The superposition of small-scale processes calls for an integrated approach that combines laboratory experiments, field observations, and numerical modeling. Field observations characterize cloud processes within their natural, dynamic environment using a combination of remote sensing and in-situ measurements. Recent advances in observational platforms (e.g., uncrewed aerial systems), measurement techniques (e.g., multi-frequency cloud radar), and experimental designs have enhanced these capabilities. Controlled laboratory experiments allow for the isolation and systematic study of specific cloud processes under defined and repeatable conditions. High-resolution, process-oriented numerical modeling enables the study of fundamental interactions, can test hypotheses, and synthesizes datasets. These models need constraints and validation by data from both laboratory and field campaigns.
This session invites contributions that advance the understanding of small-scale cloud processes. A particular emphasis is placed on synergistic studies that combines laboratory experiments, field observations and/or numerical modeling .
Orals: Tue, 5 May, 14:00–15:45 | Room L1
Cloud microphysical processes on sub-centimeter scales strongly affect precipitation formation, cloud radiative properties, and ultimately large-scale climate. However, both in situ observations and numerical models typically rely on spatial averaging at scales far larger than those at which these processes occur. We present airborne, high-resolution holographic measurements of marine shallow cumulus clouds over the North Atlantic collected during EUREC4A, that provide new insight into the spatial variability of cloud droplet populations.
The Max Planck CloudKite holography system on a tethered balloon samples large localized samples (~10 cm³) of cloud only separated by 10 cm along horizontal cloud transects.
Previous analyses of this dataset have revealed that droplet clustering is a highly localized phenomenon occurring in hotspots on meter and sub-meter scales, with important implications for collision–coalescence rates. Here, we extend the perspective to droplet size distributions. We quantify the scales at which and how often averaged size distributions are representative of local distributions. We find that representativeness is rare: spatial averaging often obscures substantial local variability in droplet size distributions.
This variability indicates distinct locally different growth histories and implies correspondingly different local microphysical process rates. Our results demonstrate that commonly resolved scales in both in situ measurements and model representations are insufficient to capture key aspects of warm-cloud microphysics, highlighting the need to account for small-scale variability when interpreting observations and developing parameterizations.
How to cite: Thiede, B., Larsen, M. L., Nordsiek, F., Schlenczek, O., Bodenschatz, E., and Bagheri, G.: What spatial resolution do we need to resolve shallow cumulus cloud microphysics?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19702, https://doi.org/10.5194/egusphere-egu26-19702, 2026.
Shallow cumulus clouds over tropical oceans play a fundamental role in the Earth’s energy budget. Their microphysical properties strongly influence cloud albedo and climate feedbacks in the tropics. However, the mechanism behind rapid raindrop formation and the role of turbulence in this process remain uncertain, particularly the role of small-scale turbulence in rapid droplet growth. To address this challenge, we analyze in-situ measurements collected during the EUREC⁴A field campaign over the tropical Atlantic near Barbados between January and February 2020. The campaign deployed Max Planck CloudKite, a tethered balloon system, from research vessels, yielding approximately 200 hours of airborne observations within shallow cumulus clouds. A subset of this dataset includes simultaneous planar Particle Image Velocimetry (PIV) and holographic measurements, providing the ability to resolve both turbulent flow properties and cloud microphysics.
The localized measurement of turbulence and droplet size distribution allows, for the first time, the simultaneous investigation of cloud microphysics and turbulence at small scales. Spatial organization of droplets shows a strong correlation with turbulence in the examined clouds. Increased turbulence strengthens voids and clustering regions, particularly in precipitating clouds. We further examine the relationship between droplet size and spatial distribution to comparatively assess the influence of turbulence and entrainment on droplet clustering. This study provides a hint of the crucial role of turbulence in precipitation within the examined shallow cumulus clouds.
How to cite: Kim, Y., Thiede, B., Bodenschatz, E., and Bagheri, G.: In-Situ Measurements of Turbulence Fluctuations and Droplet Clustering in Shallow Cumulus , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20778, https://doi.org/10.5194/egusphere-egu26-20778, 2026.
Warm rain formation in clouds requires rapid coalescence of tiny droplets, a process that pure condensation-driven processes struggle to explain within the short time available in rising cloud parcels. One potential accelerator of droplet growth is electrical charging: it has long been hypothesised that charged cloud droplets might collide and coalesce more efficiently than neutral ones, especially in a turbulent airflow. To investigate this question, we developed a stochastic model tracing droplet pair trajectories at sub-Kolmogorov scales in a turbulent flow field. The model incorporates electrostatic forces, gravitational settling, and shear-induced collisions to simulate realistic encounter rates. Our simulations reveal that even moderate droplet charges can substantially increase collision frequencies under typical cloud turbulence conditions, resulting in the faster growth of droplets into raindrop sizes. These results shed new light on the microphysical mechanisms of precipitation initiation: electric charges on droplets can enhance coalescence efficiency, suggesting that natural background charging in clouds may help bridge the gap between cloud droplet populations and the onset of rain.
How to cite: Bhattacharya, A., Warrier, S., Patra, P., and Roy, A.: Do Charged Cloud Droplets Collide Faster?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-920, https://doi.org/10.5194/egusphere-egu26-920, 2026.
Most simulations of atmospheric phenomena – including both large-eddy simulations (LES) and direct numerical simulations (DNS) – assume phase equilibrium between the liquid and the vapor phases of water. This assumption, however, implies that the relaxation processes for supersaturation fluctuations act on by far shorter time scales than the fastest convective scales, which is debatable for realistic atmospheric conditions. Stratocumulus clouds play an important two-fold role in the Earth's climate as they can have a cooling effect by reflecting large portions of solar radiation to space on the one hand, but insulating the Earth's surface at night on the other hand. An accurate representation of their formation and lifetime in climate projections, calls for a better understanding of the role of supersaturation fluctuations. Here, we investigate the influence of "slow" saturation adjustment on cloud entrainment and desiccation for stratocumulus clouds.
The relative importance of supersaturation fluctuations can be quantified in terms of a Damköhler number Da=τfl/τph defined as the ratio of the flow's mixing time scale τfl over the phase relaxation time scale of supersaturation τph. While the assumption of phase equilibrium corresponds to Da→∞, estimates of realistic atmospheric conditions rather suggest an effective Daη=O(10-2–10-1) with respect to the smallest flow scales, i.e., the Kolmogorov time scale. This indicates that supersaturation fluctuations begin to play a more prominent role.
