Cloud Droplets Research Articles

Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx

Abstract. Several global modelling studies have explored the effects of lightning-generated nitrogen oxides (LNOx) on gas-phase chemistry and atmospheric radiative transfer, but few have quantified LNOx's impact on aerosol, particularly when nitrate aerosol is included. This study addresses two key questions: (1) how does including nitrate aerosol affect properties such as tropospheric composition, and (2) how do these effects depend on lightning parameterisation and LNOx levels? Using the Met Office's Unified Model–United Kingdom Chemistry and Aerosol (UM–UKCA) global chemistry–climate model, which now includes a modal nitrate aerosol scheme, we investigate these effects with two lightning-flash-rate parameterisations. Our findings show that both nitrate aerosol and LNOx significantly impact tropospheric composition and aerosol responses. Including nitrate aerosol reduces global mean tropospheric OH by 5 %, decreases the tropospheric ozone burden by 4 %–5 %, increases methane lifetime by a similar amount, and alters the top-of-atmosphere (TOA) net downward radiative flux by −0.4 W m−2. The inclusion of nitrate also shifts the aerosol size distribution, particularly in the Aitken and accumulation modes. A 5.2 Tg N yr−1 increase in LNOx from a zero baseline results in global aerosol increases of 2.8 % in NH4, 4.7 % in fine NO3, 12 % in coarse NO3, and 5.8 % in SO4 mass burdens. This much LNOx increase causes relatively small positive changes in aerosol optical depth, TOA radiative flux, and cloud droplet number concentration compared to when nitrate is included. The results, based on a fast uptake rate for HNO3 to produce NH4NO3, likely represent an upper limit on nitrate effects.

Retention of α-pinene oxidation products and nitro-aromatic compounds during riming

Abstract. Riming is an important growth process of graupel and hailstones in the mixed-phase zones of clouds, during which supercooled liquid droplets freeze on the surface of ice particles by contact. Compounds dissolved in the supercooled cloud droplets can remain in the ice or be released to the gas phase during freezing, which might play an important role in the vertical redistribution of these compounds in the atmosphere by convective cloud processes. This is important for estimating the availability of these compounds in the upper troposphere, where organic matter can promote new particle formation and growth. The amount of organic material remaining in the ice phase can be described by the retention coefficient. Experiments were performed in the Mainz vertical wind tunnel under dry and wet growth conditions (temperature from −12 to −3 °C and a liquid water content (LWC) of 0.9±0.2 g m−3 and 2.2±0.2 g m−3) as well as with different pH values (4 and 5.6) to obtain the retention coefficients of α-pinene oxidation products and nitro-aromatic compounds. For cis-pinic acid, cis-pinonic acid, and (−)-pinanediol, mean retention coefficients of 0.96±0.07, 0.92±0.11, and 0.98±0.08 were obtained. 4-Nitrophenol, 4-nitrocatechol, 2-nitrobenzoic acid, and 2-nitrophenol showed mean retention coefficients of 1.01±0.07, 1.01±0.14, 0.99±0.04, and 0.21±0.12. Only the retention coefficient of 2-nitrophenol showed a dependence on temperature, growth regime, and pH. This is in accordance with previous studies, which showed a dependence between the dimensionless effective Henry's law constant H* and the retention coefficient for inorganic and small organic molecules. Our results reveal that this correlation can also be applied to more complex organic molecules and that retention under these conditions is not a significant factor for molecules with H* below 103, while retention close to 1 can be expected for compounds with H* above 108.

Broadening of cloud droplet spectra through eddy hopping: Why did we all have it wrong?

Abstract In situ aircraft observations in adiabatic and close-to-adiabatic cloudy volumes suggest that cloud droplet spectra are often broader than predicted by growth of a droplet population rising from the cloud base. Cloud turbulence has been suggested as one of possible mechanisms for the observed spectral broadening. This paper reviews computational studies of the impact of cloud turbulence on the diffusional growth of cloud droplets in adiabatic cloudy volumes. These studies typically apply direct numerical simulation (DNS) or scaledup DNS approach to represent diffusional growth of cloud droplets embedded within homogeneous isotropic air turbulence. There is also a theory that predicts that the droplet spectral width continuously increases in time because of the individual droplet growth or evaporation within turbulent eddies. This mechanism has been referred to as eddy hopping. This paper expands the discussion in Prabhakaran et al. (J. Atmos. Sci. 2022) and illustrates the fundamental flaw of past computational and theoretical studies. These studies do not consider vertical dispersion of droplet positions that leads to growth of droplets that in the mean move upwards, and to evaporation of those that move downwards. The theoretical prediction comes from confusing spectral broadening with the vertical dispersion of droplet positions when periodic lateral boundaries are used in DNS. Computational examples using a stochastic model mimicking eddy hopping show that droplet spectral width does not continuously increase in time, but it saturates at a small spread. Methodologies for appropriate numerical studies of the adiabatic spectral width evolution in natural clouds are discussed.

