Cloud Microphysical Properties Research Articles

The preliminary measurements of water cloud microphysical properties using multiple scattering Raman lidar

Clouds play an important role in the energy balance and water cycle for the Earth-Atmosphere system, and the accurate measurement of their macro-and microphysical properties is important for understanding atmospheric physical processes, studying aerosol-cloud interactions and improving numerical model parameterization schemes. In this paper, a multiple scattering Raman lidar system is developed, which greatly simplifies the structure of the optical system and solves the complexity of the optical system in detecting the cloud characteristic parameters by adopting the dual field-of-view (FOV) technique. Based on the Quasi-Small-Angle (QSA) approximation model, the forward single or multiple scattering signals of cloud droplet particles at the bottom of the cloud layer at the dual-FOV channel and the vibrational Raman backscattering signals of nitrogen molecules are simultaneously detected. Using the correlation between the width of the forward scattering peak and the particle size of the cloud droplets, an iterative algorithm for the Raman signal is proposed for retrieving cloud parameters such as the extinction coefficient, the effective radius, and the liquid water content (LWC). To verify the feasibility of the system and retrieval algorithms, some preliminary measurements were carried out and the resulting liquid water content was compared and verified by combined observations with a co-located microwave radiometer. The experimental results show that the average deviation of the liquid water content is 0.004 g/m3, and the relative error is 20%. The system has an ability to invert cloud microphysical properties, which provides an effective method for further study of aerosol-cloud interactions.

Clothing Textiles as Carriers of Biological Ice Nucleation Active Particles.

Microplastics have littered the globe, with synthetic fibers being the largest source of atmospheric microplastics. Many atmospheric particles can act as ice nucleators, thereby affecting the microphysical and radiative properties of clouds and, hence, the radiative balance of the Earth. The present study focused on the ice-nucleating ability of fibers from clothing textiles (CTs), which are commonly shed from the normal wear of apparel items. Results from immersion ice nucleation experiments showed that CTs were effective ice nucleators active from -6 to -12 °C, similar to common biological ice nucleators. However, subsequent lysozyme and hydrogen peroxide digestion stripped the ice nucleation properties of CTs, indicating that ice nucleation was biological in origin. Microscopy confirmed the presence of biofilms (i.e., microbial cells attached to a surface and enclosed in an extracellular polysaccharide matrix) on CTs. If present in sufficient quantities in the atmosphere, biological particles (biofilms) attached to fibrous materials could contribute significantly to atmospheric ice nucleation.

Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC

Abstract. Atmospheric aerosols can act as ice-nucleating particles (INPs) and influence the formation and the microphysical properties of cirrus clouds, resulting in distinct climate effects. We employ a global aerosol–climate model, including a two-moment cloud microphysical scheme and a parameterization for aerosol-induced ice formation in cirrus clouds, to quantify the climate impact of INPs on cirrus clouds (simulated period 2001–2010). The model considers mineral dust, soot, crystalline ammonium sulfate, and glassy organics as INPs in the cirrus regime. Several sensitivity experiments are performed to analyse various aspects of the simulated INP–cirrus effect regarding (i) the ice-nucleating potential of the INPs, (ii) the inclusion of ammonium sulfate and organic particles as INPs in the model, and (iii) the model representations of vertical updraughts. The resulting global radiative forcing of the total INP–cirrus effect, considering all different INP types, assuming a smaller and a larger ice-nucleating potential of INPs, to explore the range of possible forcings due to uncertainties in the freezing properties of INPs, is simulated as −28 and −55 mW m−2, respectively. While the simulated impact of glassy organic INPs is mostly small and not statistically significant, ammonium sulfate INPs contribute a considerable radiative forcing, which is nearly as large as the combined effect of mineral dust and soot INPs. Additionally, the anthropogenic INP–cirrus effect is analysed considering the difference between present-day (2014) and pre-industrial conditions (1750) and amounts to −29 mW m−2, assuming a larger ice-nucleating potential of INPs. In a further sensitivity experiment we analyse the effect of highly efficient INPs proposed for cirrus cloud seeding as a means to reduce global warming by climate engineering. However, the results indicate that this approach risks an overseeding of cirrus clouds and often results in positive radiative forcings of up to 86 mW m−2 depending on number concentration of seeded INPs. Idealized experiments with prescribed vertical velocities highlight the crucial role of the model dynamics for the simulated INP–cirrus effects. For example, resulting forcings increase about 1 order of magnitude (−42 to −340 mW m−2) when increasing the prescribed vertical velocity (from 1 to 50 cm s−1). The large discrepancy in the magnitude of the simulated INP–cirrus effect between different model studies emphasizes the need for future detailed analyses and efforts to reduce this uncertainty and constrain the resulting climate impact of INPs.