We perform 3D DNSs of a (stratocumulus) cloud-topped convective boundary layer at Re=5000 and analyze the influence of "slow" supersaturation relaxation for 10-2≤Daη≤101 compared to the case with phase equilibrium assumption Daη=∞. The supersaturation in our simulations is limited to the cloud layer and therein mostly correlating with ascending flow. The largest values of supersaturation up to 4% are found at the cloud base, while within and at the top of the cloud layer, supersaturation is mostly limited to a few tenths of percent. In contrast to these local extreme values, we find that, spatially, cloud bulk and top are (super)saturated to a greater extent than the cloud base. Most crucially, we find that the clouds liquid water content is decreasing for Daη>1, while it is stable for Daη≈1 and even increasing for Daη<1. This implies that clouds tend to dry out and desiccate under phase equilibrium assumption, while they might be rather accumulating in realistic conditions.
How to cite: Hartmann, R. and Mellado, J. P.: The role of supersaturation fluctuations in stratocumulus clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4932, https://doi.org/10.5194/egusphere-egu26-4932, 2026.
Cloud chamber measurements at the laboratory scale can provide valuable information on turbulence-microphysics interactions occurring at small scales in real clouds. We use a minimalistic, stochastic, particle-based model to represent scalar fluctuations at length scales in the inertial range of Rayleigh-Bénard (RB) turbulence in a cloud chamber. The scalars of interest are temperature, vapor mixing ratio of moist air, and the resulting supersaturation affecting droplet growth by condensation. The turbulent flow in the chamber is represented by an ensemble of notional particles that carry a set of Lagrangian attributes such as position, velocity and the scalars of interest. Notional particles represent either fluid particles (in dry and moist RB turbulence) or tracer liquid droplets (in cloudy RB turbulence). The model maintains scalar fluctuations through stationary exchange of temperature and vapor mixing ratio on the chamber walls. No external random scalar forcing, which is usually based on the assumption of equilibrium scalar fluctuation spectrum, is imposed. The statistical analysis of results for moist and cloudy conditions enables direct comparison with experimental data for the Eulerian scalar fields. The results show both qualitative and quantitative agreement with measurements by fitting a single model parameter, the velocity‐to‐scalar time-scale ratio. Despite its intentional simplicity, the model captures essential features previously accessible only through direct numerical simulations (DNS) and provides a practical framework for particle-based modeling of subgrid-scale scalar variance in large-eddy simulations (LES) of clouds.
How to cite: Kumela, I., Grosz, R., and Abade, G.: Minimalistic particle-based model of scalar variability in a cloud chamber, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6899, https://doi.org/10.5194/egusphere-egu26-6899, 2026.
Mixed-phase clouds are widespread throughout the troposphere across all seasons, extending from polar to tropical regions (Korolev & Milbrandt, 2022). These clouds play a critical role in the Earth’s climate system; however, their representation in numerical weather prediction and global climate models remains highly uncertain (e.g., McCoy et al. 2016), largely due to their inherently complex physical nature. Clouds constitute dispersed multiphase flows in which supercooled liquid droplets and ice crystals coexist and interact in and with a turbulent environment over a wide range of spatial and temporal scales (Bodenschatz, et al. 2010). As a consequence of this intrinsic complexity, key uncertainties persist concerning mixed-phase clouds’ microphysical behavior despite extensive observational and laboratory studies. In particular, Lagrangian investigations that resolve the coupled evolution of supercooled droplets and ice crystals remain scarce, especially in turbulent cloud-top regions.
To address these limitations, we employ a Direct Numerical Simulation (DNS) approach to quantify the impact of turbulent temperature and saturation fluctuations on the glaciation of mixed-phase clouds. Within this framework, we investigate the condensational growth of supercooled liquid droplets, heterogeneous droplet freezing, and the subsequent diffusional growth of ice crystals. The simulations are performed using the Eulerian–Lagrangian turbulence solver Tlab (https://github.com/turbulencia/tlab), extended with the TINIA module, which has been developed as an add-on to Tlab to represent ice nucleation and growth processes. We will present first results concerning the influence of turbulence-induced thermodynamic fluctuations on droplet growth, freezing, and ice crystal evolution in mixed-phase clouds.
Korolev & Milbrandt (2022), Geophysical Research Letters, 49(18), e2022GL099578,
https://doi.org/10.1029/2022GL099578
McCoy, et al. (2016), J. Adv. Model. Earth Syst., 8, 650–668,
https://doi.org/10.1002/2015MS000589
Bodenschatz, et al. (2010), Science, 327.5968 : 970-971,
https://www.science.org/doi/10.1126/science.1185138
Acknowledgement:
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project Number STR 453/14-1 (Project name: TINIA).
How to cite: Goharian, K., Niedermeier, D., Schmalfuß, S., Mellado, J. P., Shaw, R., and Stratmamm, F.: DNS of a mixed‐phase cloud with a Lagrangian microphysics scheme, and temperature and supersaturation fluctuations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12317, https://doi.org/10.5194/egusphere-egu26-12317, 2026.
Mixed-phase clouds are ubiquitous in the troposphere during all seasons, from polar to tropical regions, and have a significant impact on weather and climate (e.g., Korolev et al., 2017). Although the knowledge about mixed-phase clouds has increased significantly in recent decades, the relevant microphysical processes and interactions are still poorly understood and insufficiently quantified. For example, how turbulent fluctuations in temperature affect the immersion freezing of supercooled cloud droplets in these clouds remains a key question. To investigate the immersion freezing behavior of supercooled droplets in a turbulent environment, laboratory studies are carried out in the turbulent moist-air wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator, Niedermeier et al. (2020)). The experiments use size-selected, monodisperse Snomax particles as ice-nucleating particles. These particles are injected into the measurement section of LACIS-T where the formation of supercooled droplets, their growth, and the potential freezing occur. The study includes several experiments varying the mean temperature and the magnitude of temperature fluctuations. Droplet freezing is quantified for the different conditions by determining the fraction of frozen droplets as a function of mean temperature and temperature fluctuations. One main result is the observation of immersion freezing at higher mean temperatures compared to conditions without temperature fluctuations. In other words, turbulence affects the number of frozen droplets. The obtained results will be presented in detail and its atmospheric implications will be discussed.
References:
Korolev et al. (2017), Meteorol. Monogr., 58, 5.1-5.50, https://doi.org/10.1175/AMSMONOGRAPHS-D-17-0001.1.
Niedermeier et al. (2020), Atmos. Meas. Tech., 13, 2015-2033, https://doi.org/10.5194/amt-13-2015-2020.
Acknowledgement:
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project Number NI 2231/1-1 (Project name: TINIA).
How to cite: Niedermeier, D., Goharian, K., Schmalfuß, S., Lloyd, P., Shaw, R., Mellado, J. P., and Stratmann, F.: Laboratory studies on the influence of turbulence on heterogeneous ice formation , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9033, https://doi.org/10.5194/egusphere-egu26-9033, 2026.
