Search

The temperature for cloud glaciation importantly determines the initialization of precipitation and lifetime of clouds. The role of anthropogenic pollutants as ice nucleating particles (INPs) to determine the cloud glaciation remains uncertain. In this study, based on satellite radar and lidar observations, the clouds either in pure liquid or mixed‐phase with liquid top were statistically analyzed over China during 2006–2019, to obtain the transition freezing temperature (T*) of cloud top where mixed‐phase becomes more frequent than pure water, with further validation by the aircraft in situ measurements. Anthropogenic pollution was observed to raise T* up to −9°C, significantly increasing it by approximately 5°C per unit of aerosol optical depth. The results provide regional‐scale evidence that anthropogenic pollutants act as efficient INPs, increasing the freezing temperature of mixed‐phase clouds. Plain Language Summary: Cloud phase transition (from liquid water to ice) is of great importance to Earth's energy and water cycle. Forming ice crystals in mixed‐phase clouds requires ice nucleating particles (INPs). However, whether the anthropogenic pollution can be efficient INPs remains unclear. In this study, based on satellite and aircraft observations in China, the temperature when clouds start to freeze is estimated by analyzing the frequency of liquid water and glaciated cloud tops, under which the occurrence of glaciated cloud tops started to overtake that of pure liquid water cloud tops. We found that the clouds over the anthropogenically polluted region over China presented higher freezing temperature than other cleaner regions. The results suggest anthropogenic pollution can efficiently control cloud glaciation in regional scale by serving as INPs. Key Points: Transition freezing temperature is estimated by analyzing the frequency of mixed‐phase and liquid clouds over China using satellite dataAnthropogenic pollution can cause freezing temperature of clouds up to −9°CAnthropogenic pollutants can be efficient ice nuclei and increase the freezing temperature of mixed‐phase clouds [ABSTRACT FROM AUTHOR]

This study utilizes the wealth of observational data collected during the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift experiment to constrain and evaluate close to two‐hundred daily Large‐Eddy Simulations (LES) of Arctic boundary layers and clouds at high resolutions. A standardized approach is adopted to tightly integrate field measurements into the experimental configuration. Covering the full drift represents a step forward from single‐case LES studies, and allows for a robust assessment of model performance against independent data under a range of atmospheric conditions. A homogeneously forced domain is simulated in a Lagrangian frame of reference, initialized with radiosonde and value‐added cloud profiles. Prescribed boundary conditions include various measured surface characteristics. Time‐constant composite forcing is applied, primarily consisting of subsidence rates sampled from reanalysis data. The simulations run for 3 hours, allowing turbulence and clouds to spin up while still facilitating direct comparison to MOSAiC data. Key aspects such as the vertical thermodynamic structure, cloud properties, and surface energy fluxes are well reproduced and maintained. The model captures the bimodal distribution of atmospheric states that is typical of Arctic climate. Selected days are investigated more closely to assess the model's skill in maintaining the observed boundary layer structure. The sensitivity to various aspects of the experimental configuration and model physics is tested. The model input and output are available to the scientific community, supplementing the MOSAiC data archive. The close agreement with observed meteorology justifies the use of LES for gaining further insight into Arctic boundary layer processes and their role in Arctic climate change. Plain Language Summary: The Arctic is one of the regions most affected by global climate change, warming up to four times as fast as the rest of the globe. It is also a particularly inaccessible region to conduct measurements. Fortunately, between 2019 and 2020 the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign collected an unprecedented amount of data in the Arctic. In this study, numerous of these measurements are incorporated into high‐resolution computer simulations of the lowest part of the Arctic atmosphere. This simulation data complements and contextualizes the observations and enables insight into complex physical processes, for example, cloud formation, cloud ice production, or turbulent mixing. The Arctic is an extreme place, and models often struggle to represent the atmosphere accurately. Therefore, the main achievement of this study is to successfully simulate 190 atmospheric situations as measured during the campaign. The generated data set performs well when compared to independent observations. Single cases deliver information about individual atmospheric conditions, and the collection gives insight into how key climate variables behaved throughout the MOSAiC year. Key Points: A standardized LES setup based on campaign data is developed with an aim to supplement the local measurements during the Multidisciplinary drifting Observatory for the Study of Arctic Climate driftIndependent drift‐long statistics on key aspects of the surface energy budget, thermodynamic structure, and clouds are reproducedSensitivity tests indicate microphysics, ice‐radiation interaction and surface representation are critical for successful daily simulations [ABSTRACT FROM AUTHOR]

We analyze the importance of cloud top temperature, dust aerosol, sea salt aerosol, and sea ice cover for the thermodynamic phase of low‐level, mid‐level, and mid to low‐level clouds observed by CloudSat/CALIPSO over the Arctic and the Southern Ocean using an explainable machine learning technique. As expected, the cloud top temperature is found to be the most important parameter for determining cloud phase. The results show also a predictive power of sea salt and sea ice on the phase of low‐level clouds, while in mid‐level clouds dust shows predictive power. Over the Southern Ocean, strong zonal winds coincide with the aerosol distribution. While they can produce high mixing ratios of sea spray at lower levels, the strong zonal winds may prevent the pole‐ward transport of dust. Sea ice may prevent the release of sea salt aerosols and marine organic aerosols leading to higher liquid fractions in clouds over sea ice. Plain Language Summary: The cloud phase describes whether a cloud consists of ice particles, liquid droplets, or both. The representation of the cloud phase in climate and weather models is uncertain, leading to radiation biases over the Southern Ocean and the Arctic Ocean. To investigate the impact of four different parameters on the cloud phase, we use an explainable machine learning technique. The parameters studied are the temperature of the cloud top, the sea ice coverage, and the concentration of sea salt aerosols and dust aerosols, both of which can act as ice nucleating particles and contribute to the ice formation in clouds. We find that temperature seems to be the most important factor in determining the cloud phase. Sea salt aerosol seems to be more relevant for low‐level clouds closer to the ocean surface, the source of sea salt aerosol. Sea ice may prevent the release of sea salt aerosol by covering the ocean and our analysis supports this hypothesis. Dust is typically transported over long distances and our analysis shows that dust aerosol is more important for mid‐level clouds, but persistent strong winds surrounding Antarctica may have an influence on the dust concentration and thus on cloud phase. Key Points: Cloud phase in polar regions can be predicted based on cloud top temperature, sea ice concentration, and sea salt and dust mixing ratiosCloud top temperature has the strongest impact, while sea salt/spray aerosol is relevant for low‐level, and dust for mid‐level cloud phaseSea ice coverage and Southern Ocean westerly winds may influence the aerosol distribution and thereby cloud phase [ABSTRACT FROM AUTHOR]