Numerical simulation of aerosol concentration effects on cloud droplet size spectrum evolutions of warm stratiform clouds in Jiangxi, China

Abstract. Changes in aerosol amount and size distribution significantly impact cloud droplet size distribution, as aerosols act as cloud condensation nuclei (CCNs) and influence the relative dispersion (ε) of cloud droplet spectra. Relative dispersion plays a key role in parameterizing cloud processes in general circulation models (GCMs) and microphysical schemes, affecting precipitation estimates and climate predictions. However, the effects of varying aerosol modes on cloud microphysics remain debated, depending on thermodynamic conditions and cloud type. This study simulates a warm stratiform cloud in Jiangxi, China, using the Weather Research and Forecasting (WRF) Spectra–Bin Microphysics scheme (SBM-FAST) from 18:00 on 24 December 2014 to 06:00 on 25 December 2014 (UTC). Satellite and aircraft observations were used to validate the simulation, showing good agreement in cloud structure. Sensitivity experiments were conducted by increasing nucleation, accumulation, and coarse-mode aerosols 5-fold and by reducing the total aerosol concentration to 1/5 of the control. Results show that higher aerosol concentrations enhance cloud formation and broaden droplet spectra, while lower concentrations suppress cloud development. Accumulation-mode aerosols increase small-droplet concentrations, while nucleation- and coarse-mode aerosols favor larger droplets. The correlation between ε and volume-weighted radius (Rv) shifts from positive to negative as Rv increases. This transition is driven by cloud droplet collision–coalescence, condensation, and activation. Increased accumulation-mode aerosol concentrations shift the ε–Rv correlation from negative to positive in the Rv range of 4.5–8 µm, while reduced aerosol concentrations strengthen the negative correlation. Regardless of different coalescence intensities, ε converges with the increase in number concentration of cloud droplets (Nc).

The Impact of Cumulus Clouds and CCN Regeneration on Aerosol Vertical Distribution and Size

Abstract This study employs a high-resolution (10m) System for Atmospheric Modeling (SAM) coupled with the Spectral Bin Microphysical (SBM) scheme to thoroughly investigate the processes governing the evolution of aerosol properties within and outside a shallow cumulus cloud. The model encompasses the complete life cycle of cloud droplets, starting from their formation through their evolution until their complete evaporation or sedimentation to the ground. Additionally, the model tracks the aerosols’ evolution both within droplets and in the air. Aerosols are transported within the droplets, grow by droplet coalescence, and are released into the atmosphere after droplet evaporation (regeneration process). The aerosol concentration increases by droplet evaporation and decreases along with falling drops. So, the effects of clouds on the surrounding aerosols depend on the microphysical and dynamic processes, which in turn depend on the amount of background aerosols; here, we compare clean and polluted conditions. It is shown that the regeneration process is highly important and that shallow trade cumulus clouds significantly impact the vertical profile of aerosol concentration in the lower troposphere, as well as their size distribution, and can serve as a source of large cloud condensation nuclei. Furthermore, it is shown that both precipitating and non-precipitating boundary layer clouds contribute to a substantial increase in aerosol concentration within the inversion layer due to intense evaporation.

