Arctic Mixed-phase Clouds Research Articles

Air mass history linked to the development of Arctic mixed-phase clouds

Abstract. Clouds formed during marine cold-air outbreaks (MCAOs) exhibit a distinct transition from stratocumulus decks near the ice edge to broken cumuliform fields further downwind. The mechanisms associated with ice formation are believed to be crucial in driving this transition, yet the factors influencing such formation remain unclear. Through Lagrangian trajectories collocated with satellite data, this study investigates the development of mixed-phase clouds using these outbreaks. Cloud formed in MCAOs are characterized by a swift shift from liquid to ice-containing states, contrasting with non-MCAO clouds also moving off the ice edge. These mixed-phase clouds are predominantly observed at temperatures below −20 °C near the ice edge. However, further into the outbreak, they become dominant at temperatures as high as −13 °C. This shift is consistent with the influence of biological ice-nucleating particles (INPs), which become more prevalent as the air mass ages over the ocean. The evolution of these clouds is closely linked to the history of the air mass, especially the length of time it spends over snow- and ice-covered surfaces – terrains may that be deficient in INPs. This connection also accounts for the observed seasonal variations in the development of Arctic clouds, both within and outside of MCAO events. The findings highlight the importance of understanding both local marine aerosol sources near the ice edge and the overarching INP distribution in the Arctic for modelling of cloud phase in the region.

Surface warming in Svalbard may have led to increases in highly active ice-nucleating particles

The roles of Arctic aerosols as ice-nucleating particles remain poorly understood, even though their effects on cloud microphysics are crucial for assessing the climate sensitivity of Arctic mixed-phase clouds and predicting their response to Arctic warming. Here we present a full-year record of ice-nucleating particle concentrations over Svalbard, where surface warming has been anomalously faster than the Arctic average. While the variation of ice-nucleating particles active at around −30 °C was relatively small, those active at higher temperatures (i.e., highly active ice-nucleating particles) tended to increase exponentially with rising surface air temperatures when the surface air temperatures rose above 0 °C and snow/ice-free barren and vegetated areas appeared in Svalbard. The aerosol population relevant to their increase was largely characterized by dust and biological organic materials that likely originated from local/regional terrestrial sources. Our results suggest that highly active ice-nucleating particles could be actively released from Arctic natural sources in response to surface warming.

Simulations of primary and secondary ice production during an Arctic mixed-phase cloud case from the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) campaign

Abstract. The representation of Arctic clouds and their phase distributions, i.e., the amount of ice and supercooled water, influences predictions of future Arctic warming. Therefore, it is essential that cloud phase is correctly captured by models in order to accurately predict the future Arctic climate. Ice crystal formation in clouds happens through ice nucleation (primary ice production) and ice multiplication (secondary ice production). In common weather and climate models, rime splintering is the only secondary ice production process included. In addition, prescribed number concentrations of cloud condensation nuclei or cloud droplets and ice-nucleating particles are often overestimated in Arctic environments by standard model configurations. This can lead to a misrepresentation of the phase distribution and precipitation formation in Arctic mixed-phase clouds, with important implications for the Arctic surface energy budget. During the Ny-Ålesund Aerosol Cloud Experiment (NASCENT), a holographic probe mounted on a tethered balloon took in situ measurements of number and mass concentrations of ice crystals and cloud droplets in Svalbard, Norway, during fall 2019 and spring 2020. In this study, we choose one case study from this campaign that shows evidence of strong secondary ice production and use the Weather Research and Forecasting (WRF) model to simulate it at a high vertical and spatial resolution. We test the performance of different microphysical parametrizations and apply a new state-of-the-art secondary ice parametrization. We find that agreement with observations highly depends on the prescribed cloud condensation nuclei/cloud droplet and ice-nucleating particle concentrations and requires an enhancement of secondary ice production processes. Lowering mass mixing ratio thresholds for rime splintering inside the Morrison microphysics scheme is crucial to enable secondary ice production and thereby match observations for the right reasons. In our case, rime splintering is required to initiate collisional breakup. The simulated contribution from collisional breakup is larger than that from droplet shattering. Simulating ice production correctly for the right reasons is a prerequisite for reliable simulations of Arctic mixed-phase cloud responses to future temperature or aerosol perturbations.