Marine cold‐air outbreaks, or CAOs, are airmass transformations whereby relatively cold boundary layer (BL) air is transported over relatively warm water. To more deeply understand BL and mixed‐phase cloud properties during CAO conditions, the Cold‐Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) took place from late 2019 into early 2020. During COMBLE, the U.S. Department of Energy's first Atmospheric Radiation Measurement Mobile Facility (AMF1) was deployed to Andenes, Norway, far downstream (∼1,000 km) from the Arctic pack ice. This study examines the two most intense CAOs sampled at the AMF1 site. The observed BL structures are open cellular with high (∼3–5 km) and cold (−30 to −50 ° ${}^{\circ}$C) cloud tops, and they often have pockets of high liquid water paths (LWPs; up to ∼1,000 g m−2 ${\mathrm{m}}^{-2}$) associated with strong updrafts and enhanced turbulence. We use a high‐resolution mesoscale model to explore how well four turbulence closure methods represent open cellular clouds. After applying a radar simulator to model outputs for direct evaluation, cloud top properties agree well with AMF1 observations (within ∼10%), but radar reflectivity and LWP agreement is more variable. Results suggest that the turbulent Prandtl number may play an important role for the simulated BL and cloud properties. All simulations produce enhanced precipitation rates that are well‐correlated with a cloud transition. Finally, the eddy‐diffusivity/mass‐flux approach produces the deepest cloud layer and therefore the largest and most coherent cellular structures. We recommend the use of a non‐local turbulence closure approach to better capture turbulent processes in intense CAOs. Plain Language Summary: Over the high latitude oceans, shallow clouds containing both liquid and frozen hydrometeors, or mixed‐phase clouds, are frequently present. Moreover, they are important to the climate system due to their role in the radiation and moisture budgets. As a result of their microphysical makeup, they are especially challenging to simulate accurately for many numerical models across a range of spatial scales. To better understand these clouds during an intense outbreak of cold air from the Arctic, we utilize measurements from a recent field campaign called the Cold‐Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). We complement the COMBLE observations with high‐resolution numerical modeling to reveal more information about the cloud structures. We find that the simulated cloud properties, including morphology and abundance of liquid water at subfreezing temperatures, are dependent upon the method used to represent vertical turbulent exchanges between the ocean and atmosphere. Key Points: Cloud properties are well‐simulated compared to one satellite data set, and disagree more than they agree with ground‐based instrumentsEddy diffusivity‐mass flux approach produces the deepest clouds and largest cell sizesPrecipitation processes likely initiate cloud transition from closed to open cells [ABSTRACT FROM AUTHOR]

By assuming that liquid droplets and ice crystals within a computational grid box grow under the same conditions, mean‐field representations of mixed‐phase clouds in numerical models favour a quick cloud glaciation driven by the Wegener–Bergeron–Findeisen process. Consequently, maintenance of mixed‐phase states under the mean‐field approximation is conditioned to external dynamical forcing, such as sufficiently strong updraughts. In this work we go beyond the mean‐field representation and investigate the maintenance of mixed‐phase states in adiabatic (non‐entraining) cloud volumes by accounting for local variability in a particle's growth conditions in the turbulent cloud environment. This is done by using a Lagrangian microphysical scheme, where temperature and vapour mixing ratio are stochastic attributes attached to each cloud particle. Different dynamic scenarios show that microphysical variability and parametrised turbulence effects may significantly reduce cloud glaciation rates, resulting in much more resilient mixed‐phase states in idealised parcels containing non‐sedimenting and non‐aggregating cloud particles. We have stated a more refined criterion for the Wegener–Bergeron–Findeisen process activity in the bulk of a mixed‐phase cloud parcel (or computational grid box). This criterion is stated in terms of the conditional average supersaturations that are experienced by specific cloud particle types (liquid or ice), and not in terms of unconditional averages corresponding to parcel‐ or grid‐mean values of supersaturations. Formulation of a relation between conditional and unconditional average supersaturations poses an interesting closure problem in mixed‐phase cloud microphysics. Our stochastic microphysical model provides a Lagrangian closure to this problem and gives insights towards the development of a prognostic stochastic subgrid‐scale scheme for condensation/deposition in numerical models of mixed‐phase clouds. [ABSTRACT FROM AUTHOR]

A heavy orographic precipitation event associated with the postfrontal sector of a midlatitude cyclone over the Australian Snowy Mountains (ASM) was analyzed using field observations and numerical simulations. This event, observed during a 2018 intensive field campaign, was of particular interest as three distinct precipitation episodes were identified within a prolonged postfrontal period. Deep mixed‐phase clouds (MPCs) characterized by cold cloud‐top temperatures (colder than −30°C) and the presence of updrafts extending 3.5–4.5 km above the boundary‐layer height, produced the three enhanced precipitation events over the windward slopes of the ASM. The presence of conditional instabilities and deep updrafts were also found in the sounding and Doppler velocity observations respectively, while the cloud radar observations show the deep MPCs with cloud tops reaching to 6–7 km a.s.l. Orographic convection invigoration was found to be the main mechanism producing the precipitation enhancement over the windward slopes and higher terrain. Using the Weather Research/Forecasting model, we analyzed the rates of microphysical processes to explicitly account for the enhancement of precipitation formation processes in these MPCs. This analysis showed that the precipitation formation processes were further enhanced through depositional and riming growth of ice‐phase hydrometeors during the three precipitation events. Deposition is simulated at higher levels (above the −15°C level) and most likely enabled by deep convective updrafts through the midtroposphere, whereas riming is stronger at lower levels (below −10°C level) due to the persistent production of feeder supercooled liquid water clouds sustained by the orographic lifting. [ABSTRACT FROM AUTHOR]

We conduct a global assessment of the spatial heterogeneity of cloud phase within the temperature range where liquid and ice can coexist. Single‐shot Cloud‐Aerosol Lidar with Orthogonal Polarization lidar retrievals are used to examine cloud phase at scales as fine as 333 m, and horizontal heterogeneity is quantified according to the frequency of switches between liquid and ice along the satellite's path. In the global mean, heterogeneity is greatest between −15 and −4°C with a peak at −5°C, when small patches of ice are prevalent within liquid‐dominated clouds. Heterogeneity "hot spots" are typically found over the extratropical continents, whereas phase is relatively homogeneous over the Southern Ocean and the eastern subtropical ocean basins, where supercooled liquid clouds dominate. Even at a fixed temperature, heterogeneity undergoes a pronounced annual cycle that, in most places, consists of a minimum during autumn or winter and a maximum during spring or summer. Based on this spatial and temporal variability, it is hypothesized that heterogeneity is affected by the availability of ice nucleating particles. These results can be used to improve the representation of subgrid‐scale heterogeneity in general circulation models, which has the potential to reduce longstanding model biases in cloud phase partitioning and radiative fluxes. Plain Language Summary: At temperatures where ice and liquid can coexist within clouds, climate models tend to produce too much ice and too little liquid compared to satellite observations. This bias is likely caused by the assumption that liquid and ice are uniformly mixed, which results in the rapid conversion of liquid to ice for thermodynamic reasons. To reduce this bias, models need to account for the spatial heterogeneity ("patchiness") of liquid and ice that exists in the real atmosphere. The goal of this paper is to quantify this spatial heterogeneity using satellite‐based lidar observations of cloud phase. We find small pockets of ice in liquid‐dominated clouds to be more common than small pockets of liquid in ice‐dominated clouds. The greatest heterogeneity is found over the midlatitude continents, whereas phase is relatively uniform over the Southern Ocean and other maritime regions with extensive low cloud cover. In the mid and high latitudes, cloud phase tends to be more heterogeneous during spring and summer and more homogeneous during autumn and winter. These results can be used in the future to improve model representations of the thermodynamic processes responsible for biases in cloud phase. Key Points: Cloud phase heterogeneity is greatest at −5°C, when small ice patches form in majority‐liquid cloudsCloud phase is relatively homogeneous over the Southern Ocean and heterogeneous over the northern continentsFor a fixed temperature, extratropical phase heterogeneity is generally greatest during local spring and summer [ABSTRACT FROM AUTHOR]