Mixed-phase clouds (MPCs) are the major source for precipitation over continental mid- and high latitudes. The co-existence of cloud droplets and ice crystals makes MPCs thermodynamically unstable, allowing rapid glaciation through the Wegener–Bergeron–Findeisen (WBF) process and the efficient formation of precipitation-sized hydrometeors. Yet this simultaneous presence of both phases also enables pronounced cloud-phase heterogeneity and intermittency, such that glaciation often does not occur uniformly. Consequently, the apparent efficiency and timescale of glaciation, and its role in MPC evolution, depend on the spatial scale at which phase heterogeneity is represented and resolved.
In this study, we investigate the spatial scales at which phase heterogeneity occurs in MPCs and further assess how unresolved fine-scale variability in cloud phase affects the efficiency and timescale of glaciation. We use in situ observations from 19 targeted glaciogenic cloud seeding experiments conducted during the CLOUDLAB project and compare them with a generalized theory for MPC glaciation times based on the WBF process (Pinsky et al., 2024).
We show that the glaciation time is strongly linked to the spatial resolution at which cloud properties are sampled. Comparing observations averaged on 5, 50, and 250 m spatial scales shows that coarser resolution blurs phase intermittency. Our inferred glaciation times are systematically longer than theoretical predictions, with deviations increasing at coarser resolution. Additionally, our high-resolution in situ measurements show that phase heterogeneity in MPCs extends down to scales of at least one meter and that sub-meter resolution may be required to fully capture the intrinsic microphysical processes.
These results demonstrate that unresolved small-scale phase heterogeneity can systematically bias inferred glaciation times. This bias has direct implications for the evolution and lifetime of mixed-phase clouds and ultimately for the efficiency and timing of precipitation formation.
Pinsky, M., Khain A., and Korolev A., 2014: Analytical investigation of glaciation time in mixed-phase adiabatic cloud volumes. J. Atmos. Sci., 71, 4143–4157, https://doi.org/10.1175/JAS-D-13-0359.1
How to cite: Fuchs, C., Omanovic, N., Zhang, H., Lohmann, U., and Henneberger, J.: How spatial resolution of in situ observations affects the glaciation and evolution of mixed-phase clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12291, https://doi.org/10.5194/egusphere-egu26-12291, 2026.
Field observations of mixed-phase clouds frequently reveal ice particle number concentrations that exceed what can be explained by primary ice nucleation alone. This discrepancy is commonly attributed to secondary ice production (SIP) processes. Despite their recognized importance, the efficiency and representation of SIP mechanisms in numerical weather prediction models remain highly uncertain. One such mechanism is raindrop fragmentation upon freezing: when a supercooled drop freezes, excess internal pressure can cause it to shatter, releasing ice splinters that may subsequently grow to secondary ice particles. A comprehensive understanding and representation of both primary and secondary ice formation processes in mixed-phase clouds is crucial, as these processes strongly influence cloud properties such as precipitation formation and cloud lifetime, and thus affect numerical weather and climate predictions.
In this study, we examine the impact of secondary ice production by raindrop fragmentation upon freezing on cloud glaciation and precipitation within the ICON model framework. We focus on a warm front observed during the Evaluating Microphysical Pathways Of Midlatitude Snow Formation (EMPOS) field campaign in Hyytiälä, Finland, in February 2024, where raindrop fragmentation was directly observed by the Video In Situ Snowfall Sensor (VISSS). This case is ideal for studying raindrop fragmentation upon freezing: frozen hydrometeors fall through a warm layer, melt partially or completely, and refreeze as they enter the sub-zero layer below, creating conditions favorable to raindrop fragmentation upon freezing. We specifically assess potential limitations of the model representation of raindrop fragmentation upon freezing, including the production of sufficient raindrops of relevant size ranges, their refreezing under suitable thermodynamic conditions, and the resulting efficiency of ice splinter generation. We compare the performance of parameterizations for raindrop fragmentation upon freezing in the two-moment microphysics scheme by Seifert and Beheng (2006) – specifically Sullivan et al. (2018) and a newly implemented parametrization based on Phillips et al. (2018) - against observations at the study site. In-situ measurements from the VISSS allow us to constrain and evaluate both model parameterizations of SIP. To complement the bulk microphysics simulations and to gain deeper physical insight into the underlying SIP process, we additionally present first results from the Monte-Carlo super-particle cloud microphysics scheme by Seifert (2018), which better represents mixed-phase states of hydrometeors that bulk-microphysical schemes cannot capture.
How to cite: Meusel, J., Waman, D., Wallentin, G., Hoose, C., Pfeifer, N., and Maahn, M.: Evaluating secondary ice production by raindrop fragmentation upon freezing in mixed-phase clouds using modeling and observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8054, https://doi.org/10.5194/egusphere-egu26-8054, 2026.
From single crystal formation high in the atmosphere down to precipitating snowfalls at ground level, no snowflake takes the same path through the air column. During descent, snow crystals grow, aggregate, break, and rime into graupel while interacting with the surrounding air. Among the well-studied effects of temperature and humidity super-saturation, the specific role of the various turbulence activities throughout the atmosphere remains elusive. In this work, we utilize a novel, flexibly deployable, airborne microscopy platform mounted on an uncrewed aerial vehicle for in-situ imaging of snowflakes up to 120 Meters above ground level during their most ‘turbulent end-of-lifetime’ as they descend through the atmospheric surface layer. Our platform mounts an Infinity K2 DistaMax long-range microscope combined with powerful pulsed LED illumination and a LI-550 TriSonica Mini sonic anemometer for wind characterization on a DJI Matrice 600 Pro hexacopter capable of carrying a 5.5 Kilogram payload. The resolving power of the optical systems allows us to collect 38-Micrometer diffraction-limited high-resolution imagery of snowflakes in freefall at 3 Meters distance, well outside of the drone’s aerodynamic envelope in hovering flight. We will present the first data captured at the start of the 2025 snow season, performed at a professional meteorological field site for cross-validation. Running our system at a 10 Hertz acquisition frequency, we collect a large data sample of 1’500 snowflakes using an online image acceptance and rejection over a relatively small observation volume of approximately 30 cubic Centimeters. Further refining our data sample to 200 best in focus snowflakes, initial data analyses reveal a large variety in snowflake morphology, including dendrite crystals, aggregates, and apparent riming. Extracting morphological metrics of size, aspect ratio, orientation angle, and complexity, we then sort the data and plot statistical distributions. In particular, our data reveals a predominance in horizontal fall orientation, which we discuss in relation to the wind vector.
How to cite: Damani, V., Muller, K., Mamie, L., Roth, B., and Coletti, F.: Imaging the Orientation Dynamics of Snow in Freefall from a Hovering Microscopy Platform, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18422, https://doi.org/10.5194/egusphere-egu26-18422, 2026.
Posters on site: Tue, 5 May, 10:45–12:30 | Hall X5
Title: Moisture and stability controls on raindrop size distribution including breakup signature within convective clouds
The intensity of organised convective systems has been linked to environmental conditions; however, variability across cases suggests non-linear relationships, raising the question of whether diversity or other factors contribute to this variability. Especially, an understanding of cloud microphysical processes in these systems is necessary to bridge gaps between them from both observational and modelling perspectives.