Arctic mixed-phase clouds simulated by the WRF model: Comparisons with ACLOUD radar and in situ airborne observations and sensitivity of microphysics properties

The microphysical properties of two mixed-phase clouds (MPCs), one over sea ice, and another over open ocean, are investigated using in situ measuring probes and a cloud radar installed on-board two aircraft during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) field campaign, west of Svalbard on 17 June 2017. Comparisons between observations and different configurations of the Weather and Research Forecasting (WRF) model are conducted and reveal discrepancies in the vertical profile of the ice crystal concentrations for both MPCs due to slightly higher temperatures (by approx. 1–2 °C) in WRF than observed, affecting the ice formation. A comprehensive sensitivity analysis is carried out to address the impact of assumptions used for the microphysics (MP) and the atmospheric boundary layer (ABL) schemes on the simulated vertical properties of the MPC systems. The role of the vertical resolution of the large scale data used for model initialisation is also investigated. Results show that the model performance improves for large-scale initialisation with more numerous levels close to the surface. Moreover, modifying the ABL or MP scheme influences the altitudes of the cloud top and base as well as the liquid and ice water amounts. Our study also highlights how an increase in the cloud condensation nuclei and droplet number concentrations can impact the vertical profiles of the liquid and ice water amounts.

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.

Physicochemical characterization and source apportionment of Arctic ice-nucleating particles observed in Ny-Ålesund in autumn 2019

Abstract. Ice-nucleating particles (INPs) initiate primary ice formation in Arctic mixed-phase clouds (MPCs), altering cloud radiative properties and modulating precipitation. For atmospheric INPs, the complexity of their spatiotemporal variations, heterogeneous sources, and evolution via intricate atmospheric interactions challenge the understanding of their impact on microphysical processes in Arctic MPCs and induce an uncertain representation in climate models. In this work, we performed a comprehensive analysis of atmospheric aerosols at the Arctic coastal site in Ny-Ålesund (Svalbard, Norway) from October to November 2019, including their ice nucleation ability, physicochemical properties, and potential sources. Overall, INP concentrations (NINP) during the observation season were approximately up to 3 orders of magnitude lower compared to the global average, with several samples showing degradation of NINP after heat treatment, implying the presence of proteinaceous INPs. Particle fluorescence was substantially associated with INP concentrations at warmer ice nucleation temperatures, indicating that in the far-reaching Arctic, aerosols of biogenic origin throughout the snow- and ice-free season may serve as important INP sources. In addition, case studies revealed the links between elevated NINP and heat lability, fluorescence, high wind speeds originating from the ocean, augmented concentration of coarse-mode particles, and abundant organics. Backward trajectory analysis demonstrated a potential connection between high-latitude dust sources and high INP concentrations, while prolonged air mass history over the ice pack was identified for most scant INP cases. The combination of the above analyses demonstrates that the abundance, physicochemical properties, and potential sources of INPs in the Arctic are highly variable despite its remote location.

Model described in article titled as responses of simulated Arctic mixed-phase clouds to parameterized ice particle shape

Model described in article titled as responses of simulated Arctic mixed-phase clouds to parameterized ice particle shape

Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

Abstract Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.

MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC

Two airborne field campaigns focusing on observations of Arctic mixed-phase clouds and boundary layer processes and their role with respect to Arctic amplification have been carried out in spring 2019 and late summer 2020 over the Fram Strait northwest of Svalbard. The latter campaign was closely connected to the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Comprehensive datasets of the cloudy Arctic atmosphere have been collected by operating remote sensing instruments, in-situ probes, instruments for the measurement of turbulent fluxes of energy and momentum, and dropsondes on board the AWI research aircraft Polar 5. In total, 24 flights with 111 flight hours have been performed over open ocean, the marginal sea ice zone, and sea ice. The datasets follow documented methods and quality assurance and are suited for studies on Arctic mixed-phase clouds and their transformation processes, for studies with a focus on Arctic boundary layer processes, and for satellite validation applications. All datasets are freely available via the world data center PANGAEA.