Models assume that mixed‐phase clouds consist of uniformly mixed ice crystals and liquid cloud droplets when observations have shown that they consist of clusters, or "pockets," of ice crystals and liquid cloud droplets. We characterize the spatial distribution of cloud phase over the Arctic and the Southern Ocean using active satellite observations and determine the relative importance of collocated meteorological parameters and aerosols from reanalysis to predict how uniformly mixed mixed‐phase clouds are for the first time. We performed a multi‐linear regression fit to the data set to predict the spatial distribution of the ice and liquid pockets. Contrary to what models suggest, mixed‐phase clouds are rarely perfectly homogeneous. Our results suggest that high temperatures are associated with homogeneously mixed ice and liquid pockets. We also find that a high mixing ratio of black carbon is associated with heterogeneously mixed ice and liquid pockets. Plain Language Summary: The representation of clouds in numerical models remains one of the largest uncertainties in predicting our future climate. Clouds can consist solely of liquid droplets, ice crystals, or the coexistence of both hydrometeor types. The latter cloud type is referred to as mixed phase. Climate models assume that liquid droplets and ice crystals are uniformly mixed in space in mixed‐phase clouds, but observations show that mixed‐phase clouds are organized in separate pockets of clustered liquid droplets and ice crystals. This difference in representation has a large impact on the lifetime of clouds and on their role in climate change. Using satellite observations over the Arctic and the Southern Ocean, we quantify the spatial distribution of ice and liquid in clouds. We used a statistical method to determine the relationship between meteorology and aerosols and the spatial distribution of ice and liquid. Our results suggest that high temperatures are associated with homogeneously mixed mixed‐phase clouds and high concentrations of soot are associated with heterogeneously mixed mixed‐phase clouds. Furthermore, pockets of liquid within ice clouds are larger than pockets of ice within liquid clouds. These results will improve the representation of mixed‐phase clouds in large‐scale models. Key Points: Space‐based observations and reanalysis are considered to determine the factors that control how mixed mixed‐phase clouds areLiquid dominated clouds contain small and isolated ice pockets whereas ice dominated clouds contain large and isolated liquid pocketsTemperature and black carbon play an important role in controlling the cloud phase spatial distribution and increasing phase heterogeneity [ABSTRACT FROM AUTHOR]

Ice nucleation in mixed‐phase clouds has been identified as a critical factor in projections of future climate. Here we explore how this process influences climate sensitivity using the Community Earth System Model 2 (CESM2). We find that ice nucleation affects simulated cloud feedbacks over most regions and levels of the troposphere, not just extratropical low clouds. However, with present‐day global mean cloud phase adjusted to replicate satellite retrievals, similar total cloud feedback is attained whether ice nucleation is simulated as aerosol‐sensitive, insensitive, or absent. These model experiments all result in a strongly positive total cloud feedback, as in the default CESM2. A microphysics update from CESM1 to CESM2 had substantially weakened ice nucleation, due partly to a model issue. Our findings indicate that this update reduced global cloud phase bias, with CESM2's high climate sensitivity reflecting improved mixed‐phase cloud representation. Plain Language Summary: Simulations of Earth's climate have revealed that the extent of greenhouse gas warming depends on a microscopic process in cold clouds known as ice nucleation. Problematically, this process is poorly understood and crudely represented in projections of future climate. Here we assess why ice nucleation affects Earth's projected future temperature, and estimate the sensitivity to different simulated representations of this process. We find that ice nucleation influences warming through feedback mechanisms in clouds in all regions and heights of the troposphere that are at temperatures where either ice crystals or liquid droplets may exist. The primary link between ice nucleation and warming is revealed to be the role this process has in setting the global mean ratio of ice to liquid water within clouds. We also demonstrate that an issue that weakened ice nucleation in a widely used climate model reduced bias in this ratio. Our findings suggest that the reduced bias is responsible for this model's strong global warming projections, enhancing the possibility that such projections may be realistic. Key Points: Ice nucleation representation is only found to sizably affect total cloud feedback when allowed to promote biased global mean cloud phaseCommunity Earth System Model 2's strongly positive cloud feedback is consistent with realistic mixed‐phase cloud representation despite a known model issueSimulated relationships among ice nucleation, cloud phase, and feedback strength are partly set by mid‐level and tropical high clouds [ABSTRACT FROM AUTHOR]

Cloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented. Plain Language Summary: Arctic clouds contribute to the uncertainty attributed to global cloud‐related atmospheric feedbacks as implemented in climate models. This uncertainty ensues from incomplete observational and theoretical knowledge of cloud processes. Arctic snow properties at the cloud base level can be very useful to constrain and evaluate model simulations. However, the retrieval of cloud base precipitation properties is challenging. Analysis of radar and lidar measurements performed at fixed sites distributed around the world can nonetheless be used to estimate such essential information. Here I describe a model designed for the estimation of cloud base snow properties over Utqiagvik, North Slope of Alaska, which uses long‐term (7.5 years) radar and lidar measurements. These properties include, among others, snow particle number concentrations, integrated mass, particle size distribution parameters, precipitation rates, mass‐weighted fall velocities, vertical air motions, and effective radii, all of which are highly valuable for model evaluation and general understanding of processes resulting in polar cloud moisture loss. The model core relies on a Bayesian inference algorithm, allowing the examination of the impact of various instrument and atmospheric state characteristics on model agreement with observations. This article includes a comprehensive depiction and discussion of model run results as well as retrieval limitations. Key Points: A Markov Chain Monte Carlo‐type model applied to ground‐based data from the North Slope of Alaska (NSA) elucidates cloud base ice propertiesThe long‐term NSA data set analysis indicates ice number concentration enhancements at −15 and −5°C, possibly secondary ice production eventsParameterizations of Arctic cloud base ice precipitation rate and ice water content as a function of reflectivity (Ze‐SR, Ze‐IWC) are derived [ABSTRACT FROM AUTHOR]

Vertical profiles of cloud microphysical properties importantly determine the lifetime and precipitation rate of clouds. The 94‐GHz cloud profiling radar (CPR) onboard the CloudSat satellite can measure the vertical profile of radar reflectivity, from which the microphysical properties of cloud can be retrieved. The retrievals bear variations due to various assumptions and auxiliary products used. This study targets on the mid‐latitude clouds in the northern hemisphere, and intercompares the CloudSat products describing the vertical profiles of cloud microphysics and evaluate the uncertainties for each retrieval algorithm, with further evaluation by aircraft in‐situ observations over the North China Plain region during 2013–2017. For those retrieval products performing phase apportion, the ambient temperature‐based linear apportioning on mixed‐phase clouds can produce reasonable estimation on ice water content, apart from the heavily precipitating clouds. The retrieved liquid water content constrained by cloud optical depth well matched in‐situ observations, however its effective size is overestimated (hereby underestimating the number concentration of water droplets) because of the influence of larger precipitating hydrometeors on size distribution. The CPR‐only retrieval can well produce the effective diameter and number concentration of ice for deep convection clouds, but using additional lidar constraint underestimates the effective diameter due to the intense attenuation by thick clouds. The analysis here suggests the appropriate parameters from various products for different cloud types, and provides guidance for future development of retrieval algorithms on vertical profiles of cloud microphysical properties. Plain Language Summary: Vertical profiles of cloud microphysical properties play an important role in the cloud lifetime and precipitation rate. The 94‐GHz cloud profiling radar (CPR) onboard the CloudSat satellite can retrieve the vertical profile of cloud microphysical properties based on measured radar reflectivity. However, the retrievals bear variations due to different assumptions and auxiliary products used. By comparing various CloudSat products and aircraft in‐situ measurements over the North China Plain, our results demonstrate that radar retrievals constrained by cloud optical depth can well produce liquid water content but overestimate its effective diameter. For the temperature‐based linear apportioning products, the mixed‐phase clouds can produce reasonable estimation on ice water content, apart from the heavily precipitating clouds. These indicate the appropriate cloud microphysical parameters under certain circumstances using different retrieval algorithms and measurement constraints should be specific for cloud types. Key Points: Vertical profiles of cloud microphysics from various CloudSat products and aircraft in‐situ observations are intercompared over the North China PlainRadar retrievals constrained by cloud optical depth can well produce liquid water content but overestimate its effective diameterAmbient temperature‐based linear apportioning on mixed‐phase clouds can produce reasonable estimates on ice water content apart from the heavily precipitating clouds [ABSTRACT FROM AUTHOR]

