Cloud Droplet Size Distribution Research Articles

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.

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.

Cloud droplet size distributions governed by condensation, collision–coalescence, and sedimentation. Part 1: 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 2: 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 power-law tail at sufficiently large radius. The solutions are formally valid for a convection-cloud chamber, but can also be extended to shallow, mixed-layer clouds such as mixing fogs.

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large‐Eddy Simulations of Low‐Level Warm Clouds

AbstractIn numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate , which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local is commonly parameterized as a function of DSD moments: cloud droplet number and mass concentrations. When applied in a large‐scale model, the grid‐mean must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large‐eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local , as well as its spatial variability. The analysis of an ensemble of warm low‐level cloud cases shows that the E3SMv2 formulation represents the reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM‐tuned local rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of and its co‐variability with in parameterizing the grid‐mean .

Design and experiment of a lightweight cloud particle imager

Abstract Accurate in-situ measurement of cloud microphysical parameters such as particle diameter, number concentration and droplet spectrum distribution are of great significance in cloud physics, climate change, numerical weather forecasting and weather modification. This work describes the design and characterization of a newly developed in situ measurement instrument for cloud and fog named lightweight cloud particle imager (LCPI). The basic measurement principle of LCPI is based on scattering light imaging of particles in a dark field. A ring LED lighting source was designed to improve the image quality. Field measurements were carried out at a high-altitude research station on Lushan Mountain. The measured size distributions showed good agreement with parallel measurements of a cloud droplet spectrometer (fog monitor-120). The field data also showed that LCPI was able to measure the size distribution of cloud droplets from 5 to 300 μm with a high spatial resolution. In addition, another observation experiment carried out in the Tuli River weather station showed that LCPI also had the ability to acquire clear images of ice crystal particles larger than 10 μm. Thus, LCPI provides an opportunity to simultaneously quantify the microphysical structure of different cloud types.

Impact of cloud properties and aerosols on the spatial distribution of Indian summer monsoon rainfall: A case study

Quantitative seasonal Indian summer monsoon (ISM) rainfall forecasting has been a challenge for the climate models as it is sensitive to cloud properties, which are modulated by large-scale dynamics. Proper understanding of the role of dynamics, aerosols, and cloud microphysical processes is important for the precipitation calculation in dynamical models. The all-India averaged seasonal ISM rainfall (ISMR) from June to September had been normal or above normal, however there were large spatial variations. Some meteorological subdivisions, the majority of which lie in the Gangetic Plains, received deficient seasonal rainfall during recent years 2022 and 2010. The quantitative seasonal prediction of the spatial distribution of ISMR from global coupled models (GCMs) has also shown a hard time for accurate spatial rainfall distribution. Four monsoon years (2022, 2021, 2011, and 2010) are considered, in which the country as a whole (all India land points) was ‘above normal’ or ‘normal’. However, in two specific years (2022 and 2010), some subdivisions received deficient rainfall (17% and 15% of the total area). We have used several datasets from the ground, and satellite observations, along with reanalysis products and computed climatology and anomalies for monsoon years of 2022 and 2010. The low-level wind and vertical velocity along with cloud microphysics played a pivotal role in the heterogeneous distribution of ISMR during 2022 and 2010 as compared to years 2021 and 2011. Here, we have demonstrated that the spatial heterogeneity of the positive and negative precipitation anomalies was consistent with cloud properties. Aerosols might have an impact on the cloud microphysical processes and modulate cloud properties and rainfall over different regions due to the availability of water vapor. Therefore, the inclusion of aerosol indirect effects in climate models is crucial for better interactions among dynamics, aerosol, and cloud microphysics. Proper representation of cloud droplet size distribution and microphysical conversion rates might be helpful for quantitative seasonal ISMR forecasting at a smaller spatial scale.

Are turbulence effects on droplet collision–coalescence a key to understanding observed rain formation in clouds?