Rainfall Area Identification Algorithm Based on Himawari-8 Satellite Data and Analysis of its Spatiotemporal Characteristics

Real-time monitoring of rainfall areas based on satellite remote sensing is of vital importance for extreme rainfall research and disaster prediction. In this study, a new rainfall area identification algorithm was developed for the new generation of geostationary satellites with high spatial and temporal resolution and rich bands. As the main drivers of the rainfall process, the macro and micro physical properties of clouds play an important role in the formation and development of rainfall. We considered differences in the absorption capacity of the water vapor absorption channels in the infrared band and introduced a sensitivity difference of rainfall area in water vapor channels to construct a sensitive detection of the water vapor region. The results of this algorithm were evaluated using Global Precipitation Measurement (GPM) satellite products and CloudSat measurements in various scenarios, with hit rates of 70.03% and 81.39% and false alarm rates of 2.05% and 21.34%, respectively. Spatiotemporal analysis revealed that the types of upper clouds in the rainfall areas mainly consisted of deep convection, cirrostratus, and nimbostratus clouds. Our study provides supporting data for weather research and disaster prediction, as well as an efficient and reliable method for capturing temporal and spatial features.

Tethered balloon-borne observations of thermal-infrared irradiance and cooling rate profiles in the Arctic atmospheric boundary layer

Abstract. Clouds play an important role in controlling the radiative energy budget of the Arctic atmospheric boundary layer. To quantify the impact of clouds on the radiative heating or cooling of the lower atmosphere and of the surface, vertical profile observations of thermal-infrared irradiances were collected using a radiation measurement system carried by a tethered balloon. We present 70 profiles of thermal-infrared radiative quantities measured in summer 2020 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and in autumn 2021 and spring 2022 in Ny-Ålesund, Svalbard. Measurements are classified into four groups: cloudless, low-level liquid-bearing cloud, elevated liquid-bearing cloud, and elevated ice cloud. Cloudless cases display an average radiative cooling rate of about −2 K d−1 throughout the atmospheric boundary layer. Instead, low-level liquid-bearing clouds are characterized by a radiative cooling up to −80 K d−1 within a shallow layer at cloud top, while no temperature tendencies are identified underneath the cloud layer. Radiative transfer simulations are performed to quantify the sensitivity of radiative cooling rates to cloud microphysical properties. In particular, cloud top cooling is strongly driven by the liquid water path, especially in optically thin clouds, while for optically thick clouds the cloud droplet number concentration has an increased influence. Additional radiative transfer simulations are used to demonstrate the enhanced radiative importance of the liquid relative to ice clouds. To analyze the temporal evolution of thermal-infrared radiation profiles during the transitions from a cloudy to a cloudless atmosphere, a respective case study is investigated.

A Method for Retrieving Cloud Microphysical Properties Using Combined Measurement of Millimeter-Wave Radar and Lidar

Clouds are an important component of weather systems and are difficult to effectively characterize using current climate models and estimation of radiative forcing. Due to the limitations in observational capabilities, it remains difficult to obtain high-spatiotemporal-resolution, continuous, and accurate observations of clouds. To overcome this issue, we propose a novel and practical combined retrieval method using millimeter-wave radar and lidar, which enables the microphysical properties of thin liquid water clouds, such as cloud droplet effective radius, number concentration, and liquid water content, to be retrieved. This method was utilized to analyze the clouds observed at the Shanghai World Expo Park and was validated through synchronous observations with a microwave radiometer. Furthermore, the most suitable extinction backscatter ratio was determined through sensitivity analysis. This study provides vertical distributions of cloud microphysical properties with a time resolution of 1 min and a spatial resolution of 30 m, demonstrating the scientific potential of this combined retrieval method.