At first, the relationships between raindrop size distributions within convective clouds and their environments were investigated using available observations near Kumagaya, the eastern part of Japan. Collisional coalescence of cloud droplets and raindrops, and conversion from cloud droplets to raindrops, were likely to coincide within convective clouds. Stronger vertical wind shear and higher instability are more likely to be sensitive to more vigorous rainfall intensity, as a proxy for increasing median volume diameter in the drop-size distribution. Weaker vertical wind shear and higher moisture content in the lower layer are likely to be more sensitive to larger rainfall amounts, serving as a proxy for increased liquid water content.
In addition, numerical experiments were conducted using the Weather Research and Forecasting model under idealised conditions based on the observed relationships. This study focused on spatial and temporal features of cloud microphysics with a 250 m horizontal and ~125 m vertical grid spacing across an 80 km x 80 km domain extending 20 km vertically. Initial conditions, obtained from the mesoscale model of the Japan Meteorological Agency for 06 UTC July 12, 2022, were used as input for the sounding and included variations in humidity, temperature lapse rates, and vertical wind shear. A spectral-bin microphysics scheme was primarily used to represent cloud microphysical properties in this study. Results showed that a more moist case in the lower levels led to increased rainfall intensity due to greater drop concentration of relatively smaller raindrops and higher liquid water content within convective clouds compared to the control simulation. Larger temperature lapse rates lead to larger raindrop sizes in convective clouds, which in turn contribute to stronger rainfall intensity. Stronger shear conditions generally lead to stronger rainfall intensity, whilst weaker shear conditions, with smaller temperature lapse rates or in humid environments, lead to larger rainfall amounts. These results may reflect midlatitude-type convection and tropical-type convection, including microphysical interpretations, and were consistent with the observational relationships.
These findings suggest that the established relationships between raindrop size distributions within convective clouds and environments could be extended as a baseline for operational quantitative precipitation estimation and to improve the microphysical scheme.
How to cite: Unuma, T.: Moisture and stability controls on raindrop size distribution including breakup signature within convective clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-376, https://doi.org/10.5194/egusphere-egu26-376, 2026.
Cirrus cloud optical properties strongly depend on the orientation of nonspherical ice crystals, which are influenced by the interplay between turbulence and gravitational settling. In this study, we introduce a stochastic modelling framework that predicts ensemble-averaged light scattering from ice crystals with turbulence-driven orientation distributions. The orientation statistics are derived from a stochastic representation of turbulent velocity gradients, and single-particle scattering properties are computed using a Lattice Boltzmann Method–based electromagnetic solver. Integrating over the derived orientation probability density function yields bulk optical quantities such as phase functions and scattering intensities. Results show that turbulence modulates scattering anisotropy and phase function features, revealing measurable optical impacts even in weakly turbulent regimes. The framework offers a physically consistent and computationally efficient approach for incorporating orientation effects into radiative transfer and remote sensing models of ice clouds.
How to cite: Mishra, H., Khan, M., and Roy, A.: Light scattering by ice crystals in homogeneous isotropic turbulence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-955, https://doi.org/10.5194/egusphere-egu26-955, 2026.
Understanding how cloud droplets transition across the “size gap” between condensational growth and efficient gravitational collection remains central to predicting warm-rain formation in turbulent clouds. We examine this transition by solving the Smoluchowski Coagulation Equation with a high-order, mass-conserving flux scheme and by comparing a suite of physically grounded hydrodynamic collision kernels. These kernels combine differential settling with turbulence-driven relative motion and explicitly account for near-field interactions—non-continuum lubrication forces and van der Waals attraction—that strongly influence coalescence at small separations. By diagnosing the evolution and convergence of mass flux across droplet sizes, we assess how different kernel formulations accelerate or delay growth through the bottleneck regime and whether the resulting distributions exhibit quasi-steady or self-similar structure. The study provides quantitative insight into how turbulence-modified microphysical interactions shape droplet size distributions and ultimately regulate warm-rain initiation in atmospheric clouds.
How to cite: Halder, A., Patra, P., Chandrakar, K. K., and Roy, A.: Evaluating Droplet Size Distribution Evolution with Physically Based Collision Kernels in Warm Cumulus Clouds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1063, https://doi.org/10.5194/egusphere-egu26-1063, 2026.
The recently discovered “W-Layer” reveals an unexplored perspective in the modelling of the stratocumulus-topped boundary layer (STBL). The clear-sky radiative heating in the capping inversion, which constitutes the W-Layer, was previously unresolved in numerical models, either because of insufficient vertical resolution or the lack of an appropriate radiation model which represents the clear-sky effects.
To study the impact of the W-Layer on the STBL, we introduce a “band” radiation model to direct numerical simulations (DNSs) which resolve metre-scale features. The band model partly retains the spectral dependence of the clear-sky absorption by partitioning the longwave spectrum into two water vapour absorption bands, one CO2 absorption band and a window region. The band model is computationally efficient and can reproduce the warming characteristics in the W-Layer.
We run a set of DNSs at Reynolds number Re = 5000, which corresponds to a vertical resolution of 2.2 m at the cloud top. We find that the W-Layer causes a direct effect of warming, which is most prominent in the cloudy region, leading to a slight drop in liquid water content. Meanwhile, an indirect effect of the W-Layer suppresses entrainment and the STBL growth rate by enhancing the buoyancy jump across the capping inversion. Correspondingly, the turbulence and convection intensity is reduced.
How to cite: Chan, K., Mellado, J. P., Buehler, S. A., and Brath, M.: From five metres to one kilometre: How does the W-Layer shape the stratocumulus-topped boundary layer?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3167, https://doi.org/10.5194/egusphere-egu26-3167, 2026.
Rain evaporation drives mesoscale organization through downdrafts and cold pools, influencing cloud cover and the radiative budget, yet its magnitude and variability remain poorly constrained by observations and models. To address this gap, we develop a rain evaporation dataset at the Barbados Cloud Observatory (BCO) using observations from the SCORE (Sub-Cloud Observations of Rain Evaporation) sub-campaign of ORCESTRA. Because rain evaporation cannot be measured directly, it must be inferred from changes in the drop size distribution (DSD) as rain falls. DSDs can be derived from cloud radar Doppler spectra, but these are affected by vertical air motion, turbulence broadening, and attenuation.