Rain formation is a critical factor governing the lifecycle and radiative forcing of clouds and therefore it is a key element of weather and climate. Cloud microphysics-turbulence interactions occur across a wide range of scales and are challenging to represent in atmospheric models with limited resolution. Based on past experiments and idealized numerical simulations, it has been postulated that cloud turbulence accelerates rain formation by enhancing drop collision-coalescence. We provide substantial evidence for significant impacts of turbulence on the evolution of cloud droplet size distributions and rain formation by comparing high-resolution observations of cumulus congestus clouds with state-of-the-art large-eddy simulations coupled with a Lagrangian particle-based microphysics scheme. Turbulent coalescence must be included in the model to accurately represent the observed drop size distributions, especially for drizzle drop sizes at lower heights in the cloud. Turbulence causes earlier rain formation and greater rain accumulation compared to simulations with gravitational coalescence only. The observed rain size distribution tail just above cloud base follows a power law scaling that deviates from theoretical scalings considering either a purely gravitation collision kernel or a turbulent kernel neglecting droplet inertial effects, providing additional evidence for turbulent coalescence in clouds. In contrast, large aerosols acting as cloud condensation nuclei ("giant CCN") do not significantly impact rain formation owing to their long timescale to reach equilibrium wet size relative to the lifetime of rising cumulus thermals. Overall, turbulent drop coalescence exerts a dominant influence on rain initiation in warm cumulus clouds, with limited impacts of giant CCN.

Aerosol‐Cloud Interactions Near Cloud Base Deteriorating the Haze Pollution in East China

AbstractAtmospheric aerosols not only cause severe haze pollution, but also affect climate through changes in cloud properties. However, during the haze pollution, aerosol‐cloud interactions are not well understood due to a lack of in situ observations. In this study, we conducted simultaneous observations of cloud droplet and particle number size distribution, together with supporting atmospheric parameters, from ground to cloud base in East China using a high‐payload tethered airship. We found that high concentrations of aerosols and cloud condensation nuclei were constrained below cloud, leading to the pronounced “Twomey effect” near the cloud base. The cloud inhibited the pollutants dispersion by reducing surface heat flux and thus deteriorated the near‐surface haze pollution. Satellite retrievals matched well with the in situ observations for low stratus clouds, while were insufficient to quantify aerosol‐cloud interactions for other cases. Our results highlight the importance to combine in situ vertical and satellite observations to quantify the aerosol‐cloud interactions.

Life Cycle Evolution of Mixing in Shallow Cumulus Clouds

AbstractUnderstanding how entrainment and mixing shape the cloud droplet size distribution (DSD) is crucial for understanding the optical properties and precipitation efficiency of clouds. Different mixing scenarios, mainly homogeneous and inhomogeneous, shape the DSD in a distinct way and alter the cloud's impact on climate. However, the prevalence of these mixing scenarios and how they vary in space and time is still uncertain, as underlying processes are commonly unresolved by conventional numerical models. To overcome this challenge, we employ the L3 model, which considers supersaturation fluctuations and turbulent mixing down to the finest relevant lengthscales, making it possible to represent different mixing scenarios realistically. We investigate the spatial and temporal evolution of mixing scenarios over the life cycle of shallow cumulus clouds for varying boundary layer humidities and aerosol concentrations. Our findings suggest homogeneous mixing is generally predominant in cumulus clouds, while different mixing scenarios occur concurrently in the same cloud. Notably, inhomogeneous mixing increases over the cloud life cycle across all analyzed cases. The mean and standard deviation of supersaturation are found to be the most capable indicators of this evolution, providing a comprehensive insight into the characteristics of mixing scenarios. Finally, we show inhomogeneous mixing is more prevalent in drier boundary layers and for higher aerosol concentrations, underscoring the need for a more comprehensive investigation of how these mixing dynamics evolve in a changing climate.

Ground-based cloud microphysical observations at Mount Lu in the East Asian monsoon region from 2015 to 2020