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at the Daily and Sub-Daily Scales in the Western Mediterranean

In the last decade, substantial improvements have been achieved in quantitative satellite precipitation estimates, which are essential for a wide range of applications. In this study, we evaluated the performance of Integrated Multi-satellitE Retrievals for GPM (IMERG V06B) at the sub-daily and daily scales. Ten years of half-hourly precipitation records aggregated at different sub-daily periods were evaluated over a region in the Western Mediterranean. The analysis at the half-hourly scale examined the contribution of passive microwave (PMW) and infrared (IR) sources in IMERG estimates, as well as the relationship between various microphysical cloud properties using Cloud Microphysics (CMIC–NWC SAF) data. The results show the following: (1) a marked tendency to underestimate precipitation compared to rain gauges which increases with rainfall intensity and temporal resolution, (2) a weaker negative bias for retrievals with PMW data, (3) an increased bias when filling PMW gaps by including IR information, and (4) an improved performance in the presence of precipitating ice clouds compared to warm and mixed-phase clouds. This work contributes to the understanding of the factors affecting satellite estimates of extreme precipitation. Their relationship with the microphysical characteristics of clouds generates added value for further downstream applications and users’ decision making.

Wind-driven emissions of coarse-mode particles in an urban environment

Abstract. Quantifying surface–atmosphere exchange rates of particles is important for understanding the role of suspended particulate matter in radiative transfer, clouds, precipitation, and climate change. Emissions of coarse-mode particles with a diameter greater than 0.5 µm provide giant cloud condensation nuclei and ice nuclei. These emissions are critical for understanding the evolution of cloud microphysical properties yet remain poorly understood. Here we introduce a new method that uses lidar retrievals of the elastic backscatter and Doppler velocity to obtain surface number emissions of particles with a diameter greater than 0.53 µm. The technique is applied to study particle number fluxes over a 2-month period from 1 June to 10 August 2022 during the TRACER campaign at an urban site near Houston, TX, USA. We found that all the observed fluxes were positive (upwards), indicating particle emission from the surface. The fluxes followed a diurnal pattern and peaked near noon local time. Flux intensity varied through the 2 months with multi-day periods of strong fluxes and multi-day periods of weak fluxes. Emission particle number fluxes peaked near ∼ 100 cm−2 s−1. The daily averaged emission fluxes correlated with friction velocity and were anticorrelated with surface relative humidity. The emission flux can be parameterized as F= 3000 u*4, where u* is the friction velocity in m s−1 and the emission flux F is in cm−2 s−1. The u* dependence is consistent with emission from wind-driven erosion. Estimated values for the mass flux are in the lower range of literature values from non-urban sites. These results demonstrate that urban environments may play an important role in supplying coarse-mode particles to the boundary layer. We anticipate that quantification of these emissions will help constrain aerosol–cloud interaction models that use prognostic aerosol schemes.

Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties

Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.

Responses of Simulated Arctic Mixed-Phase Clouds to Parameterized Ice Particle Shape

Abstract In simulations of Arctic mixed-phase clouds, cloud persistence and the liquid water path (LWP) are sensitive to ice particle number concentrations. Here, we explore sensitivities of cloud microphysical properties to the dominant ice particle shape (dendrites, plates, columns, or spheres) using the SCALE-AMPS large-eddy simulation model. AMPS is a bin microphysics scheme that predicts particle shapes based on the inherent growth ratio (IGR) of spheroids, which determines vapor depositional growth rates along the a and c axes, and the rimed and aggregate mass fractions. We examine the impacts of various IGR values on simulations of clouds observed during the M-PACE and SHEBA experiments. Under M-PACE (SHEBA) conditions, LWP varies between 49 (1.1) and 230 (6.7) g m−2, and the ice water path (IWP) varies between 3 (0.03) and 40 (0.12) g m−2, depending on the ice shape. The lowest LWP and the highest IWP are obtained when columnar particles dominate because their low terminal velocities and large capacitance and collisional area result in large vapor deposition and riming rates, whereas the highest LWP and lowest IWP are obtained when spherical particles dominate because their vapor deposition and riming rates are low. Because ice particle shape significantly influences simulated Arctic mixed-phase clouds, reliable simulations require accurately estimated IGR values under various atmospheric conditions. Finally, comparisons between the simulation results and observations show that the size distribution larger than 2000 μm is better reproduced when the increase in rimed mass that causes ice particles to become spherical is suppressed. Significance Statement Atmospheric models have difficulties in reproducing Arctic mixed-phase clouds because of uncertainties in the parameterization of microphysical processes. This is the first study to use a large-eddy simulation model implemented with a habit-predicting bin microphysics scheme to demonstrate the important role of ice particle shape on the microphysical properties of both heavy-riming and no-riming mixed-phase clouds. We found the vapor deposition and riming rates to be greatly influenced by ice particle shape. By comparing the ice particle size distribution, mass–diameter relationship, and area ratio between simulation results and observations, we show that a hexagonal ice shape model and a riming model that simply converts ice crystals to graupel may not accurately reproduce actual heavy-riming clouds.