By using Doppler spectra from BCO cloud radars at two frequencies (Ka- and W-band), we can overcome the limitations of single-frequency approaches and retrieve the full shape and concentration of the DSDs. The application of an optimal estimation method to this data also allows us to retrieve total differential attenuation, vertical velocities, and turbulence. We derive rain evaporation rates from DSDs during stationary periods. These retrievals can be used to evaluate evaporation estimates from one-dimensional rain shaft models, including the super-droplet model CLEO. If robust, the retrieved cloud-base DSDs provide a basis for fast and reliable long-term rain evaporation estimates at the BCO. Here we present first results from the SCORE evaporation and environmental conditions dataset, including analyses of individual rain events and statistics from the full sub-campaign.
How to cite: Robbins-Blanch, N., Poydenot, F., Tridon, F., Schnitt, S., Acquistapace, C., and Vogel, R.: Dual-frequency radar retrievals of rain evaporation at the Barbados Cloud Observatory during the ORCESTRA-SCORE campaign, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7908, https://doi.org/10.5194/egusphere-egu26-7908, 2026.
As hydrometeors in the upper troposphere are usually solid, especially in winter, ice crystals, snow, and graupel serve as important aerosol scavengers in the atmosphere. Electrostatic forces are highly relevant to the removal of submicron aerosol particles (APs), as they provide an additional mechanism for capturing particles that might otherwise be difficult to remove from the atmosphere. However, this type of scavenging is less well understood than scavenging by liquid hydrometeors, both theoretically and experimentally. Motivated by gaps in knowledge regarding the scavenging of APs by ice crystals, we investigated the impact of electrostatic collection of APs by solid hydrometeors on the scavenging of APs from the air. Collection kernels were calculated for discrete values of the diameters of cloud ice, snow, and graupel. These kernels were then implemented in a cloud-resolving numerical model, using a three-moment microphysical scheme with six separate hydrometeor categories, along with a two-moment aerosol scheme introduced by Vučković et al. (2022). We also considered electroscavenging processes for liquid hydrometeors, where, in addition to the point Coulomb force interaction, image charge induction was included, following previous work (Vučković et al., 2025a). This effect was not considered for solid hydrometeors. All other known collection mechanisms were also included. The aerosol particles were treated as ice-nucleating (with AgI properties) and non-nucleating in separate experiments. Our results suggest that the reduction in the total mass of aerosol particles in the air caused by electrostatic scavenging by liquid hydrometeors was greater than that caused by electrostatic scavenging by cloud ice by a factor of six after one hour of model integration. Electrostatic scavenging by solid hydrometeors increased the relative aerosol precipitation mass by less than 0.1%, while the inclusion of liquid hydrometeor electrostatic scavenging increased the aerosol precipitation mass by 24% (Vučković et al.,2025b).
Acknowledgements: This research was supported by the Science Fund of the Republic of Serbia, No. 7389, Project “Extreme weather events in Serbia – analysis, modelling and impacts” – EXTREMES.
References:
Vučković, V., D. Vujović, and A. Jovanović, 2022: Aerosol parameterisation in a three-moment microphysical scheme: Numerical simulation of submicron-sized aerosol scavenging. Atmos Res, 273, 106148, https://doi.org/10.1016/j.atmosres.2022.106148.
Vučković, V., D. Vujović, D. Savić, and L. Filipović, 2025a: Impact of electro-collection and ice nucleation on aerosol scavenging. Aerosol Science and Technology, 59, 1006–1026, https://doi.org/10.1080/02786826.2024.2441289.
Vučković, V., D. Vujović, D. Savić, and L. Filipović, 2025b: The Effect of Electrocollection by Ice Hydrometeors on the Scavenging of Submicron-Sized Aerosol Particles. Atmosphere (Basel), 16, 1265, https://doi.org/10.3390/atmos16111265.
How to cite: Vučković, V., Vujović, D., Savić, D., and Filipović, L.: Assessing the effect of electrocollection by ice and liquid hydrometeors on the scavenging of submicron-sized aerosol particles, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8175, https://doi.org/10.5194/egusphere-egu26-8175, 2026.
Damages associated with severe convective storms are increasing worldwide, motivating the continued use of weather modification techniques such as cloud seeding for hail mitigation. Despite decades of operational application in many countries, including Serbia, the physical effectiveness of convective cloud seeding remains insufficiently quantified due to the complexity and a wide range of physical processes in clouds.
Numerical models provide a valuable tool for examining cloud processes in depth and help us understand aerosol-cloud interactions. We use a cloud-resolving numerical model with three-moment microphysics to simulate a supercell storm. This model is modified by introducing aerosols with all known scavenging mechanisms (by 5 hydrometeor categories) included (Vučković et al. 2025b). This is achieved by implementing a two-moment aerosol scheme, where aerosols are described by the gamma distribution (Vučković et al. 2022, 2023, 2025a). Furthermore, DeMott silver-iodide freezing parameterisation is implemented. This method provides a way to track number concentration and mixing ratios of aerosols explicitly in the air and in all 6 hydrometeor categories for every grid box. Simulations are performed at 500 m horizontal and 250 m vertical resolution over a 3-hour integration period.
On the other hand, two complex operational convective cloud seeding methodologies have been implemented into the model. First developed by the Republic Hydrometeorological Service of Serbia (RHSS 2023) and the other proposed by Abshaev et al. (2023). Both methodologies consider the radar reflectivity and supercooled water parameters as well as the storm's movement and life-cycle stage to determine seeding timing and location.
This framework enables a direct numerical comparison of the microphysical and dynamical impacts of operational hail suppression strategies under controlled conditions.
Acknowledgement: This research was supported by the Science Fund of the Republic of Serbia, No. 7389, Project Extreme weather events in Serbia - analysis, modelling and impacts” – EXTREMES
References:
Abshaev, M. T., Abshaev, A. M., & Malkarova, A. M. (2022, May). Results of 65-Years Project of Hail Suppression in Russian Federation. In International Scientific Conference" Problems of Atmospheric Physics, Climatology and Environmental Monitoring" (pp. 1-28). Cham: Springer International Publishing.
Republic Hydrometeorological Service of Serbia, Hail Suppression Center (2023). Instruction 5/2023: Methods for radar identification and seeding of single-cell, multicell, and supercell hail-producing storms using the OGIS automated system. Belgrade, Serbia. (in Serbian, Cyrillic)
Vučković, V., D. Vujović, and A. Jovanović, 2022: Aerosol parameterisation in a three-moment microphysical scheme: Numerical simulation of submicron-sized aerosol scavenging. Atmos Res, 273, 106148, https://doi.org/10.1016/j.atmosres.2022.106148.
Vučković, V., D. Vujović, and D. Savić, 2023: Influence of electrostatic collection on scavenging of submicron-sized aerosols by cloud droplets and raindrops. Aerosol Science and Technology, 57, https://doi.org/10.1080/02786826.2023.2251551.