Ground-based cloud microphysical observations were continuously conducted at Mount (Mt.) Lu site from 2015 to 2020, which is located in the East Asian monsoon areas of eastern China. The statistical characteristics of cloud microphysics under different meteorological conditions were analyzed by using visibility, cloud droplet and raindrop size distribution data, and meteorological variables. The mean cloud droplet number concentration (Nc), liquid water content (LWC) and effective diameter (De) are 151 cm−3, 0.08 g m−3 and 11.4 μm, respectively. Nc and LWC observed at Mount Lu are lower than the observation results of cloud from other mountain stations all over the world. Broader cloud droplet spectra are correlated with higher temperatures and lower wind speeds. The clouds are classified into nonprecipitating, lightly-raining and raining clouds. Statistics show that lightly-raining and raining clouds account for 66% of all clouds. Nc and LWC of lightly-raining (drizzling) clouds are highest, while spectral width of raining clouds is largest. Spectral dispersion of raining clouds converges to the narrow range of 0.4–0.7. Notably, medium sized cloud droplets (11–40 μm) promote the formation of large cloud droplets (40–50 μm, pre-drizzle size) and drizzle drops which initiate the auto-conversion from condensation to collision-coalescence growth. This study relying on in-situ continuous cloud observation from mountain station are helpful to understand cloud microphysical structures in East Asian monsoon region, and fitting parameters also provide observational evidence for numerical models.

Locally narrow droplet size distributions are ubiquitous in stratocumulus clouds.

Marine stratocumulus clouds are the "global reflectors," sharply contrasting with the underlying dark ocean surface and exerting a net cooling on Earth's climate. The magnitude of this cooling remains uncertain in part owing to the averaged representation of microphysical processes, such as the droplet-to-drizzle transition in global climate models (GCMs). Current GCMs parameterize cloud droplet size distributions as broad, cloud-averaged gammas. Using digital holographic measurements of discrete stratocumulus cloud volumes, we found cloud droplet size distributions to be narrower at the centimeter scale, never resembling the cloud average. These local distributions tended to form pockets of similar-looking cloud regions, each characterized by a size distribution shape that is diluted to varying degrees. These observations open the way for new modeling representations of microphysical processes.

Cloud microphysical response to entrainment and mixing is locally inhomogeneous and globally homogeneous: Evidence from the lab

Entrainment of dry air into clouds strongly influences cloud optical and precipitation properties and the response of clouds to aerosol perturbations. The response of cloud droplet size distributions to entrainment-mixing is examined in the Pi convection-cloud chamber that creates a turbulent, steady-state cloud. The experiments are conducted by injecting dry air with temperature (Te) and flow rate (Qe) through a flange in the top boundary, into the otherwise well-mixed cloud, to mimic the entrainment-mixing process. Due to the large-scale circulation, the downwind region is directly affected by entrained dry air, whereas the upwind region is representative of the background conditions. Droplet concentration (Cn) and liquid water content (L) decrease in the downwind region, but the difference in the mean diameter of droplets (Dm) is small. The shape of cloud droplet size distributions relative to the injection point is unchanged, to within statistical uncertainty, resulting in a signature of inhomogeneous mixing, as expected for droplet evaporation times small compared to mixing time scales. As Te and Qe of entrained air increase, however, Cn, L, and Dm of the whole cloud system decrease, resulting in a signature of homogeneous mixing. The apparent contradiction is understood as the cloud microphysical responses to entrainment and mixing differing on local and global scales: locally inhomogeneous and globally homogeneous. This implies that global versus local sampling of clouds can lead to seemingly contradictory results for mixing, which informs the long-standing debate about the microphysical response to entrainment and the parameterization of this process for coarse-resolution models.

Paths From Aerosol Particles to Activation and Cloud Droplets in Shallow Cumulus Clouds: The Roles of Entrainment and Supersaturation Fluctuations

AbstractThe activation of aerosol particles and its contribution to cloud droplet size distributions in shallow cumulus clouds are investigated by analyzing the cloud field simulation results using a Lagrangian cloud model coupled with large eddy simulation, which allows explicit simulations of the activation and tracking of each super‐droplet. Analysis is focused on the differences in activations for aerosol particles following central updraft from a cloud base (CB) and particles entrained above the cloud base (EA). Time series of various variables following individual particles confirm the distinctive nature of CB and EA activation. Strong supersaturation fluctuations induced by entrainment and turbulent mixing at cloud edges cause most EA particles to be deactivated soon after activation, substantially limiting their lifetime and growth relative to CB particles. Most net activation—the difference between activation and deactivation—occurs at the cloud base and vanishes aloft. Cloud droplet activation spectra follow the theoretical prediction at high supersaturation conditions, although the proportional constant is smaller because of particle deactivation. The spectra deviate from the theoretical prediction at low supersaturation conditions since they are affected by the transport of the CB particles activated elsewhere.