The formation of ice in clouds is an important process in mixed-phase clouds, and the radiative properties and dynamical developments of clouds strongly depend on their partitioning between liquid and ice phases. In this study, we investigate the sensitivities of the cloud phase to ice-nucleating particle (INP) concentration and thermodynamics. Experiments are conducted using the ICOsahedral Nonhydrostatic model (ICON) at the convection-permitting resolution of about 1.2 km on a domain covering significant parts of central Europe, and are compared to two different retrieval products based on SEVIRI measurements. We select a day with several isolated deep convective clouds, reaching a homogeneous freezing temperature at the cloud top. The simulated cloud liquid pixel number fractions are found to decrease with increasing INP concentration both within clouds and at the cloud top. The decrease in cloud liquid pixel number fraction is not monotonic but is stronger high INP cases. Cloud-top glaciation temperatures shift toward warmer temperatures with increasing INP concentration by as much as 8 °C. Moreover, the impact of INP concentration on cloud phase partitioning is more pronounced at the cloud top than within the cloud. Moreover, initial and lateral boundary temperature fields are perturbed with increasing and decreasing temperature increments from 0 to +/-3K and +/-5K between 3 and 12 km. Perturbing the initial thermodynamic state is also found to affect the cloud phase distribution systematically. However, the simulated cloud-top liquid number fraction, diagnosed using radiative transfer simulations as input to a satellite forward operator and two different satellite remote sensing retrieval algorithms, deviates from one of the satellite products regardless of perturbations in the INP concentration or the initial thermodynamic state for warmer sub-zero temperatures, while agreeing with the other retrieval scheme much better, in particular for the high INP and high convective available potential energy (CAPE) scenarios. Perturbing the initial thermodynamic state, which artificially increases the instability of the mid- and upper-troposphere, brings the simulated cloud-top liquid number fraction closer to the satellite observations, especially in the warmer mixed phase temperature range. [ABSTRACT FROM AUTHOR]

Recent observations show that dust emitted within the Arctic (Arctic dust) has a remarkably high ice nucleating ability, especially between −20°C and −5°C, but its impacts on the number concentrations of ice nucleating particles (INPs) and radiative balance in the Arctic are not well understood. Here we incorporate an observation‐based ice‐nucleation parameterization indicating the high ice nucleating ability of Arctic dust into a global aerosol‐climate model. A simulation using this parameterization better reproduces INP observations in the Arctic and estimates >100 times higher dust INP number concentrations with ∼100% contribution from Arctic dust in the Arctic lower troposphere (>60°N and >700 hPa) during summer and fall (June–November) than a simulation applying a standard ice‐nucleation parameterization suitable for desert dust to Arctic dust. Our results demonstrate the importance of considering an ice‐nucleation parameterization suitable for Arctic dust when simulating INPs and their effects on aerosol‐cloud interactions in the Arctic. Plain Language Summary: Dust is an important aerosol type acting as "ice nucleating particles," which initiate the formation of ice crystals within mixed‐phase clouds (consisting of both supercooled water droplets and ice crystals) and influence the cloud lifetime and distribution. Recent observations show that dust is emitted from ice‐ and vegetation‐free areas in the Arctic region (hereafter Arctic dust), which has a remarkably high ice nucleating ability, compared with desert dust such as Asian dust and Saharan dust, because of the presence of certain organic matter. However, the impacts of Arctic dust with high ice nucleating ability on ice nucleating particles and mixed‐phase clouds in the Arctic are unknown. In this study, we investigate the importance of Arctic dust with high ice nucleating ability for ice nucleating particles in the Arctic using a global aerosol‐climate model. Our simulation results show that Arctic dust accounts for almost all dust ice nucleating particles in the Arctic lower troposphere (>60°N and about 0–3 km) during summer and fall (June–November). This study demonstrates the importance of considering the high ice nucleating ability of Arctic dust when simulating ice nucleating particles and their impacts on mixed‐phase clouds and radiative balance in the Arctic. Key Points: Arctic dust, emitted within the Arctic, accounts for most of dust ice nucleating particles in the Arctic lower troposphere in summer to fallImportance of Arctic dust as ice nucleating particles in the Arctic strongly depends on its high ice nucleating ability at high temperaturesConsidering an ice‐nucleation parameterization suitable for Arctic dust is crucial for aerosol‐cloud‐climate simulations in the Arctic [ABSTRACT FROM AUTHOR]

The sizes and shapes of ice crystals influence the radiative properties of clouds, as well as precipitation initiation and aerosol scavenging. However, ice crystal growth mechanisms remain only partially characterized. We present the growth processes of two complex ice crystal habits observed in Arctic mixed‐phase clouds during the Ny‐Ålesund AeroSol Cloud ExperimeNT campaign. First, are capped‐columns with multiple columns growing out of the plates' corners that we define as columns on capped‐columns. These ice crystals originated from cycling through the columnar and plate temperature growth regimes, during their vertical transport by in‐cloud circulation. Second, is aged rime on the surface of ice crystals having grown into faceted columns or plates depending on the environmental conditions. Despite their complexity, the shapes of these ice crystals allow to infer their growth history and provide information about the in‐cloud conditions. Additionally, these ice crystals exhibit complex shapes and could enhance aggregation and secondary ice production. Plain Language Summary: Snowflakes formed in the atmosphere have a wide variety of shapes and sizes and no two snowflakes are identical. The reason for this infinite number of shapes is that the environmental temperature and relative humidity prevailing during the snowflakes' growth determine their exact aspects. Thus, the prevailing environmental conditions can be determined from the shape of snowflakes, and become more complicated with increased shape complexity. During a measurement campaign in the Arctic, we identified two complex snowflake types and the history of environmental conditions in which they grew in. We inferred that some snowflakes were recirculating to higher or lower parts of the clouds and that others had collided with cloud droplets that froze on their surface at the early stage of their growth. These snowflakes may enhance the formation of new snowflakes and the initiation of precipitation. Key Points: A large variety of ice crystal sizes and shapes were observed in Arctic mixed‐phase clouds with a holographic imagerThe growth history of two types of complex ice crystals was inferred from their shapesThese ice crystals could enhance aggregation and secondary ice production [ABSTRACT FROM AUTHOR]