Vučković, V., Vujović, D., Savić, D., & Filipović, L. (2025a). Impact of electro-collection and ice nucleation on aerosol scavenging. Aerosol Science and Technology, 59(8), 1006–1026. https://doi.org/10.1080/02786826.2024.2441289
Vučković, V., Vujović, D., Savić, D., & Filipović, L. (2025b). The Effect of Electrocollection by Ice Hydrometeors on the Scavenging of Submicron-Sized Aerosol Particles. Atmosphere, 16(11), 1265. https://doi.org/10.3390/atmos16111265
How to cite: Savić, D., Vučković, V., and Vujović, D.: Explicit numerical simulations of convective cloud seeding for hail mitigation using two operational methodologies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9376, https://doi.org/10.5194/egusphere-egu26-9376, 2026.
Clouds constitute an ensemble of a huge number of particles. A general approach for representing the system is the use of size or mass distributions, leading to a population balancing equation (PBE). Since solving this equation is quite challenging and computationally expensive, numerical weather prediction models often use so-called bulk schemes, based on general moments of the underlying distribution, and assuming a fixed functional form for the particle size distribution, from which evolution equations for the moments are derived. These schemes are much simpler and computationally cheaper, though they overly constrain the evolution of the size distribution.
In this work, we directly address the problem of solving the PBE for the mass distribution of atmospheric hydrometeors. We present analytical solutions for idealized cases and reduce more complex scenarios to systems of ordinary differential equations, which can be numerically integrated. These analytical solutions can be compared to the standard bulk schemes, testing the accuracy of the latter. Future work will involve extending these solutions to more complicated regimes and validating the results against empirical field measurements of the hydrometeor size distributions.
How to cite: Torregrosa Abellan, A.: Solutions to the population balance equation for cloud hydrometeors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9886, https://doi.org/10.5194/egusphere-egu26-9886, 2026.
It is known that cloud droplet sedimentation affects the development of stratocumulus-topped boundary layers by reducing entrainment. However, previous studies mainly focused on timescales below 6h covering the early stratocumulus stages, while later timescales remain largely unexplored. This study targets the impact of sedimentation on subtropical stratocumulus evolution in the context of the stratocumulus to cumulus transition (SCT) in the Northeast Pacific. To this end, we perform 48h long large-eddy simulations of 10 transects from the Marine ARM GPCI Investigation of Clouds ship campaign, capturing the full deepening phase prior to cloud breakup.
In all cases of active droplet sedimentation, the previously reported reduction in entrainment is confirmed in the initial hours. However, the effects observed in the later stages differ depending on the cloud's liquid water path (LWP). The expected result of weaker boundary layer growth only continues to occur in the more frequent precipitating, high-LWP cases, whereas the opposite occurs in non-precipitating, low-LWP cases. Here, the initial effect is reversed and the cloud exhibits stronger entrainment, that can result in deeper boundary layers. The underlying reason is that low-LWP clouds are radiatively unsaturated, allowing the LWP increase associated with the initial reduction in entrainment to trigger a feedback chain, which amplifies LWP, longwave cooling and turbulence in the boundary layer. This counteracts the impact of the sedimenting droplets and ultimately yields increased entrainment. Previous process studies on droplet sedimentation have studied the low-LWP regime, where we actually find an opposite response over long time periods. Nonetheless, our results confirm the interpretation of the droplet sedimentation feedback in numerous aerosol-cloud interaction studies as these are applicable to the high-LWP regime where we show that also over long time scales droplet sedimentation decreases boundary layer deepening. Despite the substantial influence on boundary layer growth, the timing of cloud breakup remains largely unchanged across the transition.
How to cite: Schnelke, M., Ahlgrimm, M., and Possner, A.: Opposing entrainment effects of cloud droplet sedimentation during the pre-breakup stage of the stratocumulus to cumulus transition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11752, https://doi.org/10.5194/egusphere-egu26-11752, 2026.
The number of ice particles in mixed-phase clouds often exceeds the concentration of ice-nucleating
particles by several orders of magnitude. This discrepancy can be explained by secondary ice
production, which is a set of physical processes that can multiply the number of ice particles in the
atmosphere. Due to their transient and microscopic nature, observations and quantifications of these
processes are scarce. One such process is the fragmentation of drops upon freezing, whereby ice
splinters are produced when a drop undergoes a phase transition from liquid to ice. Recent
laboratory studies suggest that this process could significantly contribute to ice crystal number
concentrations. However, the number of ice fragments that can be produced under realistic
atmospheric conditions remains highly uncertain.
In this talk, we present cases of droplet fragmentation occurring during refreezing rain episodes in
Hyytiälä, Finland. These cases were identified using a combination of ground-based in situ
observations and cloud radar. Based on the classification of in situ image data, we evaluate the
effectiveness of the process from an event-based perspective. Additionally, we identify the different
modes of deformation that occur during refreezing and demonstrate how their frequencies change
over time.
These results provide novel insights into the effectiveness of drop fragmentation upon freezing,
addressing a long-standing knowledge gap in cloud microphysics.
How to cite: Pfeifer, N., Mom, B., Dmitri, M., Hartmann, S., Meusel, J., Hoose, C., and Maximilian, M.: Efficient ice multiplication from freezingraindrop fragmentation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11910, https://doi.org/10.5194/egusphere-egu26-11910, 2026.
Large-scale models struggle to accurately represent maritime low-level boundary layer clouds, leading to uncertainties in projecting a future climate. This study uses a regime-based approach to assess global climate model representation of warm-phase microphysical processes over the Southern Ocean (SO) and northeast Pacific, regions frequently characterized by the stratocumulus-to-cumulus transition (SCT) regime. In situ aircraft observations collected during the Southern Ocean Clouds, Radiation and Aerosol Transport Experimental Study (SOCRATES) and the Cloud Systems Evolution in the Trades (CSET) campaigns were used to evaluate simulated low-level cloud microphysical properties. Using environmental variables and airborne remote sensing, we investigate methods for compositing aircraft observations into stratocumulus, open-cell, and undetermined cloud sampling regimes. This approach aims to mitigate issues with scaling aircraft observations to model grid resolutions and discrepancies with collocating aircraft observations with simulated clouds. We assessed simulated warm-phase cloud processes in the Community Earth System Model (CESM) using new model diagnostics tools to improve our representation of the SCT regime, and results from both CESM2 and CESM3 will be presented.
How to cite: Patnaude, R., Richling, J., Truesdale, J., Simpson, I., Petch, J., and McCluskey, C.: Rethinking how to characterize cloud biases in coarse resolution models: a regime-based approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13299, https://doi.org/10.5194/egusphere-egu26-13299, 2026.