Conditions favorable for secondary ice production in Arctic mixed-phase clouds

Abstract. The Arctic is very susceptible to climate change and thus is warming much faster than the rest of the world. Clouds influence terrestrial and solar radiative fluxes and thereby impact the amplified Arctic warming. The partitioning of thermodynamic phases (i.e., ice crystals and water droplets) within mixed-phase clouds (MPCs) especially influences their radiative properties. However, the processes responsible for ice crystal formation remain only partially characterized. In particular, so-called secondary ice production (SIP) processes, which create supplementary ice crystals from primary ice crystals and the environmental conditions that they occur in, are poorly understood. The microphysical properties of Arctic MPCs were measured during the Ny-Ålesund AeroSol Cloud ExperimENT (NASCENT) campaign to obtain a better understanding of the atmospheric conditions favorable for the occurrence of SIP processes. To this aim, the in situ cloud microphysical properties retrieved by a holographic cloud imager mounted on a tethered balloon system were complemented by ground-based remote sensing and ice-nucleating particle measurements. During the 6 d investigated in this study, SIP occurred during about 40 % of the in-cloud measurements, and high SIP events with number concentrations larger than 10 L−1 of small pristine ice crystals occurred in 4 % of the in-cloud measurements. This demonstrates the role of SIP for Arctic MPCs. The highest concentrations of small pristine ice crystals were produced at temperatures between −5 and −3 ∘C and were related to the occurrence of supercooled large droplets freezing upon collision with ice crystals. This suggests that a large fraction of ice crystals in Arctic MPCs are produced via the droplet-shattering mechanism. From evaluating the ice crystal images, we could identify ice–ice collision as a second SIP mechanism that dominated when fragile ice crystals were observed. Moreover, SIP occurred over a large temperature range and was observed in up to 80 % of the measurements down to −24 ∘C due to the occurrence of ice–ice collisions. This emphasizes the importance of SIP at temperatures below −8 ∘C, which are currently not accounted for in most numerical weather models. Although ice-nucleating particles may be necessary for the initial freezing of water droplets, the ice crystal number concentration is frequently determined by secondary production mechanisms.

Composition and mixing state of Arctic aerosol and cloud residual particles from long-term single-particle observations at Zeppelin Observatory, Svalbard

Abstract. The Arctic region is sensitive to climate change and is warming faster than the global average. Aerosol particles change cloud properties by acting as cloud condensation nuclei and ice-nucleating particles, thus influencing the Arctic climate system. Therefore, understanding the aerosol particle properties in the Arctic is needed to interpret and simulate their influences on climate. In this study, we collected ambient aerosol particles using whole-air and PM10 inlets and residual particles of cloud droplets and ice crystals from Arctic low-level clouds (typically, all-liquid or mixed-phase clouds) using a counterflow virtual impactor inlet at the Zeppelin Observatory near Ny-Ålesund, Svalbard, within a time frame of 4 years. We measured the composition and mixing state of individual fine-mode particles in 239 samples using transmission electron microscopy. On the basis of their composition, the aerosol and cloud residual particles were classified as mineral dust, sea salt, K-bearing, sulfate, and carbonaceous particles. The number fraction of aerosol particles showed seasonal changes, with sulfate dominating in summer and sea salt increasing in winter. There was no measurable difference in the fractions between ambient aerosol and cloud residual particles collected at ambient temperatures above 0 ∘C. On the other hand, cloud residual samples collected at ambient temperatures below 0 ∘C had several times more sea salt and mineral dust particles and fewer sulfates than ambient aerosol samples, suggesting that sea spray and mineral dust particles may influence the formation of cloud particles in Arctic mixed-phase clouds. We also found that 43 % of mineral dust particles from cloud residual samples were mixed with sea salt, whereas only 18 % of mineral dust particles in ambient aerosol samples were mixed with sea salt. This study highlights the variety in aerosol compositions and mixing states that influence or are influenced by aerosol–cloud interactions in Arctic low-level clouds.

The role of aerosols on the turbulent state of the Arctic mixed-phase clouds

The role of aerosols on the turbulent state of the Arctic mixed-phase clouds

Do Arctic mixed-phase clouds sometimes dissipate due to insufficient aerosol? Evidence from comparisons between observations and idealized simulations