Mixed‐phase clouds are recognized as significant contributors to the modulation of precipitation and radiation transfer on both regional and global scales. This study is focused on the analysis of spatial inhomogeneity of mixed‐phase clouds based on an extended data set obtained from airborne in situ observations. The lengths of continuous segments of ice, liquid, and mixed‐phase clouds present a cascade of scales varying from 102 km down to a minimum scale of 100 m determined by the spatial resolution of measurements. It was found that the phase composition of mixed‐phase clouds is highly intermittent, and the frequency of occurrence of ice, liquid, and mixed‐phase regions increases with the decrease of their spatial scales. The distributions of spatial scales have well‐distinguished power‐law dependencies. The results obtained yield insight into the morphology of mixed‐phase clouds and have important implications for improvement in representing subgrid inhomogeneity of mixed‐phase clouds in weather and climate models. Plain Language Summary: In situ observations showed that mixed‐phase clouds might exist in the form of two extremes: (a) genuinely mixed, when supercooled droplets and ice particles are uniformly distributed in a cloud volume, and (b) conditionally mixed, when ice and liquid phases are spatially separated. The objective of this study is to explore spatial scales of genuinely mixed and single‐phase ice and liquid cloud segments. It was found that the spatial scales of genuine mixed‐phase, ice and liquid phase clouds may vary from 100 km down to 100 m or even smaller. The obtained results are of great importance for improvements in the subgrid presentation of mixed‐phase clouds in numerical weather and climate models and interpretation of remote sensing measurements. Key Points: In mixed‐phase clouds droplets and ice particles may be uniformly distributed (genuinely mixed) or spatially separated (conditionally mixed)Horizontal lengths of genuine mixed‐phase and single‐phase ice and liquid clouds present a cascade of scales from 100 km down to 100 m or lessAt small scales mixed‐phase clouds have high spatial intermittency, which is currently unconstrained in weather and climate models [ABSTRACT FROM AUTHOR]

Maritime boundary‐layer clouds over the Southern Ocean (SO) have a large shortwave radiative effect. Yet, climate models have difficulties in representing these clouds and, especially, their phase in this observationally sparse region. This study aims to increase the knowledge of SO cloud phase by presenting in‐situ cloud microphysical observations from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES). We investigate the occurrence of ice in summertime marine stratocumulus and cumulus clouds in the temperature range between 6 and −25°C. Our observations show that in ice‐containing clouds, maximum ice number concentrations of up to several hundreds per liter were found. The observed ice crystal concentrations were on average one to two orders of magnitude higher than the simultaneously measured ice nucleating particle (INP) concentrations in the temperature range below −10°C and up to five orders of magnitude higher than estimated INP concentrations in the temperature range above −10°C. These results highlight the importance of secondary ice production (SIP) in SO summertime marine boundary‐layer clouds. Evidence for rime splintering was found in the Hallett‐Mossop (HM) temperature range but the exact SIP mechanism active at lower temperatures remains unclear. Finally, instrument simulators were used to assess simulated co‐located cloud ice concentrations and the role of modeled HM rime‐splintering. We found that CAM6 is deficient in simulating number concentrations across the HM temperature range with little sensitivity to the model HM process, which is inconsistent with the aforementioned observational evidence of highly active SIP processes in SO low‐level clouds. Plain Language Summary: Clouds in the Southern Ocean are important for climate but not well represented in climate models. Observations in this remote region have been rare. This study presents results from a recent airborne campaign that took place in the Southern Ocean where low‐ and mid‐level clouds were investigated by detecting individual cloud particles within the clouds. Although large fraction of the observed clouds did not contain ice crystals, occasionally high amounts of ice crystals were observed that cannot be explained by ice formation on aerosol particles but were result of multiplication of existing ice crystals. We tested the capability of a commonly used climate model to represent the observed ice concentrations and their sensitivity to one ice multiplication process parameterized in the model. These investigations revealed that the in the model the ice multiplication process was not responsible for generation of ice, which is in contradiction with the observations. Key Points: Ice concentrations several orders of magnitude higher than ice nucleating particle concentrations were observedSecondary ice production was believed to be responsible for the observed high ice number concentrationsComparison with climate model indicated that secondary ice processes are still inadequately represented in the model [ABSTRACT FROM AUTHOR]

Mixed‐phase clouds (MPCs), which consist of both supercooled cloud droplets and ice crystals, play an important role in the Earth's radiative energy budget and hydrological cycle. In particular, the fraction of ice crystals in MPCs determines their radiative effects, precipitation formation and lifetime. In order for ice crystals to form in MPCs, ice‐nucleating particles (INPs) are required. However, a large‐scale relationship between INPs and ice initiation in clouds has yet to be observed. By analyzing satellite observations of the typical transition temperature (T*) where MPCs become more frequent than liquid clouds, we constrain the importance of INPs in MPC formation. We find that over the Arctic and Southern Ocean, snow and sea ice cover significantly reduces T*. This indicates that the availability of INPs is essential in controlling cloud phase evolution and that local sources of INPs in the high‐latitudes play a key role in the formation of MPCs. Plain Language Summary: Mixed‐phase clouds (MPCs), which consist of both liquid droplets and ice crystals, play an important role for the Earth's climate system. For example, the number of ice crystals in MPCs determines how much sunlight is reflected by the cloud and how efficiently the cloud can form precipitation. The formation of ice crystals in MPCs requires a special subset of aerosol particles called ice‐nucleating particles (INPs). INPs are required for liquid cloud droplets to freeze at temperatures warmer than −36°C. However, a large‐scale relationship between INPs and ice formation in clouds has yet to be observed. Using satellite observations, we determine the transition temperature (T*) where MPCs become more frequent than liquid clouds and find that T* is strongly dependent on snow and sea ice cover over the Arctic and Southern Ocean. This indicates that sea ice and snow cover act as a lid that inhibits the emission of INPs from the ocean. In a warming world with retreating sea ice and snow cover, our results suggest that clouds in these regions will contain ice crystals at warmer temperatures than previously estimated and, thus, have potential implications for future warming predictions. Key Points: Ice‐nucleating particles (INPs) control ice formation in high‐latitude cloudsSea ice and snow cover inhibit the local emission of INPs, which directly influences cloud phase in the Arctic and Southern OceanThis has implications for the predicted negative cloud phase feedback with future warming and the associated sea ice and snow cover loss [ABSTRACT FROM AUTHOR]

Abstract The Advanced Microphysics Prediction System (AMPS), which adopts a two‐moment hybrid‐bin habit‐predicting scheme, was previously developed to study cloud microphysical processes that depend on ice habit; however, only one particular atmospheric model, the University of Wisconsin‐Nonhydrostatic Modeling System, has been used to test the AMPS. In this study, AMPS is implemented into the Scalable Computing for Advanced Library and Environment (SCALE) large‐eddy simulation model. The AMPS Eulerian advection scheme for non‐mass characteristic variables of ice particles, such as axis lengths, is refined to minimize numerical artifacts. The resulting SCALE‐AMPS model successfully reproduces features of mixed‐phase clouds observed during the Surface Heat Budget of the Arctic campaign, including liquid water path (LWP), ice particle size distributions, and ice habits, when ice particle number concentrations (Nice) are reproduced. Sensitivity studies show that increases in Nice result in reductions of LWP that are generally consistent with previous results. Interestingly, LWP reductions lead to changes in ice habits through increases in cloud temperature due to weaker cloud top radiative cooling. Furthermore, aspect ratios of precipitating particles also change following LWP reductions, because in Bigg's immersion freezing scheme, adopted in this study, the aspect ratios depend on the initial size of the ice particles and freezing rates depend on both temperature and droplet size. Because habits of ice particles affect their growth rates, fall speeds, and collision rates, the results obtained in this study reveal possible feedback processes of Arctic mixed‐phase clouds operating through ice habits.