The armored T-28 aircraft obtained in-situ imaging probe observations in hailstorms over multiple field projects. The T-28 is unique in its ability to sample hailstorms containing particles up to 3 inches in diameter. Particle size distributions derived from the imaging probe observations are invaluable for comparison with the CSU-CHILL S-band polarimetric radar. Images from the T-28 Hail Spectrometer are typically processed using one-dimensional (1D) size information; however, an instrument upgrade enabled two-dimensional (2D) sizing capabilities for multiple field projects. Particle size distributions from 14 flights that include both 1D and 2D Hail Spectrometer processing are analyzed. Consistently, 1D processing results in larger maximum particle sizes and lower concentrations of small particles. Review of 2D images shows that the typical 1D processing method overestimates particle sizes due to noise and coincidence effects; therefore, the 2D processing methodology should be used for creating particle size distributions. Reflectivity calculated using the 2D particle size distribution is substantially lower than reflectivity calculated using the 1D particle size distribution. Hence, more water inclusion is necessary to match the CSU-CHILL radar observations.
How to cite: Delene, D., Klinman, J., Detwiler, A., Coleman, S., Skow, A., Hernandez, I., Kennedy, P., and Chandrasekar, V.: T-28 Aircraft Image Probe Data Processing: Hail Storm Uncertainty and Radar Coupling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14691, https://doi.org/10.5194/egusphere-egu26-14691, 2026.
Cloud droplet temperature plays a key role in fundamental cloud microphysical and radiative processes. The supercooled droplet temperature and lifetime can impact cloud ice and precipitation formation via homogeneous freezing and activation of ice-nucleating particles through contact and immersion freezing. While most observational and modeling studies often assume droplet temperature to be spatially uniform and equal to the ambient temperature (Ta), this assumption may not always be valid, particularly when droplets experience strong relative humidity (RH) gradients at cloud boundaries.
For a wide range of ambient conditions, we model the coupled heat and mass transfer between the droplet and its environment and quantify the decrease in droplet temperature (ΔT) from that of the far-away ambient temperature (Ta), and the increase in droplet lifetime due to reduced droplet surface temperatures, compared to Maxwellian diffusion-limited evaporation estimates. ΔT is found to increase with Ta, and decrease with increase in ambient relative humidity (RH), and pressure (P). For a prescribed environment and assuming the droplet has infinite thermal heat conductivity, ΔT was typically 1-5°C lower than Ta, with highest values (~10.3°C) for very low RH, low P, and Ta closer to 0ºC. For higher RH and larger droplets, droplet lifetimes can increase by more than 100s compared to the diffusion-limited evaporation approach, which ignores droplet cooling. The steady state temperature of evaporating droplets can be approximated by environmental thermodynamic wet-bulb temperature. Radiation was found to play a minor role in influencing droplet temperatures, except for larger droplets in environments close to saturation. If we resolve the spatiotemporally varying thermal and vapor density gradients near the evaporating droplet, results demonstrate a higher subsaturation-dependent decrease in the droplet temperature as well as the envelope of air in the vicinity of the droplet surface. For an ambient environment specified far away, with Ta = -5°C, RH = 10%, 40%, and 70%, the decrease in droplet temperatures due to evaporative cooling is ~ 24, 11, and 5°C, respectively and the evaporatively cooled droplets survive longer compared to previous estimates.
The implications of evaporative cooling and increased lifetimes of supercooled cloud droplets on potential enhancement of ice nucleation near evaporating cloud edges, such as cloud-top generating cells, and especially for moderately supercooled ambient temperatures, are discussed. The importance of using accurate droplet temperatures to improve activated ice nuclei number concentrations from existing primary ice nucleation parameterization schemes, especially in sub-saturated environments, is highlighted. Finally, using high-resolution direct numerical simulations of moderately supercooled cloud boundaries, we discuss the impacts of droplet evaporative cooling on the evolution of supercooled droplet size distributions, which critically impacts ice nucleation.
How to cite: Roy, P., Chen, S., Xue, L., Tessendorf, S., M. Rauber, R., and Di Girolamo, L.: Investigation of supercooled cloud droplet evaporation through very high-resolution numerical modeling, with implications for ice nucleation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15701, https://doi.org/10.5194/egusphere-egu26-15701, 2026.
Radar simulators enable quantitative evaluation of cloud resolving models by translating predicted hydrometeor populations into synthetic radar observations (e.g., reflectivity) comparable to measurements. Most existing simulators are designed for Eulerian bulk or bin microphysics schemes and require gridded size-distribution information that is not directly available from Lagrangian particle-based approarches such as the Super-Droplet Method (SDM). Here we assess the feasibility and current limitations of driving an existing radar simulator using SDM output through a bin-type conversion. Within each model grid cell, super-droplets are categiorized based on phase and size to construct particle size distributions on fixed diameter bins. The resulting simulations capture liquid-phase (rain) signatures reasonably well, indicating that the binning approarch preserves key information needed for warm-rain radar signals. In contrast, simulated radar signatures associated with ice particles remain more uncertain, largely because additional assumptions are required during conversion and scattering calculations (e.g., ice particle habit and density), and because some super-droplet information is not yet fully utilized in the simulator interface. We discuss how the rich attributes carried by super-droplets can be leveraged to better constrain ice particle properties and to develop a more direct, standardized pathway from SDM to radar-simulator-ready inputs, enabling more robust radar-based evaluation of small-scale cloud microphysical processes.
How to cite: Nirasawa, Y., Alhilali, M., Shima, S., Matsugishi, S., Roh, W., Hashino, T., and Miyakawa, T.: From super-droplets to synthetic radar observations: applying a radar simulator to SDM using bin-type data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16303, https://doi.org/10.5194/egusphere-egu26-16303, 2026.
Microscale properties of cloud particles govern processes that influence weather and climate from local to global scales, yet accurate detection and quantification of these properties remains a fundamental challenge. Addressing this, recently launched and planned satellite missions have prioritized instrument development based on multi-angle polarimetric imaging of particle light scattering. However, obtaining quantitative microscale properties from these measurements relies on retrieval algorithms that require robust validation against high-fidelity, in-situ data.
To address this critical need, we introduce the Hyper-Angular Cloud Polarimeter - Prototype Version (HACP-PV), a novel in-situ instrument designed and manufactured by schnaiTEC. The instrument's design foundation is shared with the optical principles of satellite-platform multi-angle polarimetry. Independent modulation of the instrument’s emitted and received light polarization states enables direct measurements of the unique elements needed to fully constrain the scattering matrix of the sample volume. We resolve angular scattering functions from approximately 101.5° to 168.5° at a resolution finer than 0.1°, tightly constraining measurements of the Particle Size Distribution (PSD). Crucially, the HACP-PV features an open-path sampling design, eliminating inlet-based sampling artifacts that typically introduce measurement uncertainty. We leverage these complete, artifact-free, scattering signatures to quantify key cloud microphysical quantities, including liquid water content and effective droplet diameter. In addition, the polarimetric measurements offer high sensitivity for discriminating ice from liquid particles, which is crucial for understanding phase-partitioning in mixed-phase clouds.