Abstract. Mixed-phase clouds are ubiquitous in the Arctic. These clouds can persist for days and dissipate in a matter of hours. It is sometimes unknown what causes this sudden dissipation, but aerosol–cloud interactions may be involved. Arctic aerosol concentrations can be low enough to affect cloud formation and structure, and it has been hypothesized that, in some instances, concentrations can drop below some critical value needed to maintain a cloud. We use observations from a Department of Energy ARM site on the northern slope of Alaska at Oliktok Point (OLI), the Arctic Summer Cloud Ocean Study (ASCOS) field campaign in the high Arctic Ocean, and the Integrated Characterisation of Energy, Clouds, Atmospheric state, and Precipitation at Summit – Aerosol Cloud Experiment (ICECAPS-ACE) project at the NSF (National Science Foundation) Summit Station in Greenland (SMT) to identify one case per site where Arctic boundary layer clouds dissipated coincidentally with a decrease in surface aerosol concentrations. These cases are used to initialize idealized large eddy simulations (LESs) in which aerosol concentrations are held constant until, at a specified time, all aerosols are removed instantaneously – effectively creating an extreme case of aerosol-limited dissipation which represents the fastest a cloud could possibly dissipate via this process. These LESs are compared against the observed data to determine whether cases could, potentially, be dissipating due to insufficient aerosol. The OLI case's observed liquid water path (LWP) dissipated faster than its simulation, indicating that other processes are likely the primary drivers of the dissipation. The ASCOS and SMT observed LWP dissipated at similar rates to their respective simulations, suggesting that aerosol-limited dissipation may be occurring in these instances. We also find that the microphysical response to this extreme aerosol forcing depends greatly on the specific case being simulated. Cases with drizzling liquid layers are simulated to dissipate by accelerating precipitation when aerosol is removed while the case with a non-drizzling liquid layer dissipates quickly, possibly glaciating via the Wegener–Bergeron–Findeisen (WBF) process. The non-drizzling case is also more sensitive to ice-nucleating particle (INP) concentrations than the drizzling cases. Overall, the simulations suggest that aerosol-limited cloud dissipation in the Arctic is plausible and that there are at least two microphysical pathways by which aerosol-limited dissipation can occur.

Relative importance of high-latitude local and long-range-transported dust for Arctic ice-nucleating particles and impacts on Arctic mixed-phase clouds

Abstract. Dust particles, serving as ice-nucleating particles (INPs), may impact the Arctic surface energy budget and regional climate by modulating the mixed-phase cloud properties and lifetime. In addition to long-range transport from low-latitude deserts, dust particles in the Arctic can originate from local sources. However, the importance of high-latitude dust (HLD) as a source of Arctic INPs (compared to low-latitude dust, LLD) and its effects on Arctic mixed-phase clouds are overlooked. In this study, we evaluate the contribution to Arctic dust loading and INP population from HLD and six LLD source regions by implementing a source-tagging technique for dust aerosols in version 1 of the US Department of Energy's Energy Exascale Earth System Model (E3SMv1). Our results show that HLD is responsible for 30.7 % of the total dust burden in the Arctic, whereas LLD from Asia and North Africa contributes 44.2 % and 24.2 %, respectively. Due to its limited vertical transport as a result of stable boundary layers, HLD contributes more in the lower troposphere, especially in boreal summer and autumn when the HLD emissions are stronger. LLD from North Africa and East Asia dominates the dust loading in the upper troposphere with peak contributions in boreal spring and winter. The modeled INP concentrations show better agreement with both ground and aircraft INP measurements in the Arctic when including HLD INPs. The HLD INPs are found to induce a net cooling effect (−0.24 W m−2 above 60∘ N) on the Arctic surface downwelling radiative flux by changing the cloud phase of the Arctic mixed-phase clouds. The magnitude of this cooling is larger than that induced by North African and East Asian dust (0.08 and −0.06 W m−2, respectively), mainly due to different seasonalities of HLD and LLD. Uncertainties of this study are discussed, which highlights the importance of further constraining the HLD emissions.

