and liquid water potential temperature inside and outside the bubble) are obtained. The spatial structure of these quantities is investigated using analytical expressions. Analytical models for spatial distributions of liquid water content (LWC) and adiabatic fraction (AF) are also designed and analyzed. The results demonstrate the existence of a cloud core with high values of LWC and AF up to the height of 1800 m. The horizontally averaged value of the adiabatic fraction, calculated analytically using the Hill’s vortex concept, is evaluated as 0.39, which is the typical AF value in the upper parts of such Cu. The vertical profiles of different important quantities characterizing cloud structure are presented. The analysis performed in this study allows us to conclude that a rising vortex ring plays the dominating role in formation of the thermodynamic and microphysical structure of developing Cu. Significance Statement 1) Dynamic and thermodynamic fields of a developing cumulus cloud simulated by high-resolution LES with spectral bin microphysics are separated into convective and turbulent components by means of the wavelet technique. 2) The analysis of convective component of the cloud revealed the existence of a vortex ring at the developing stage of the cloud and evaluate its parameters. 3) The analysis performed in this study allows us to conclude that a rising vortex ring plays the important role in formation of the thermodynamic and microphysical structure of developing Cu. 4) The study provides a novel insight into the cloud–environment interaction. 5) The approximating equations describing the vortex ring can be usefully applied for developing new schemes of convective parameterization.

Meteorology & Atmospheric Sciences↗

DOE OSTI2023

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Dual Nature of Entrainment-Mixing Signatures Revealed through Large-Eddy Simulations of a Convection-Cloud Chamber

Abstract Entrainment of subsaturated air into a cloud can influence its optical and microphysical properties in various ways, depending on the droplet evaporation and turbulent mixing time scales. Previous experiments in the Pi convection-cloud chamber have revealed that, given a fixed entrained air property, the mixing of entrained subsaturated air results in complete evaporation of some cloud droplets, with the rest remaining unchanged. This is a signature of inhomogeneous mixing. While comparing the results of entrainment with varying air properties, the mixing signature appears as if the subsaturated air is well mixed with the cloud to evenly reduce the droplets’ size. In other words, taken together, the experiments appear to have the signature of homogeneous mixing. To explore these results in a greater depth, we conduct large-eddy simulations combined with a bin microphysics scheme. Our results reproduce the similar signatures of inhomogeneous and homogeneous mixing, implying that LES can resolve the inhomogeneous mixing when the grid spacing is smaller than the entrained air parcel. Additionally, we observe that increasing the aerosol injection rate enhances the signature of inhomogeneous mixing, while coarser grid spacing diminishes it. Finally, the change in wall fluxes in response to various entrained air properties confirms that the homogeneous signature seen in the analysis of an ensemble of simulations is the result of various equilibrium states. This further strengthens the suggestion that the homogeneous mixing signature found in aircraft observations near the cloud top may result from combining entrainment events of different intensities, possibly caused by various-sized eddies. Significance Statement Large-eddy simulation and size-resolved microphysics can resolve time scales for turbulent mixing and evaporation and, therefore, are well suited for reproducing, extending, and interpreting the entrainment experiment in the Pi convection-cloud chamber. Our simulation results confirm (i) the inhomogeneous mixing signature for an individual entrainment event and (ii) the appearance of homogeneous mixing in an ensemble of entrainment episodes. Furthermore, we demonstrate that the inhomogeneous mixing signature is more pronounced in a polluted cloud, but coarser grid spacing in simulations may compromise the accuracy of this signature. Last, the homogeneous mixing signature results from various equilibrium states established for different entrainment intensities and adjusted wall fluxes, which are challenging to measure experimentally but can be easily analyzed in the simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Dependence of Convective Cloud Microphysical Properties on Environmental Conditions during the TRACER and ESCAPE Field Campaigns: A Synergistic Approach of Observations, Machine Learning and Parcel Models

The sensitivity of convective clouds to aerosols and their interactions with environment, combined with limited observational constraints in parameterizations, introduces significant uncertainties in atmospheric models. Here, this study investigates the dependence of convective cloud microphysical properties on environmental conditions using a synergistic approach that combines unique observations from the TRACER and ESCAPE field campaigns, machine learning techniques, and parcel model simulations with a super-droplet microphysics scheme. A random forest algorithm identifies in-situ vertical velocity (w), temperature (T), and surface fine-mode aerosol mass concentration as the three most important environmental conditions influencing cloud properties including liquid water content (LWC), number concentration for particles with D max < 50 μm (N c ,<50), 50 μm ≤ D max ≤ 3000 μm (N c,50–3000 ), and droplet effective diameter (D e ). Results show that LWC, N c,<50 , and N c,50–3000 significantly increase with w in updrafts. Across w bins, as T decreases, LWC, D e , and N c,50–3000 increase, while N c,<50 decreases, which are closely linked to the distance above cloud bases. Warmer cloud bases yield higher LWC, greater N c,50–3000 , and smaller N c,<50 , while polluted environments produce greater N c,<50 . Parcel model simulations successfully replicate these observed dependencies. The simulation results indicate that warmer cloud bases enhance condensation generating larger droplets, and differences in droplet sizes are then amplified through collision-coalescence, resulting in a greater N c,50–3000 . Polluted conditions result in a greater N c,<50 primarily due to enhanced cloud condensation nuclei activation despite increased collision-coalescence rates compared to pristine conditions. This study provides observed quantitative patterns characterizing cloud microphysical properties as a function of key environmental parameters, offering valuable constraints for improving physics parameterizations and numerical models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A Computationally Efficient Linear Semi-Lagrangian Scheme for the Advection of Microphysical Variables in Cloud-Resolving Models

An efficient semi-Lagrangian (SL) numerical scheme for the advection of positive-definite microphysical variables in cloud-resolving models is proposed. The scheme is a linear combination of SL schemes of the first and second order. The proposed scheme is compared with two high-order, monotonic, nonlinear Eulerian schemes, in two 2D tests. In the first test, advection of a positive scalar field with large gradients is performed within complicated idealized steering flows. In the second test, a hail storm is simulated using the 2D Hebrew University Cloud Model, describing the interactions between 15 size distributions of different microphysical quantities (each distribution is described by 43 mass bins). The proposed scheme is computationally efficient, has a low numerical diffusion and a high level of mass conservation accuracy, and preserves the sum of multiple advected variables as well as the linear relationships between the advected scalar variables. Although the proposed SL scheme is not exactly positive definite, the negative values and their number, which may appear only in the case of very strong gradients, are negligible. The scheme produces results similar to those of nonlinear Eulerian advection schemes while reducing computation time by approximately a factor of 10.

54 ENVIRONMENTAL SCIENCES↗