Cloud Droplet Size Distributions Governed by Condensation, Collision–Coalescence, and Sedimentation. Part I: Monte Carlo Simulations and Scaling Relations for Growth in a Convection–Cloud Chamber

Abstract Atmospheric clouds are crucial to weather and climate, and the rate at which droplets collide and coalesce to form precipitation is one of the fundamental controlling processes. A convection–cloud chamber allows the interactions between aerosols and cloud droplets produced by condensation to be investigated within a turbulent environment. Studying the full range of microphysical conditions in atmospheric clouds is not possible, however, unless conditions for droplet growth by collision and coalescence are also achieved. In this study, we explore the conditions favorable to collision–coalescence growth in convection–cloud chambers, extending previous work on steady-state droplet size distributions due to condensation only to obtain analytic expressions for number concentration and supersaturation as a function of small-droplet injection rate and for collision–coalescence rates. We derive several scaling laws and demonstrate consistency between these theoretical results and Monte Carlo simulations of growth and precipitation within a convection–cloud chamber. Specifically, the coalescence rate is shown to scale as the square of the liquid water content, which in turn can be modulated in a convection–cloud chamber by varying the small-droplet injection rate as well as the applied temperature difference.

Cloud Droplet Size Distributions Governed by Condensation, Collision–Coalescence, and Sedimentation. Part II: Analytical Expressions for Size Distribution Shape and Asymptotic Behavior for Large-Droplet Tails

Abstract Droplet growth via condensation and collision–coalescence has been investigated in the limit of very weak coalescence growth: a collector-mode approximation emerges for coalescence growth that consists solely of droplets in the tail collecting droplets near the main mode of the cloud droplet size distribution and that does not deplete the mode. In this second part, the approximation is formalized, leading to a simplified form of the collision–coalescence term in the equation governing the evolution of the droplet size distribution. This form allows for analytical solutions for transient growth and for steady-state distributions representing a balance between condensation, collision–coalescence growth, and removal by sedimentation. The solutions lead to an expression for the drizzle growth time, formally, the finite time in which a droplet approaches infinite size. The drizzle growth time is related to a transition radius at which droplet growth switches from condensation-dominated to coalescence-dominated. The solutions also provide a dimensionless group that governs the steady-state distribution shape, which is referred to as the drizzle number. The solutions are checked by comparing to a Monte Carlo model developed in part 1, and it is found that the analytical solution is excellent when the drizzle number is much greater than unity, which is the typical situation for the microphysical conditions achievable in a convection–cloud chamber. The steady-state size distribution has the form of a modified gamma distribution, with a transition to a power-law tail at a sufficiently large radius. The solutions are not only formally valid for a convection–cloud chamber but can also be extended to shallow, mixed-layer clouds such as mixing fogs.

Impact of stochastic collisions on cloud droplet number concentration and relative dispersion during Meiyu frontal system

Impact of stochastic collisions on cloud droplet number concentration and relative dispersion during Meiyu frontal system

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.

An experimental study on flame propagation and combustion characteristics of multiple emulsified diesel and biodiesel fuel droplets

To unravel the interaction mechanism between droplets that is relevant for practical liquid fueled burners, the flame propagation characteristics of multi-droplet of emulsified diesel and biodiesel (FAME) fuels were studied using a suspended line droplet array. It was found that when S/d0 ≤ 3 (ratio of droplet spacing to initial droplet diameter), the double droplets were ignited simultaneously and surrounded by a single flame, and as the droplet spacing increased, two independent flames were formed around each droplet. The highest flame propagation rate was attained at S/d0 = 3, which was attributed to the consistent values of flame standoff ratio limited by the dominant heat conduction and finite evaporating rate. The droplet interaction, such as oxygen competition effect, enhanced with smaller droplet distance, can result in the reduction in the droplet combustion rate and flame propagation rate; the latter one, however, showed an increasing trend when small droplet or the size non-uniformity of droplet cloud was considered. In addition, the child droplet ejected from the emulsified droplets showed three burning modes and was an important factor promoting the flame spread, and the results showed that compared with the FAME emulsified fuels, the child droplets in diesel cases were more prone to ignition, expanding the burning regime.

Turbulent dispersion and evaporation of charged nanofuel droplet clouds under the influence of electrostatic fields

Turbulent dispersion and evaporation of charged nanofuel droplet clouds under the influence of electrostatic fields

Similar freezing spectra of particles in plant canopies and in the air at a high-altitude site