Primary and secondary ice production: interactions and their relative importance

Abstract. A discrepancy of up to 5 orders of magnitude between ice crystal and ice nucleating particle (INP) number concentrations was found in the measurements, indicating the potentially important role of secondary ice production (SIP) in the clouds. However, the interactions between primary and SIP processes and their relative importance remain unexplored. In this study, we implemented five different ice nucleation schemes as well as physical representations of SIP processes (i.e., droplet shattering during rain freezing, ice-ice collisional break-up, and rime splintering) in the Community Earth System Model version 2 (CESM2). We ran CESM2 in the single column mode for model comparisons with the DOE Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We found that the model experiments with aerosol-aware ice nucleation schemes and SIP processes yield the best simulation results for the M-PACE single-layer mixed-phase clouds. We further investigated the relative importance of ice nucleation and SIP to ice number and cloud phase as well as interactions between ice nucleation and SIP in the M-PACE single-layer mixed-phase clouds. Our results show that SIP contributes 80 % to the total ice formation and transforms ∼30 % of pure liquid-phase clouds simulated in the model experiments without considering SIP into mixed-phase clouds. The SIP is not only a result of ice crystals produced from ice nucleation, but also competes with the ice nucleation by reducing the number concentrations of cloud droplets and cloud-borne dust INPs. Conversely, strong ice nucleation also suppresses SIP by glaciating mixed-phase clouds and thereby reducing the amount of precipitation particles (rain and graupel).

Ice multiplication from ice–ice collisions in the high Arctic: sensitivity to ice habit, rimed fraction, ice type and uncertainties in the numerical description of the process

Abstract. Atmospheric models often fail to correctly reproduce the microphysical structure of Arctic mixed-phase clouds and underpredict ice water content even when the simulations are constrained by observed levels of ice nucleating particles. In this study we investigate whether ice multiplication from breakup upon ice–ice collisions, a process missing in most models, can account for the observed cloud ice in a stratocumulus cloud observed during the Arctic Summer Cloud Ocean Study (ASCOS) campaign. Our results indicate that the efficiency of this process in these conditions is weak; increases in fragment generation are compensated for by subsequent enhancement of precipitation and subcloud sublimation. Activation of collisional breakup improves the representation of cloud ice content, but cloud liquid remains overestimated. In most sensitivity simulations, variations in ice habit and prescribed rimed fraction have little effect on the results. A few simulations result in explosive multiplication and cloud dissipation; however, in most setups, the overall multiplication effects become substantially weaker if the precipitation sink is enhanced through cloud-ice-to-snow autoconversion. The largest uncertainty stems from the correction factor for ice enhancement due to sublimation included in the breakup parameterization; excluding this correction results in rapid glaciation, especially in simulations with plates. Our results indicate that the lack of a detailed treatment of ice habit and rimed fraction in most bulk microphysics schemes is not detrimental for the description of the collisional breakup process in the examined conditions as long as cloud-ice-to-snow autoconversion is considered.

Impacts of secondary ice production on Arctic mixed-phase clouds based on ARM observations and CAM6 single-column model simulations

Abstract. For decades, measured ice crystal number concentrations have been found to be orders of magnitude higher than measured ice-nucleating particle number concentrations in moderately cold clouds. This observed discrepancy reveals the existence of secondary ice production (SIP) in addition to the primary ice nucleation. However, the importance of SIP relative to primary ice nucleation remains highly unclear. Furthermore, most weather and climate models do not represent SIP processes well, leading to large biases in simulated cloud properties. This study demonstrates a first attempt to represent different SIP mechanisms (frozen raindrop shattering, ice–ice collisional breakup, and rime splintering) in a global climate model (GCM). The model is run in the single column mode to facilitate comparisons with the Department of Energy (DOE)'s Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We show the important role of SIP in four types of clouds during M-PACE (i.e., multilayer, single-layer stratus, transition, and frontal clouds), with the maximum enhancement in ice crystal number concentrations up to 4 orders of magnitude in moderately supercooled clouds. We reveal that SIP is the dominant source of ice crystals near the cloud base for the long-lived Arctic single-layer mixed-phase clouds. The model with SIP improves the occurrence and phase partitioning of the mixed-phase clouds, reverses the vertical distribution pattern of ice number concentrations, and provides a better agreement with observations. The findings of this study highlight the importance of considering SIP in GCMs.