Influence of natural and anthropogenic aerosols on cloud base droplet size distributions in clouds over the South China Sea and West Pacific

Abstract. Cumulus clouds are common over maritime regions. They are important regulators of the global radiative energy budget and global hydrologic cycle, as well as a key contributor to the uncertainty in anthropogenic climate change projections due to uncertainty in aerosol–cloud interactions. These interactions are regionally specific owing to their strong influences on aerosol sources and meteorology. Here, our analysis focuses on the statistical properties of marine boundary layer (MBL) aerosol chemistry and the relationships of MBL aerosol to cumulus cloud properties just above cloud base as sampled in 2019 during the NASA Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). The aerosol and clouds were sampled by instruments on the NASA P-3 aircraft over three distinct maritime regions around the Philippines: the West Pacific, the South China Sea, and the Sulu Sea. Our analysis shows three primary sources influenced the aerosol chemical composition: clean marine (ocean source), industrial (Southeast Asia, Manila, and cargo and tanker ship emissions), and biomass burning (Borneo and Indonesia). The clean marine aerosol chemical composition had low values of all sampled chemical signatures, specifically median values of 2.2 µg m−3 of organics (ORG), 2.3 µg m−3 of SO4, 0.3 µg m−3 of NO3, 1.4 µg m−3 of NH4, 0.04 µg m−3 of Cl, and 0.0074 µg m−3 of refractory black carbon (BC). Chemical signatures of the other two aerosol source regions were industrial, with elevated SO4 having a median value of 6.1 µg m−3, and biomass burning, with elevated median concentrations of ORG 21.2 µg m−3 and BC 0.1351 µg m−3. Based on chemical signatures, the industrial component was primarily from ship emissions, which were sampled within 60 km of ships and within projected ship plumes. Normalized cloud droplet size distributions in clouds sampled near the MBL passes of the P-3 showed that clouds impacted by industrial and biomass burning contained higher concentrations of cloud droplets, by as much as 1.5 orders of magnitude for diameters &lt; 13 µm compared to clean marine clouds, while at size ranges between 13.0–34.5 µm the median concentrations of cloud droplets in all aerosol categories were nearly an order of magnitude less than the clean marine category. In the droplet size bins centered at diameters &gt; 34.5 µm concentrations were equal to, or slightly exceeded, the concentrations of the clean marine clouds. These analyses show that anthropogenic aerosols generated from industrial and biomass burning sources significantly influenced cloud base microphysical structure in the Philippine region enhancing the small droplet concentration and reducing the concentration of mid-sized droplets.

Use of multiplatform in-situ observation to study vertical structure and microphysics of clouds during southwest monsoon over Western Ghats, India

Combination of radiosonde profiles with collocated in-situ ground and aircraft measurements is used for the first time to study the vertical structure and microphysics of clouds during southwest monsoon over the Western Ghats, India. The morphology of clouds is detailed with the help of radiosonde observations and classified as low, mid, and high-level clouds depending on the cloud base height. Radiosonde sounding profiles indicated occurrences of both single and multi-layered clouds with higher occurrences of single-layered (∼35%) clouds during monsoon transition period (June and September) and two-layered (∼42%) during core monsoon period (July and August). Dominance of low (∼30%) and high-level (∼60%) clouds were noticed compared to mid-level clouds over the observational site during the southwest monsoon.Warm cloud microphysics was investigated using collocated ground and airborne in situ measurements. Irrespective of the cloud type, the cloud liquid water content and the effective droplet diameter increased with altitude. One of the key results is the rapid broadening of the cloud droplet size distribution with height. The number concentration of droplets above 25 μm diameters showed a steep decrease at altitudes above 1800 m, suggesting active collision-coalescence.