The amount of ice versus supercooled water in clouds is important for their radiative properties and role in climate feedbacks. Hence, knowledge of the concentration of ice‐nucleating particles (INPs) is needed. Generally, the concentrations of INPs are found to be very low in remote marine locations allowing cloud water to persist in a supercooled state. We had expected the concentrations of INPs at the North Pole to be very low given the distance from open ocean and terrestrial sources coupled with effective wet scavenging processes. Here we show that during summer 2018 (August and September) high concentrations of biological INPs (active at >−20°C) were sporadically present at the North Pole. In fact, INP concentrations were sometimes as high as those recorded at mid‐latitude locations strongly impacted by highly active biological INPs, in strong contrast to the Southern Ocean. Furthermore, using a balloon borne sampler we demonstrated that INP concentrations were often different at the surface versus higher in the boundary layer where clouds form. Back trajectory analysis suggests strong sources of INPs near the Russian coast, possibly associated with wind‐driven sea spray production, whereas the pack ice, open leads, and the marginal ice zone were not sources of highly active INPs. These findings suggest that primary ice production, and therefore Arctic climate, is sensitive to transport from locations such as the Russian coast that are already experiencing marked climate change. Plain Language Summary: Clouds play a critical role in Earth's climate, both reflecting incoming sunlight and trapping outgoing infrared radiation. Hence, even small errors in the representation of clouds in climate models can lead to uncertainty in predictions of, for example, sea ice extent. In the Arctic, liquid clouds often exist below 0°C and cloud water droplets can exist in a supercooled liquid state. In the absence of special particles that can trigger ice formation in droplets, ice‐nucleating particles (INPs), supercooled water droplets can cool well below −35°C before spontaneously freezing. The presence of INPs can reduce the lifetime of a cloud and the amount of supercooled water in clouds, making them less reflective. Based on our knowledge of INPs in other remote oceans, we expected very low INP concentrations in the central Arctic. However, we found very high concentrations of biological INPs in the summertime North Pole. Furthermore, these INPs come from the seas off the coast of Russia, a region already experiencing strong climate change. It is possible that these sources may become even more important as the Arctic becomes increasingly ice‐free, causing changes in Arctic clouds and further changes in climate. Key Points: The concentration of ice‐nucleating particles at the North Pole in summer 2018 was amongst the highest anywhere in the worldBiological ice‐nucleating particles were derived from the Russian seas and perhaps associated with wind‐driven sea sprayThe concentration of ice‐nucleating particles at the surface was often different to that higher in the boundary layer where clouds form [ABSTRACT FROM AUTHOR]

This paper analyzes the temperature, cloud type, and life stage dependencies of phase partitioning in mixed-phase clouds spanning tropics, midlatitudes, and the Arctic, using data from ground-based remote sensing measurements in Alaska and aircraft measurements from three field campaigns. The results show: (1) The liquid fraction in Arctic stratiform clouds decreased from 1 to 0.6 between 0 °C and −30 °C and was lower in spring because of the higher dust occurrence in Barrow, Alaska; (2) In wintertime orographic clouds, the liquid fraction was greater than 0.8; (3) Phase partitioning in convective clouds varied significantly with life stages. In the developing stage, it decreased from 1 to 0.3 between −5 °C and −15 °C, indicating rapid ice generation, while at the mature and dissipating stages, the liquid fractions were lower; (4) The stratiform regions of mesoscale convective systems were dominated by ice, with liquid fractions lower than 0.2; and (5) The variability of phase partitioning varied for different cloud types. In stratiform clouds, liquid dominated at warm temperatures. As the temperature decreased, an ice-dominated region was more frequently observed, while the occurrence of the mixed-phase region remained low. For convective clouds, the variability of phase partitioning was controlled by continuous glaciation with decreasing temperature and life cycle. [ABSTRACT FROM AUTHOR]

Changes in the ambient aerosol concentration are known to affect the microphysical properties of clouds. Especially regarding precipitation formation, increasing aerosol concentrations are assumed to delay the precipitation onset, but may increase precipitation rates via convective invigoration and orographic spillover further downstream. In this study, we analyse the effect of increased aerosol concentrations on a heavy precipitation event observed in summer 2017 over northeastern Switzerland, an event which was considerably underestimated by the operational weather forecast model. Preceding the precipitation event, Saharan dust was advected towards the Alps, which could have contributed to increased precipitation rates north of the Alpine ridge. To investigate the potential impact of the increased ambient aerosol concentrations on surface precipitation, we perform a series of sensitivity simulations using the Consortium for Small-scale Modeling (COSMO) model with different microphysical parametrizations and prognostic aerosol perturbations. The results show that the choice of the microphysical parametrization scheme in terms of a one- or two-moment scheme has the relatively largest impact on surface precipitation rates. In the one-moment scheme, surface precipitation is strongly reduced over the Alpine ridge and increased further downstream. Simulated changes in surface precipitation in response to aerosol perturbations remain smaller in contrast to the impact of the microphysics scheme. Elevated cloud condensation nuclei (CCN) concentrations lead to increased cloud water and decreased cloud ice mass, especially in regions of high convective activity south of the Alps. These altered cloud properties indeed increase surface precipitation further downstream, but the simulated change is too small to explain the observed heavy precipitation event. Additional ice-nucleating particles (INPs) increase cloud ice mass, but only trigger local changes in downstream surface precipitation. Thus, increased aerosol number concentrations during the Saharan dust outbreak are unlikely to have caused the heavy precipitation event in summer 2017. [ABSTRACT FROM AUTHOR]

Due to the complex interplay of various meteorological phenomena, simulating weather is a challenging and open research problem. In this contribution, we propose a novel physics-based model that enables simulating weather at interactive rates. By considering atmosphere and pedosphere we can define the hydrologic cycle - and consequently weather - in unprecedented detail. Specifically, our model captures different warm and cold clouds, such as mammatus, hole-punch, multi-layer, and cumulonimbus clouds as well as their dynamic transitions. We also model different precipitation types, such as rain, snow, and graupel by introducing a comprehensive microphysics scheme. The Wegener-Bergeron-Findeisen process is incorporated into our Kessler-type microphysics formulation covering ice crystal growth occurring in mixed-phase clouds. Moreover, we model the water run-off from the ground surface, the infiltration into the soil, and its subsequent evaporation back to the atmosphere. We account for daily temperature changes, as well as heat transfer between pedosphere and atmosphere leading to a complex feedback loop. Our framework enables us to interactively explore various complex weather phenomena. Our results are assessed visually and validated by simulating weatherscapes for various setups covering different precipitation events and environments, by showcasing the hydrologic cycle, and by reproducing common effects such as Foehn winds. We also provide quantitative evaluations creating high-precipitation cumulonimbus clouds by prescribing atmospheric conditions based on infrared satellite observations. With our model we can generate dynamic 3D scenes of weatherscapes with high visual fidelity and even nowcast real weather conditions as simulations by streaming weather data into our framework. [ABSTRACT FROM AUTHOR]