Simultaneous Retrieval Algorithm of Water Cloud Optical and Microphysical Properties by High-Spectral-Resolution Lidar

Simultaneous Retrieval Algorithm of Water Cloud Optical and Microphysical Properties by High-Spectral-Resolution Lidar

New airborne research facility observes sensitivity of cumulus cloud microphysical properties to aerosol regime over the great barrier reef

The new research aircraft, Cessna 337, is equipped with a meteorological, aerosol, and cloud microphysical instrumentation. A case study from its first campaign is presented showing the sensitivity of cumulus cloud microphysical properties to the aerosol regime over the Great Barrier Reef.

Aerosol effects on liquid cloud microphysical properties in south China: Land–ocean contrasts

The aerosol effects on liquid cloud microphysical properties over South China and adjacent ocean regions are investigated by using aerosol reanalysis data from MERRA-2, cloud property data from CLARA-A2, and reanalysis data from ERA5 from 1995 to 2015. The aerosol optical depth (AOD) in South China and adjacent ocean regions shows an upward trend with obvious land–ocean contrasts. The AOD is significantly positively correlated with the liquid cloud droplet effective radius (LREF) over both land and the ocean in summer and autumn, while increasing AOD significantly suppresses the LREF in spring and winter over land. This indicates that the thermal supply is likely the reason for the differences in aerosol effects on liquid cloud properties in different seasons. The weak correlation between the AOD and LREF over the ocean in spring may be because the South China Sea monsoon onset increases the atmospheric instability, and springtime in southeastern China is characterized by high rainfall. This indicates that the effects of aerosols on clouds are not as significant as those on large-scale systems. Further analysis shows that the aerosol effects on the liquid cloud properties are strong and positive at low liquid water paths (LWP) in summer and autumn, while the effect is weak at high LWPs. This may be due to the presence of sufficient liquid water droplets with large LWPs in summer and autumn, and few liquid water droplets in spring and winter. The aerosol effects on liquid cloud properties also significantly depend on lower-tropospheric stability (LTS).

Secondary droplet activation during condensational growth in convective clouds and its detection from satellites

By acting as cloud condensation nuclei (CCN), aerosol particles play a key role in the climate system. The CCN can be activated into cloud droplets at the cloud base (i.e., primary activation), or above it (i.e., secondary activation). This study shows the conditions required for secondary activation during the condensational growth phase in convective clouds. It also proposes a methodology for detecting this secondary activation from satellites. Using a spectral bin adiabatic parcel model, we simulate the vertical profile of cloud microphysical properties and demonstrate how different aerosol size distributions and updraft velocities greatly affect the secondary activation initiation and the cloud properties. The secondary activation slows down the cloud drop effective radius (re) growth rate with increasing height, and decreasing temperature (T), due to the relatively larger population of smaller droplets in the cloud parcel. Therefore, the vertical profile of re growth with height is slower than the adiabatic rate when the secondary activation occurs.The proposed physical principle was verified by satellite-retrieved T-re profiles and adiabatic cloud drop number concentrations (Nd) over the Amazon region. The results obtained from this study can be utilized to identify the secondary droplet activation during the condensational growth phase, which can lead to an overestimation of the retrieved Nd as well as suppression of warm rain. This improves our knowledge and observational capabilities of the role of aerosol particles in the microphysics, dynamics, and precipitation behavior of convective clouds. Plain text summarySmall particles serve as sites for cloud droplets' condensation at the cloud base (primary droplet activation) or above it (secondary activation). Once a droplet is activated at the cloud base, the surrounding water vapor condenses on it and the droplet grows - this is called condensational growth. The cloud droplet number concentrations (Nd) can be obtained by the satellite-retrieved vertical growth rate of droplet size in the condensational growth phase. However, new small droplets formed during this phase (i.e., secondary activation), might cause an overestimate in the retrieved Nd. This study presents the physical principle of secondary activation during condensational growth. Using a model, we simulate the condensational growth of aerosol particles, which act as cloud condensation nuclei (CCN), for different particle size distributions and thermodynamic conditions (i.e., vertical velocities). Our simulations show that secondary activation slows the cloud droplet growth rate with height due to the larger competition for the available water vapor promoted by the new drops. Comparisons between satellite-retrieved Nd of convective clouds and in-situ measurements show that the satellite retrievals overestimate Nd when the secondary activation of droplets is neglected. Our findings improve the understanding of aerosols' role in the condensational growth of droplets in convective clouds.