We report on the progress in bringing this prototype version of the HACP from concept to reality. Our presentation overviews its novel design and summarizes calibration metrics and performance benchmarks from laboratory characterization. We highlight results from an initial deployment in a controlled, cloud-simulating wind tunnel environment, demonstrating the first retrievals of high-fidelity, complete scattering matrix measurements for liquid droplet clouds. Subsequent evaluation of these measurements against scattering calculations based on Mie theory validates the instrument's measurement principle and demonstrates its readiness for synergistic cloud physics research across laboratory and field domains.
This prototype establishes a pathway towards a new benchmark for satellite validation or even serving as a reference standard at operational monitoring networks. Its direct, high-resolution measurements enable rigorous validation of remote sensing algorithms and assumptions. Ultimately, this work contributes to more accurate polarimetric scattering measurements of clouds, facilitating improved constraints on quantitative microphysical estimates, and an advanced understanding of small-scale cloud physics.
How to cite: DeLaFrance, A., Ballington, H., Järvinen, E., and Schnaiter, M.: Constraining Small-Scale Cloud Microphysics with High-Resolution Scattering: The Novel Hyper-Angular Cloud Polarimeter and Synergistic Applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20222, https://doi.org/10.5194/egusphere-egu26-20222, 2026.
The method of ice crystal replication in Formvar (polyvinyl formal resin) was introduced by Vincent Schaefer in 1941 [1]. At that time no aircraft based optical instrumentation was available to study the morphology of ice crystals. In spite of the rapid advance of the sophisticated optical particle probes, the formvar replication technique, applied in its very original form, turns out to be a valuable complimentary method for the ice crystal habit characterization [4].
In addition to habit and surface morphology, some formvar replicas preserve residual particles that may have acted as ice nucleating particles (INPs). Early attempts to identify these nuclei (e.g. Kumai, 1951 [2] and Koenig, 1960 [3]) were limited by poor instrumental resolution and lack of accurate elemental analysis. Modern scanning electron microscopy and X-Ray spectroscopic techniques allows us to revisit this approach. The ice nucleating particles preserved within the replicas can be characterized and attributed to the ice crystal habits and sampling environmental conditions. Based on several case studies, including ice nucleation experiments conducted in AIDA chamber and analysis of formvar replicas of ice crystals collected from free atmosphere and by airborne probes, we evaluate the potential of the ice replication method combined with SEM analysis for INP identification.
References:
[1] Schaefer, V. J.: A method for making snowflake replicas. Science, 93 (1941) pp. 239-240.
[2] Kumai, M.: Electron-microscope study of snow-crystal nuclei. J. Atmos. Sci., 8 (1951) pp. 151-156.
[3] Koenig, L. R.: The chemical identification of silver-iodide ice nuclei: a laboratory and preliminary field study. J. Atmos. Sci., 17 (1960) pp. 426-434.
[4] Miloshevich, L. M. and Heymsfield, A. J.: A Balloon-Borne Continuous Cloud Particle Replicator for Measuring Vertical Profiles of Cloud Microphysical Properties: Instrument Design, Performance, and Collection Efficiency Analysis, J. Atmos. and Oceanic Tech., 14 (1997), pp. 753-768.
How to cite: Arnold, L., Zanger, F., Schnaiter, M., Hamel, A., Schmitt, C., Heymsfield, A., Wex, H., Fuchs, C., Henneberger, J., and Kiselev, A. A.: A hidden treasure: ice nucleating particles preserved inside formvar replicas of ice crystals can be identified using scanning electron microscopy , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20615, https://doi.org/10.5194/egusphere-egu26-20615, 2026.
Ice crystal surface roughness influences the global shortwave cloud radiative effect by an estimated 1-2 Wm-2 and affects backscattering properties required for lidar retrievals, yet the microscale structure of atmospheric ice particles remains poorly constrained. In-situ observations indicate that rough and irregular surfaces are common, but insufficient measurements linking particle imagery to angular scattering data limit the development of representative shape models.
During a flight of the CIRRUS-HL campaign in summer 2021, an unusually large proportion of quasi-spherical ice particles resembling frozen droplets were observed by the Particle Habit Imaging and Polar Scattering probe (PHIPS). We use this dataset as a case study to constrain surface roughness in ice clouds. PHIPS provides particle imagery from two viewing angles alongside simultaneous scattering measurements from 18 to 170°. Several thousand single, chain, and aggregated frozen droplets were identified, with mean radius ~14 μm (size parameter X ≈ 200).
We model these particles using the droxtal geometry, and compute scattering properties using a beam tracing physical optics method. Preliminary results indicate pristine droxtals are insufficient to reproduce observed scattering, suggesting that surface roughness cannot be ignored.
The surface roughness implementation is characterised by a mesh edge length and vertex displacement amplitude. Ensembles of roughened droxtals with radii sampled from the measured size distribution are compared against PHIPS measurements using a novel Bayesian optimisation implementation to efficiently explore the 2D roughness parameter space. We present results and discuss implications for constraining ice crystal roughness from in-situ measurements.
How to cite: Ballington, H., DeLaFrance, A., Järvinen, E., and Schnaiter, M.: Characterising Surface Roughness in Ice Clouds Using In-Situ Measurements of Frozen Droplets and Bayesian-Optimised Physical Optics Simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20869, https://doi.org/10.5194/egusphere-egu26-20869, 2026.
Turbulent entrainment at cloud top regulates exchange across the cloud–clear-air interface and shapes cloud microphysical structure, variability, and evolution. Yet the governing gradients and mixing events remain difficult to represent in models and to observe with sufficient vertical context, largely due to limited observational capabilities at small scales. Furthermore, quantifying turbulent transport requires high-frequency measurements of vertical velocity and scalar quantities.
Here, we present first results on cloud-top entrainment from the IMPACT field campaign (”In-situ Measurement of Particles, Atmosphere, Cloud and Turbulence”, May-June 2024) in Pallas, Finland, under polar-day conditions. During IMPACT, we deployed the Max Planck WinDarts, lightweight airborne in situ probes designed for vertically distributed measurements on the Max Planck CloudKite (a tethered kite-balloon system). Each WinDart provides high-resolution measurements of 3-D wind, temperature, relative humidity, and pressure, enabling the derivation of turbulent statistics and fluxes across a vertical column. By deploying four WinDarts spaced 50 m apart along the tether, we estimate vertical turbulent fluxes of heat and moisture in the cloud-top region. The vertically resolved measurements provide insights into entrainment processes, turbulence statistics and scalar variability near the cloud top. The findings also demonstrate the potential of tethered, vertically distributed in situ sampling to advance our understanding of entrainment processes.
How to cite: Chávez-Medina, V., Khodamoradi, H., Bodenschatz, E., and Bagheri, G.: Cloud-top entrainment during polar day: first results from in situ observations in Pallas, Finland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21115, https://doi.org/10.5194/egusphere-egu26-21115, 2026.