Increases in aerosol concentration are well known to influence the microphysical processes and radiative properties of clouds. By reducing droplet size, an increase in aerosol can lessen collision efficiency and increase liquid water path (LWP) in precipitating clouds or enhance evaporation rate and decrease LWP in non‐precipitating clouds. We utilize large eddy simulations to further investigate these aerosol indirect effects in Arctic mixed‐phase clouds and find, in agreement with previous studies, precipitating clouds to experience an increase in LWP and non‐precipitating clouds a decrease in LWP. Most importantly however, our results reveal a different explanation for why such an LWP decrease occurs in decoupled, non‐precipitating clouds. We find enhanced evaporation near cloud top to be driven primarily by a strengthening of maximum radiative cooling rate with aerosol concentration which drives stronger entrainment, an effect that holds true even in clouds that are optically thick. Plain Language Summary: Known as aerosol indirect effects, atmospheric aerosols can alter cloud processes and properties by serving as particles for water to condense on to form droplets. Depending on whether or not a cloud is producing rain and snow, an increase in the amount of aerosol present can either cause an increase in cloud amount by slowing precipitation formation or a decrease in cloud amount by quickening evaporation. Our study confirms these responses. However, the physical mechanism driving the decreased cloud amount is found to differ from previous studies. Certainly there is more evaporation with more aerosol, but we show that the extra evaporation is primarily driven by a strengthening of the maximum radiative cooling at cloud top (which leads to greater mixing of dry air and evaporation) rather than driven directly by smaller cloud droplet sizes that evaporate more easily. Key Points: Maximum cloud top radiative cooling rate depends on both liquid water path and drop size even when clouds are optically thickIncreases in aerosol concentration strengthen maximum radiative cooling rate at cloud topStronger maximum cloud top cooling strengthens entrainment and evaporation which reduces liquid water in decoupled, non‐precipitating clouds [ABSTRACT FROM AUTHOR]

Volcanic ash (VA) from explosive eruptions contributes to aerosol loadings in the atmosphere. Aside from the negative impact of VA on air quality and aviation, these particles can alter the optical and microphysical properties of clouds by triggering ice formation, thereby influencing precipitation and climate. Depending on the volcano and eruption style, VA displays a wide range of different physical, chemical, and mineralogical properties. Here, we present a unique data set on the ice nucleation activity of 15 VA samples obtained from different volcanoes worldwide. The ice nucleation activities of these samples were studied in the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud simulation chamber as well as with the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT). All VA particles nucleated ice in the immersion freezing mode from 263 to 238K with ice nucleation active site (INAS) densities ranging from ∼105 to 1011 m−2, respectively. The variabilities observed among the VA samples, at any given temperature, range over 3.5 orders of magnitude. The ice‐nucleating abilities of VA samples correlate to varying degrees with their bulk pyroxene and plagioclase contents as a function of temperature. We combined our new data set with existing literature data to develop an improved ice nucleation parameterization for natural VA in the immersion freezing mode. This should be useful for modeling the impact of VA on clouds. Plain Language Summary: Volcanic ash particles, which are generated during volcanic eruptions, can initiate ice formation in clouds. The clouds formed by these volcanic ash particles can influence precipitation, and in turn, weather and climate. In our study, we investigated the ability with which volcanic ash particles form ice in clouds. We performed our study in a state‐of‐the‐art aerosol and cloud simulation chamber and on a cold‐stage instrument. The findings show that volcanic ash particles can form ice as effectively as mineral dust particles or their components. These results will help scientists to have a better understanding of the impact of volcanic ash particles on clouds. Key Points: The ice‐nucleating ability of natural volcanic ash particles in the immersion freezing mode can vary by 3.5 orders of magnitudeIce‐nucleating properties of volcanic ash particles correlate to varying degrees with their pyroxene and plagioclase contentsThe temperature‐dependent immersion freezing ability of volcanic ash is approximated with an exponential fit line [ABSTRACT FROM AUTHOR]

Low‐level mixed‐phase clouds are important for Earth's climate but are poorly represented in climate models. A one‐moment microphysics scheme from Seiki and Roh (2020, https://doi.org/10.1175/JAS-D-19-0266.1) improves the representation of supercooled water and verifies it with a single‐column model. We evaluate the performance of this scheme using a global cloud‐system‐resolving simulation. We show that the scheme has several major improvements over the original scheme on which it is based, which underestimated the generation of supercooled droplets. The new scheme suppresses the original scheme's tendency to overestimate the conversion of cloud water to rain, vapor to cloud ice, and cloud water to cloud ice. It greatly improves the previously underestimated production of low‐level mixed‐phase clouds at middle‐to‐high latitudes, particularly over the ocean at the middle latitudes of the Southern Hemisphere. It also increases the lifetime of liquid clouds, thus improving the simulation of low‐level liquid clouds in western coastal regions of the tropics. The temperature dependency of the ratio of mass fraction of liquid cloud to the sum of ice and liquid clouds, F, reveals that mixed‐phase clouds statistically develop in a much wider range of temperature (−30°C ∼ 0°C), which supports the development of more mixed‐phase clouds in our simulation. The change to a wider range of F at given temperature is expected to be important, because it allows more complex feedback processes to arise from different cloud phase regimes. An improved simulation in seasonal variation of shortwave radiation and its cloud radiative effect are also identified. Plain Language Summary: Low‐level mixed‐phase clouds are important for the Earth's radiation budget because they persistently develop especially over the Southern Ocean, and reflect sunlight back to space. However, most climate models have suffered from simulating those mixed‐phase clouds, which has been a major source of uncertainty to project a future climate change. This paper reveals that an improved modeling of mixed‐phase clouds leads to better representation of the global distribution and seasonal change of mixed‐phase clouds considerably, which also results in an improved simulation of the Earth's radiation budget. The present result is capable of contributing to improve not only our climate model, but current climate models worldwide. Key Points: We use a global cloud‐system‐resolving simulation to analyze a one‐moment microphysics scheme for representing mixed‐phase low‐level cloudsWe show that the new scheme improves the representation of supercooled water and increases the lifetime of liquid cloudsThe new scheme also better represents seasonal changes in reflection of solar radiation, compared with the previous schemes [ABSTRACT FROM AUTHOR]

Abstract What concentration of ice‐nucleating particles is required to completely glaciate a typical atmospheric supercooled liquid cloud? This seemingly esoteric question has far reaching implications, as the ratio of liquid to ice in these clouds governs, for example, their influence on Earth's radiation budget and their precipitation efficiency. Microphysical properties of steady‐state mixed‐phase clouds formed in a laboratory convection chamber are observed using digital holography. It is observed that the ratio of ice to total water content of steady‐state mixed‐phase clouds is determined by the concentration of ice‐nucleating aerosol particles. Existing theory is adapted to show such clouds result from a balance between the thermodynamic forcing (i.e., the source of excess water vapor that is condensing to liquid and ice) and the number and size of particles that become ice (i.e., the ice integral radius). The measurements quantitatively support the Korolev‐Mazin conditions for existence of mixed‐phase clouds.