High-altitude demonstration of LWIR polarimetry using uncooled microbolometers

An Infrared Channeled Spectro-Polarimeter (IRCSP) was successfully demonstrated in a near-space environment on a high-altitude balloon mission out of the NASA Columbia Scientific Balloon Facility in August 2021. The compact IRCSP is sensitive to linearly polarized thermal radiation between 7-12μm and targets polarized cloud top scattering. The IRCSP comprises a series of polarization modulation components followed by a diffraction grating and lens that images a polarization modulated spectrum at the focal plane. At altitudes greater than 30 km, the IRCSP reported brightness temperatures (Tb) between 250–285 K with an uncertainty of less than 1.5K. These IRCSP Tb values overlapped the collated GOES-16 cloud top temperatures within the pointing uncertainty of the instrument. IRCSP’s inaugural high-altitude deployment demonstrated the operation of uncooled microbolometers in the low-pressure environment and resulted in the first known observations of downward-viewing thermal polarized radiation from Earth’s atmosphere. Using the Lomb–Scargle periodogram with a maximum acceptable false alarm probability of 1%, the IRCSP detected statistically significant polarized signals with average degrees of linear polarization (DoLP) ranging from 1% to 20%. The top-of-atmosphere simulations that motivated IRCSP’s development predict that LWIR polarization is highest for ice clouds of moderate optical thickness. IRCSP observed cloud-top DoLP trends with brightness temperature that are consistent with these simulations. The highest and lowest Tb values occur for no clouds and optically thick clouds, respectively. The lowest DoLP measurements by IRCSP were at these extreme conditions. The DoLP peaked at intermediate Tb values. This preliminary work motivates IRCSP’s participation in future deployments that provide independent data products of cloud microphysical properties.

Variability and properties of liquid-dominated clouds over the ice-free and sea-ice-covered Arctic Ocean

Abstract. Due to their potential to either warm or cool the surface, liquid-phase clouds and their interaction with the ice-free and sea-ice-covered ocean largely determine the energy budget and surface temperature in the Arctic. Here, we use airborne measurements of solar spectral cloud reflectivity obtained during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign in summer 2017 and the Arctic Amplification: FLUXes in the Cloudy Atmospheric Boundary Layer (AFLUX) campaign in spring 2019 in the vicinity of Svalbard to retrieve microphysical properties of liquid-phase clouds. The retrieval was tailored to provide consistent results over sea-ice and open-ocean surfaces. Clouds including ice crystals that significantly bias the retrieval results were filtered from the analysis. A comparison with in situ measurements shows good agreement with the retrieved effective radii and an overestimation of the liquid water path and reduced agreement for boundary-layer clouds with varying fractions of ice water content. Considering these limitations, retrieved microphysical properties of clouds observed over the ice-free ocean and sea ice in spring and early summer in the Arctic are compared. In early summer, the liquid-phase clouds have a larger median effective radius (9.5 µm), optical thickness (11.8) and effective liquid water path (72.3 g m−2) compared to spring conditions (8.7 µm, 8.3 and 51.8 g m−2, respectively). The results show larger cloud droplets over the ice-free Arctic Ocean compared to sea ice in spring and early summer caused mainly by the temperature differences in the surfaces and related convection processes. Due to their larger droplet sizes, the liquid clouds over the ice-free ocean have slightly reduced optical thicknesses and lower liquid water contents compared to the sea-ice surface conditions. The comprehensive dataset on microphysical properties of Arctic liquid-phase clouds is publicly available and could, e.g., help to constrain models or be used to investigate effects of liquid-phase clouds on the radiation budget.