Thawing permafrost: an overlooked source of seeds for Arctic cloud formation

As the Arctic warms at twice the global rate, radiative feedbacks from clouds will lead to compounding impacts on the surface energy budget that affect both regional and global weather, and climate. In a future warmer world, the Arctic is projected to become cloudier. However, the formation and evolution of Arctic clouds remain highly uncertain in part due to a limited understanding of current and future sources of ice nucleating particles (INPs). In particular, the sources and abundance of biologically-derived INPs are poorly characterized, yet they may be pivotal for cloud ice formation, especially at temperatures in which Arctic mixed-phase clouds (AMPCs) persist (i.e. >−15 °C). Here, we show for the first time that permafrost is a remarkably rich source of biologically-derived INPs, both heat labile (probably proteinaceous) and other organic INPs of biomolecular origin (41%–100% and 99%–100% of the total INPs, respectively). INP concentrations in 1000 to 30 000 year old permafrost were comparable to the most active of other Arctic and midlatitude soil sources (up to 1010 INPs per gram of soil). Thawing of permafrost—which promotes metabolic activity in microbes—and subsequent mobilization of those soils directly into the atmosphere or into lakes, rivers, and the ocean, suggests the intriguing possibility that increasing emissions of INPs from this hitherto overlooked reservoir could be widespread, and, in time, greatly impact Arctic cloud cloud glaciation and radiative properties. This discovery is timely given the rapidly-thawing permafrost in Alaska and across Earth’s high latitudes. Since permafrost covers 15% of Northern Hemisphere land, this novel and prevalent INP source may become central to predictions of aerosol-cloud-precipitation interactions in AMPCs.

Relationships between Immersion Freezing and Crystal Habit for Arctic Mixed-Phase Clouds—A Numerical Study

AbstractThe number concentration of ice particles in Arctic mixed-phase clouds is a major controlling factor of cloud lifetime. The relationships between ice nucleation mode and ice crystal habit development are not yet constrained by observations. This study uses a habit-predicting microphysical scheme within a 3D large-eddy simulation model to evaluate the relationship between immersion freezing and ice habit in a simulated Arctic mixed-phase cloud case. Three immersion freezing parameterizations are considered: a volume-dependent freezing scheme (VF), a parameterization limited to activated droplets (C-AC), and a parameterization limited to coarse aerosol particles (C-CM). Both C-AC and C-CM are based on classical nucleation theory. The freezing rate with VF is found to be greater in downdraft regions than in updraft regions due to the downdraft having a higher number concentration of large droplets. The C-AC cases show active freezing of small droplets near cloud top, whereas in the C-CM cases, mainly the 8–32-μm-sized droplets freeze in updraft regions near the cloud base. Because the initial crystal size is assumed to affect the axis ratio of hexagonal plates, the VF cases produce crystals with larger axis ratios, resulting in smaller mode radii than the C-AC cases. In all cases, irregular polycrystals dominate near cloud top and a band-like structure develops within the cloud, which qualitatively agrees with previous observations. In the VF and C-CM cases, unactivated large droplets arising from coarse-mode aerosol particles contributed significantly to the freezing rate, producing an important influence on crystal habit.

Small-scale structure of thermodynamic phase in Arctic mixed-phase clouds observed by airborne remote sensing during a cold air outbreak and a warm air advection event

Abstract. The combination of downward-looking airborne lidar, radar, microwave, and imaging spectrometer measurements was exploited to characterize the vertical and small-scale (down to 10 m) horizontal distribution of the thermodynamic phase of low-level Arctic mixed-layer clouds. Two cloud cases observed in a cold air outbreak and a warm air advection event observed during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign were investigated. Both cloud cases exhibited the typical vertical mixed-phase structure with mostly liquid water droplets at cloud top and ice crystals in lower layers. The horizontal, small-scale distribution of the thermodynamic phase as observed during the cold air outbreak is dominated by the liquid water close to the cloud top and shows no indication of ice in lower cloud layers. Contrastingly, the cloud top variability in the case observed during a warm air advection showed some ice in areas of low reflectivity or cloud holes. Radiative transfer simulations considering homogeneous mixtures of liquid water droplets and ice crystals were able to reproduce the horizontal variability in this warm air advection. Large eddy simulations (LESs) were performed to reconstruct the observed cloud properties, which were used subsequently as input for radiative transfer simulations. The LESs of the cloud case observed during the cold air outbreak, with mostly liquid water at cloud top, realistically reproduced the observations. For the warm air advection case, the simulated ice water content (IWC) was systematically lower than the measured IWC. Nevertheless, the LESs revealed the presence of ice particles close to the cloud top and confirmed the observed horizontal variability in the cloud field. It is concluded that the cloud top small-scale horizontal variability is directly linked to changes in the vertical distribution of the cloud thermodynamic phase. Passive satellite-borne imaging spectrometer observations with pixel sizes larger than 100 m miss the small-scale cloud top structures.