Comparison of Cloud Properties between SGLI Aboard GCOM-C Satellite and MODIS Aboard Terra Satellite

This study presents a comprehensive comparison of Level 2.0 cloud properties between a Second-generation Global Imager (SGLI) aboard the GCOM-C satellite and a Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, to better understand the qualities of cloud properties obtained from SGLI/GCOM-C launched on 23 December 2017. The cloud pixels identified as water phase by both satellite sensors are highly consistent to each other by more than 90%, although the consistency is only ~60% for ice phase cloud pixels. A comparison of cloud properties—cloud optical thickness (COT) and cloud particle effective radius (CER)—between these two satellite sensors reveals that water and ice cloud properties can have different degrees of agreement depending on underlying surface. The relative difference (RD) values of 22% (18%) and 37% (24%) for water cloud COT (CER) comparison over ocean and land surfaces and respective values of 35% (42%) and 35% (62%) for comparisons of ice cloud properties, and also other comparison metrics, suggest better agreements for water cloud properties than for ice cloud properties, and for ocean surface than for land surface. Though cloud properties differences between MODIS and SGLI can arise from inherent features of cloud retrieval algorithms, such as differences in ancillary data, surface reflectance, cloud droplet size distribution function, model for ice particle habit, etc., this study further identifies the important roles of cloud thickness and Sun and satellite positions for differences in cloud properties between SGLI and MODIS: the differences in cloud properties are found to increase for thinner clouds, higher solar zenith angle, and higher differences in viewing zenith and azimuth angles between these satellite sensors, and such differences are more distinct for water cloud properties than for ice cloud properties.

High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow

Abstract. The cloud droplet size distribution is often described by a gamma distribution defined by the effective radius and the effective variance. The effective radius is directly related to the cloud's optical thickness, which influences the radiative properties of a cloud. The effective variance affects, among other things, the evolution of precipitation. Both parameters can be retrieved from measurements of the cloudbow. The cloudbow (or rainbow) is an optical phenomenon that forms due to the single scattering of radiation by liquid cloud droplets at the cloud edge. The polarized radiance of the cloudbow crucially depends on the cloud droplet size distribution. The effective radius and the effective variance can be retrieved by fitting model simulations (stored in a lookup table) to polarized cloudbow observations. This study uses measurements from the wide-field polarization-sensitive camera of the spectrometer of the Munich Aerosol Cloud Scanner (specMACS) aboard the German “High Altitude and LOng range research aircraft” (HALO). Along with precise cloud geometry data derived by a stereographic method, a geolocalization of the observed clouds is possible. Observations of the same cloud from consecutive images are combined into one radiance measurement from multiple angles. Two case studies of trade-wind cumulus clouds measured during the EUREC4A (ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte) field campaign are presented, and the cloudbow technique is demonstrated. The results are combined into maps of the effective radius and the effective variance with a 100 m × 100 m spatial resolution and large coverage (across-track swath width of 8 km). The first case study shows a stratiform cloud deck with distinct patches of large effective radii up to 40 µm and a median effective variance of 0.11. specMACS measures at a very high angular resolution (binned to 0.3∘) which is necessary when large droplets are present. The second case study consists of small cumulus clouds (diameters of approximately 2 km). The retrieved effective radius is 7.0 µm, and the effective variance is 0.08 (both median values). This study demonstrates that specMACS is able to determine the droplet size distribution of liquid water clouds even for small cumulus clouds, which are a problem for traditional droplet size retrievals based on total reflectances.

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

AbstractThe convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H1/3, consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H2/3. Temperature and other scalar fluctuations scale as H−3/7. Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

Impact of the Microphysics in HARMONIE-AROME on Fog

This study concerns the impact of microphysics on the HARMONIE-AROME NWP model. In particular, the representation of cloud droplets in the single-moment bulk microphysics scheme is examined in relation to fog forecasting. We focus on the shape parameters of the cloud droplet size distribution and recent changes to the representation of the cloud droplet number concentration (CDNC). Two configurations of CDNC are considered: a profile that varies with height and a constant one. These aspects are examined together since few studies have considered their combined impact during fog situations. We present a set of six experiments performed for two non-idealised three-dimensional case studies over the Iberian Peninsula and the North Sea. One case displays both low clouds and fog, and the other shows a persistent fog field above sea. The experiments highlight the importance of the considered parameters that affect droplet sedimentation, which plays a key role in modelled fog. We show that none of the considered configurations can simultaneously represent all aspects of both cases. Hence, continued efforts are needed to introduce relationships between the governing parameters and the relevant atmospheric conditions.