Asymmetries in cloud microphysical properties ascribed to sea ice leads via water vapour transport in the central Arctic

Abstract. To investigate the influence of sea ice openings like leads on wintertime Arctic clouds, the air mass transport is exploited as a heat and humidity feeding mechanism which can modify Arctic cloud properties. Cloud microphysical properties in the central Arctic are analysed as a function of sea ice conditions during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019–2020. The Cloudnet classification algorithm is used to characterize the clouds based on remote sensing observations and the atmospheric thermodynamic state from the observatory on board the research vessel (RV) Polarstern. To link the sea ice conditions around the observational site with the cloud observations, the water vapour transport (WVT) being conveyed towards RV Polarstern has been utilized as a mechanism to associate upwind sea ice conditions with the measured cloud properties. This novel methodology is used to classify the observed clouds as coupled or decoupled to the WVT based on the location of the maximum vertical gradient of WVT height relative to the cloud-driven mixing layer. Only a conical sub-sector of sea ice concentration (SIC) and the lead fraction (LF) centred on the RV Polarstern location and extending up to 50 km in radius and with an azimuth angle governed by the time-dependent wind direction measured at the maximum WVT is related to the observed clouds. We found significant asymmetries for cases when the clouds are coupled or decoupled to the WVT and selected by LF regimes. Liquid water path of low-level clouds is found to increase as a function of LF, while the ice water path does so only for deep precipitating systems. Clouds coupled to WVT are found to generally have a lower cloud base and larger thickness than decoupled clouds. Thermodynamically, for coupled cases the cloud-top temperature is warmer and accompanied by a temperature inversion at the cloud top, whereas the decoupled cases are found to be closely compliant with the moist adiabatic temperature lapse rate. The ice water fraction within the cloud layer has been found to present a noticeable asymmetry when comparing coupled versus decoupled cases. This novel approach of coupling sea ice to cloud properties via the WVT mechanism unfolds a new tool to study Arctic surface–atmosphere processes. With this formulation, long-term observations can be analysed to enforce the statistical significance of the asymmetries. Furthermore, our results serve as an opportunity to better understand the dynamic linkage between clouds and sea ice and to evaluate its representation in numerical climate models for the Arctic system.

An open-hardware community ice nucleation cold stage for research and teaching

Aerosol particles with rare specific properties act as nuclei for ice formation. The presence of ice nucleating particles in the atmosphere leads to heterogeneous freezing at warm temperatures and thus these particles play an important role in modulating microphysical properties of clouds. This work presents an ice nucleation cold stage instrument for measuring the concentration of ice nucleating particles in liquids. The cost is ∼ $10 k including an external chiller. Using a lower cost heat sink reduces the cost to ∼ $6 k. The instrument is suitable for studying ambient ice nucleating particle concentrations and laboratory-based process-level studies of ice nucleation. The design plans allow individuals to self-manufacture the cold-stage using 3D printing, off-the-shelf parts, and a handful of standard tools. Software to operate the instrument and analyze the data is also provided. The design is intended to be simple enough that a graduate student can build it as part of a course or thesis project. Costs are kept to a minimum to facilitate use in classroom demonstrations and laboratory classes.

CCN activation in homogeneous isotropic turbulence: Response to particle characteristics and environmental conditions

Direct Numerical Simulation (DNS) of turbulent cloud parcels are presented where particles evolve in response to the local values in supersaturation (s) led by turbulent fluctuations. A pseudo-spectral DNS is modified to incorporate aerosol particles and Cloud Condensation Nuclei (CCN) activation applying a droplet growth equation based on κ-Köhler theory that works for the whole range of warm cloud particles, from un-activated deliquesced aerosol particles to activated cloud droplets, that grow by condensation. The Lagrangian microphysics applied ensures that each particle experiences a supersaturation (fluctuations added to the mean) corresponding to its near-particle gas phase surroundings, which differs from the uniform parcel view where an average value of supersaturation, s¯, is applied to every particle in the domain. A non-turbulent Lagrangian parcel model with similar mean thermodynamics and CCN properties is compared with turbulent DNS parcels of varying fluctuation intensities to distinguish the impact of turbulence on CCN activation. It is shown that, in a given distribution, a subset of aerosols respond to fluctuations rather than the mean thermodynamics allowing particles of similar dry size to co-exist as un-activated haze particles as well as cloud droplets. The cloud microphysical properties are analysed in a series of DNS experiments with contrasting thermodynamic and aerosol properties. DNS results agrees with the general understanding of aerosol activation and cloud droplets evolution in response to various background conditions such as pristine and polluted aerosol distributions, composition of CCN with respect to organic - inorganic components and magnitude of vertical velocity. DNS considers turbulence-microphysics interactions in such problems providing additional knowledge on the role of turbulence in clouds. It is argued that incorporating turbulent fluctuations in simulating the CCN activation and droplet growth is well reasoned and a constructive way forward.

Aerosol and dynamical contributions to cloud droplet formation in Arctic low-level clouds

Abstract. The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.