Abstract. Plant canopies are an important source of biological particles aerosolized into the atmosphere. Certain aerosolized microorganisms are able to freeze slightly supercooled cloud droplets and therefore affect mixed-phase cloud development. Still, spatiotemporal variability of such biological ice-nucleating particles (INPs) is currently poorly understood. Here, we study this variability between late summer and leaf shedding on the scale of individual leaves collected about fortnightly from four temperate broadleaf tree species (Fagus sylvatica, Juglans regia, Prunus avium and Tilia platyphyllos) on a hillside (Gempen, 650 m a.s.l. (metres above sea level)) and in a vertical canopy profile of one Fagus sylvatica (Hölstein, 550 m a.s.l.) in north-western Switzerland. The cumulative concentration of INPs active at ≥-10 °C (INPs−10) did not vary significantly between the investigated tree species but, as inferred from leaf mass per area and leaf carbon isotopic ratios, seemed to be lower on sun leaves as compared with shade leaves. Between August and mid-November, the median INP concentration increased from 4 to 38 INP−10 cm−2 of leaf area and was positively correlated with mean relative humidity throughout 24 h prior to sampling (Spearman's r=0.52, p<0.0001, n=64). In 53 of the total 64 samples collected at the Gempen site, differential INP spectra between −3 and −10 °C exhibited clearly discriminable patterns: in 53 % of the spectra, the number of additionally activated INPs increased persistently with each 1 °C decrease in temperature; the remaining spectra displayed significant peaks in differential INP concentration above −9 °C, most frequently in the temperature interval between −8 and −9 °C (21 %) and between −7 and −8 °C (17 %). Interestingly, the three most frequent patterns in differential INP spectra on leaves in Gempen were also prevalent in similar fractions in air samples with clearly discriminable patterns at the high-altitude Jungfraujoch site (3580 m a.s.l., Switzerland) collected during summer in the previous year. These findings corroborate the idea that a large fraction of the airborne biological INP population above the Alps during summer originates from plant surfaces. Which parameter or set of parameters could affect biological INP populations on both scales – upwind airsheds of high-altitude sites as well as individual leaves – is an intriguing question for further exploration. A first guess is that leaf wetness duration plays a role.

Modeling analysis and experiments of dual-FOV multiple scattering Raman lidar for detecting water cloud microphysical properties

Clouds are the primary regulators of the Earth’s climate, but the mechanisms through which they influence climate are poorly understood. Probing the microphysical properties of liquid water clouds is an urgent need for research on the Earth’s atmospheric system and atmospheric physics. In this paper, an iterative inversion of water cloud microphysical properties for a multiple scattering Raman lidar is presented, which can enable continuous, vertical measurements of the extinction coefficient of water clouds, the liquid water content (LWC), the effective radius of the cloud droplets, and cloud droplet number concentration (CDNC). The technique based on a constructed dual-field-of-view (dual-FOV) device combined with a quasi-small-angle (QSA) approximation model was investigated. The determination method of the optimal field of view (FOV) for lidar detection was discussed to enhance the sensitivity of the measured signals to the observed cloud microphysical parameters. Field observations with a co-located microwave radiometer (MWR) were carried out to verify the effectiveness of the lidar system, also an error analysis of the measurement examples was performed. The dual FOV Raman lidar experimental LWC measurement has an average deviation of 0.034 g/m3 and the relative error is 27.2% relative to the MWR measurement. The system has important potential applications in aerosol-cloud interactions and provides new ideas and methods for studying water cloud microphysical properties, further studying aerosol indirect effects.

Gibbs states and Brownian models for coexisting haze and cloud droplets.

Cloud microphysics studies include how tiny cloud droplets grow and become rain. This is crucial for understanding cloud properties like size, life span, and impact on climate through radiative effects. Small weak-updraft clouds near the haze-to-cloud transition are especially difficult to measure and understand. They are abundant but hard to capture by satellites. Köhler's theory explains initial droplet growth but struggles with large particle groups. Here, we present a stochastic, analytical framework building on Köhler's theory to account for (monodisperse) aerosols and cloud droplet interaction through competitive growth in a limited water vapor field. These interactions are modeled by sink terms, while fluctuations in supersaturation affecting droplet growth are modeled by nonlinear white noise terms. Our results identify hysteresis mechanisms in the droplet activation and deactivation processes. Our approach allows for multimodal cloud's droplet size distributions supported by laboratory experiments, offering a different perspective on haze-to-cloud transition and small cloud formation.

Glaciation of liquid clouds, snowfall, and reduced cloud cover at industrial aerosol hot spots.

The ability of anthropogenic aerosols to freeze supercooled cloud droplets remains debated. In this work, we present observational evidence for the glaciation of supercooled liquid-water clouds at industrial aerosol hot spots at temperatures between -10° and -24°C. Compared with the nearby liquid-water clouds, shortwave reflectance was reduced by 14% and longwave radiance was increased by 4% in the glaciation-affected regions. There was an 8% reduction in cloud cover and an 18% reduction in cloud optical thickness. Additionally, daily glaciation-induced snowfall accumulations reached 15 millimeters. Glaciation events downwind of industrial aerosol hot spots indicate that anthropogenic aerosols likely serve as ice-nucleating particles. However, rare glaciation events downwind of nuclear power plants indicate that factors other than aerosol emissions may also play a role in the observed glaciation events.

Exploring How the Surface-Area-to-Volume Ratio Influences the Partitioning of Surfactants to the Air-Water Interface in Levitated Microdroplets.

Quantitative characterization of the surface of microdroplets is important to understanding and predicting numerous chemical and physical processes, such as cloud droplet formation and accelerated chemistry in microdroplets. However, it is increasingly appreciated that the surface compositions of microdroplets do not necessarily match those of macroscale solution due to their large surface-area-to-volume (SA-V) ratios and confined volumes. In this work, we explore how both droplet size and composition affect the surface composition of microdroplets by measuring the equilibrium surface tensions of levitated microdroplets containing a single surfactant. We measure the critical micelle concentrations (CMCs) for surfactants of various strengths (macroscale CMC values ranging from 0.02 to 10 mM) in microdroplets with radii ranging from 5 to 25 μm. We accurately model the surface tensions of microdroplets using an equilibrium partitioning model that only requires droplet size and adsorption parameters from macroscale measurements as inputs. Our model predicts that surfactants have an "effective CMC" in microdroplets that is always larger in value than the corresponding macroscale CMC. In some instances, the effective CMC of a surfactant in microdroplets is several orders of magnitude larger than both its macroscale CMC and its macroscale solubility limit. We present a simple expression for the effective CMC in microdroplets that depends on both the macroscale CMC of a surfactant and the SA-V ratio of the microdroplet. Ultimately, our experimental results and model can be used broadly to predict microdroplet surface compositions when investigating surface-driven accelerated chemistry in microdroplets or estimating cloud droplet activation.

Evaluation of Spatial and Temporal Distribution of Carbon Emissions in Power Grid Based on Cloud Theory

In order to clearly determine the carbon emission distribution of regions, lines or nodes in the power grid, this paper applies cloud theory to the evaluation of the distribution of carbon emissions in the power grid. Based on the theory of carbon emission flow in the whole life cycle, five indicators that can reflect the spatial and temporal distribution of carbon emissions are constructed from the two dimensions of space and time. Cloud theory is used to establish the standard cloud of the carbon emission distribution level to quantify the randomness and fuzziness of the data to be evaluated. The bilateral constraint cloud theory and data-driven cloud transformation are combined to construct five comprehensive standard clouds of excellent, good, medium, poor and inferior, which are used as the evaluation interval of the evaluation index of carbon emission distribution. The reverse cloud is used to convert multiple sets of data into cloud droplets. Through the similarity measurement algorithm based on cloud model overlap, the comprehensive evaluation level of carbon emission distribution state in the time dimension is determined. Taking the IEEE 39 system as the research object, the spatial and temporal distribution of carbon emissions is evaluated, and the rationality and effectiveness of the proposed model are verified. Finally, the influence of the new energy penetration rate and power supply structure on the carbon emission distribution of the power grid is discussed by using cloud computing. Based on this, the targeted carbon reduction strategies for different types of nodes and the method of measuring the optimal new energy penetration rate are proposed and can provide a decision-making reference for optimizing the carbon emissions of the power grid.

The Cycle 46 Configuration of the HARMONIE-AROME Forecast Model

The aim of this technical note is to describe the Cycle 46 reference configuration of the HARMONIE-AROME convection-permitting numerical weather prediction model. HARMONIE-AROME is one of the canonical system configurations that is developed, maintained, and validated in the ACCORD consortium, a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale numerical weather prediction. This technical note describes updates to the physical parametrizations, both upper-air and surface, configuration choices such as lateral boundary conditions, model levels, horizontal resolution, model time step, and databases associated with the model, such as for physiography and aerosols. Much of the physics developments are related to improving the representation of clouds in the model, including developments in the turbulence, shallow convection, and statistical cloud scheme, as well as changes in radiation and cloud microphysics concerning cloud droplet number concentration and longwave cloud liquid optical properties. Near real-time aerosols and the ICE-T microphysics scheme, which improves the representation of supercooled liquid, and a wind farm parametrization have been added as options. Surface-wise, one of the main advances is the implementation of the lake model FLake. An outlook on upcoming developments is also included.

Aircraft observation of aerosol and mixed-phase cloud microphysical over the North China Plain, China: Vertical distribution, size distribution, and effects of cloud seeding in two-layered clouds

Aerosol and clouds are essential to climate effects. Based on an aircraft observation in a mixed-phase cloud in Shijiazhuang, China, on November 21, 2020, analyzing the vertical and size distributions of cloud droplets, and ice crystal particles, and the effects of the similar to a “seeder-feeder” process after cloud seeding on cloud microphysics. The first seeding cloud (CS1) and second seeding cloud (CS2) were at 2600–2800 m and 1500–2300 m, respectively. Before seeding, the average number concentration of cloud droplets (Nc) was 236.91 cm−3 and 152.13 cm−3 in CS1 and CS2 from vertical observation. In CS1, the average number concentration of ice crystals (Ni) was 0.26 L−1 with dendritic ice crystals and graupel, while in CS2, the average Ni was 0.19 L−1, including rimed plate ice crystals, graupel, and needle ice crystals. After seeding, the average Nc decreased from 322.90 to 260.69 cm−3 and the spectrum of Nc broadened from 2.5 to 24 to 45 μm in CS1. The ice microphysics also had different responses in the layered cloud. Ni increased by 421 times in regions with high Nc and low LWC (Nc > 322.90 cm−3, LWC < 0.14 g∙m−3), including spoked and heavily rimed ice crystals and graupel (200–500 μm) in CS1. In CS2, the maximum Ni was 252.03 L−1 and the average Ni increased by 2 magnitudes (from 0.39 to 11.44 L−1). There were rimed needles and columnar ice crystals (200–300 μm) in regions with high Nc and high LWC (Nc > 92.78 cm−3, LWC > 0.13 g∙m−3), and high Nc and low LWC (Nc > 92.78 cm−3, LWC < 0.13 g∙m−3). Seeding in CS1 and CS2 formed a structure similar to the “seeder-feeder” process. Controlled by the downdraft (>1 m/s), these particles descended into the “feeder” region of CS2. Appropriate temperature and rimed crystals contributed to secondary ice crystal production (SIP), resulting in main columns (200–300 μm) observed in CS2. The “feeder” region generated more ice crystals than the “seeder” region.

Airborne Observations of Highly Variable and Complex Freezing Drizzle and Mixed-Phase Environments

Abstract Airframe icing caused by interactions with supercooled cloud droplets and precipitation can pose a risk to aviation operations and life safety. The In-Cloud Icing and Large-drop Experiment (ICICLE) was conducted in January–March 2019 to capture measurements in freezing conditions in support of the Federal Aviation Administration (FAA) Terminal Area Icing Weather Information for NextGen (TAIWIN) program. The National Research Council of Canada’s Convair-580 research aircraft fulfilled the airborne data collection requirements for the ICICLE campaign and sampled icing clouds and atmospheric conditions over the midwestern United States. ICICLE flight 18, conducted on 17 February 2019, collected cloud and precipitation measurements during a widespread storm that generated supercooled small drops and freezing drizzle (FZDZ) within both liquid and mixed-phase regions. Supercooled liquid water content (LWC) typically ranged 0.30–0.45 g m−3 and exceeded 0.70 g m−3 in one instance. Maximum FZDZ diameters of 300–400 μm were commonly sampled near the base of clouds. Missed approaches performed at four Illinois airfields provided measurements of conditions from near ground level to above cloud top and supplied information regarding FZDZ formation and evolution. FZDZ was found to form at altitudes featuring relatively high LWC and sufficiently low droplet number concentrations. FZDZ formation zones were sometimes collocated with regions of atmospheric instability and/or wind shear. Flight through highly variable supercooled cloud droplet and FZDZ conditions resulted in significant Convair-580 airframe icing, highlighting the risk that icing conditions can pose to aircraft safety.