Mineral dust affects the microphysical and radiative properties of mixed‐phase clouds and hence the radiative balance of the Earth by acting as ice nucleating particles (INPs). However, the importance of Asian dust as INPs is not well understood. In this study, we examined the contribution of Asian dust to global dust INPs and its effect on cloud radiative forcing (CRF) using a global aerosol‐climate model with an ice nucleation parameterization that links INP number concentrations to ambient temperature and dust number concentrations. Our model well reproduces INP number concentrations measured over the Tokyo Metropolitan area in Japan during May 2017, when Asian dust was transported to Japan. Our simulation for the years 2013–2017 shows that Asian dust extends from its source regions (e.g., the Gobi and Taklimakan Deserts) to the North Pacific, North America, and the Arctic. Notably, Asian dust is transported to higher altitudes (i.e., to temperature regimes relevant for the formation of mixed‐phase clouds) more efficiently than dust from other regions. The annual‐mean simulated contribution of Asian dust to global dust INPs is 15%, which is 4.4 times higher than its contribution to global atmospheric dust loading (3.4%). These characteristics of Asian dust show its high potential to act as INPs in mixed‐phase clouds. Sensitivity simulations show that Asian dust INPs have a positive net CRF of 0.054–0.19 W m−2 in East Asia and the North Pacific during 2013–2017 (cf. 0.092–1.0 W m−2 for dust from other regions). Key Points: Asian dust can be transported to temperature regimes relevant for mixed‐phase clouds more efficiently than dust from other sourcesAsian dust contributes 15% of the global dust ice nucleating particles (INPs), while its contribution to the global dust loading is only 3.4%INPs from Asian dust have a net cloud radiative forcing of 0.054–0.19 W m−2 in East Asia and the North Pacific [ABSTRACT FROM AUTHOR]

Mixed‐phase clouds (MPCs), composed of both liquid and ice, are prevalent in Southern Ocean cyclones. A characterization of these clouds on fine vertical scales is required in order to understand the microphysical processes within these clouds, and for model and satellite evaluations over this region. We investigated three examples of cloud systems collected by ship‐mounted remote‐sensing instruments adjacent to East Antarctica at latitudes between 64°S and 69°S. These cases allow us to examine the properties of midlevel MPCs, with cloud tops between 2 and 6 km. Midlevel MPCs contain multiple layers of supercooled liquid water (SLW) embedded within ice during the passage of cyclones. SLW layers are capped by strong temperature inversions and are observed at temperatures as low as −31°C. Convective generating cells (GCs) are present inside supercooled liquid‐topped midlevel MPCs. The horizontal extent, vertical extent, and maximum upward Doppler velocity of these GCs were 0.6–3.6 km, 0.7–1.0 km, and 0.5–1.0 m s−1, respectively, and are consistent with observations from previous lower‐latitude studies. Ice precipitation is nearly ubiquitous, except in the thinnest clouds at the trailing end of the observed systems. Seeding of lower SLW layers from above leads to periods with either larger ice particles or greater ice precipitation rates. Periods of supercooled drizzle lasting up to 2 h were observed toward the end of two of the three cyclone systems. This supercooled drizzle turns into predominantly ice precipitation as the result of seeding by ice clouds located above the precipitating SLW layer. Key Points: Generating cells at the top of midlevel mixed‐phase clouds are commonly observed over the high‐latitude Southern OceanSupercooled drizzle is present in two of the three cases examined here with phase changes following supercooled liquid layer seedingSeeding of single‐layer ice‐precipitating supercooled liquid clouds occurs in the trailing clouds of each system [ABSTRACT FROM AUTHOR]

The thermodynamic phase transition of clouds is still not well understood, therefore, the partitioning of ice and liquid in mixed phase clouds is often misrepresented in numerical models. We use 12 years of cloud observations from the geostationary Spinning Enhanced Visible and InfraRed Imager over the Southern Ocean to detect clouds which contain both liquid and ice pixels at their tops and we retrieve microphysical and radiative properties in each cloud object. The results show that large cloud droplet effective radius coincides with high ice fraction and high ice optical thickness for cloud top temperatures higher than −8 °C. We also found that the density of ice pixel clusters increases with the cloud ice fraction, for ice fraction lower than 0.5, suggesting a multiplication of ice pockets in line with previous studies, particularly efficient for clouds with high perimeter fractal dimension. Plain Language Summary: Clouds with coexisting liquid droplets and ice crystals are frequent but they are still not well understood and often misrepresented in numerical models. We analyze the temperature, the optical properties of clouds, and the size of droplets and ice crystals from 12 years of satellite observations over the Southern Ocean. We find that clouds with large droplets are more likely to undergo glaciation than clouds with small droplets and that at temperatures higher than −8 °C the glaciation is probably associated with a higher concentration of ice crystals. We also analyze how liquid and ice are spatially distributed within clouds and we highlight that multiple ice pockets are formed when clouds glaciate rather than spreading from one ice pocket to the entire cloud. A better understanding of clouds allows a better representation of their interaction with the environment and therefore their impact on the climate. Clouds precipitate more easily if they consist of ice crystals, potentially reducing the lifetime of clouds and impacting the radiation balance at the surface and top of the atmosphere. Also, the spatial distribution of ice and liquid in clouds impacts how ice crystals and liquid droplets interact with each other. Key Points: The cloud top layer within individual cloud objects frequently consists of both liquid and ice pixelsLarge cloud droplets are associated with high ice‐cloud fraction and high ice optical thicknessFor ice fraction lower than 0.5, the ice fraction increases with an increase in the ice pixel pocket concentration [ABSTRACT FROM AUTHOR]

Climate models exhibit major radiative biases over the Southern Ocean owing to a poor representation of mixed‐phase clouds. This study uses the remote‐sensing dataset from the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean (MARCUS) campaign to assess the ability of the Weather Research and Forecasting (WRF) model to reproduce frontal clouds off Antarctica. It focuses on the modeling of thin mid‐level supercooled liquid water layers which precipitate ice. The standard version of WRF produces almost fully glaciated clouds and cannot reproduce cloud top turbulence. Our work demonstrates the importance of adapting the ice nucleation parameterization to the pristine austral atmosphere to reproduce the supercooled liquid layers. Once simulated, droplets significantly impact the cloud radiative effect by increasing downwelling longwave fluxes and decreasing downwelling shortwave fluxes at the surface. The net radiative effect is a warming of snow and ice covered surfaces and a cooling of the ocean. Despite improvements in our simulations, the local turbulent circulation related to cloud‐top radiative cooling is not properly reproduced, advocating for the need to develop a parameterization for top‐down convection to capture the turbulence‐microphysics interplay at cloud top. Plain Language Summary: Among the major shortcomings of climate models is a poor representation of clouds over the Southern Ocean. Thanks to new measurements from the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean campaign that took place aboard the Aurora Australia ice breaker, we can now better assess the ability of models to represent clouds off Antarctica. In particular, we focus here on clouds that are mostly composed of ice crystals but that are topped by a thin layer of so‐called "supercooled" liquid droplets that form at temperatures below zero Celsius. While the standard version of the model produces clouds composed only of ice, we show that by adapting the formulation of ice crystal formation to the very pristine atmospheric conditions peculiar to the Southern Ocean it is possible to successfully reproduce thin layers of supercooled liquid droplets observed in mixed‐phase clouds. The latter significantly changes how much sunlight these clouds reflect to space, which is critical to understanding the climate. Compared to ice crystals, liquid droplets tend to reflect more solar energy toward space and at the same time, they enhance the cloud infrared emission toward the surface of the Antarctic ice sheet. Key Points: Weather Research and Forecasting‐observation comparison during Measurements of Aerosols, Radiation and Clouds over the Southern Ocean shows the inability of the model in standard configurations to simulate austral mixed‐phase cloudsA parameterization of ice nucleation based on new ice nucleating particle measurements improves the simulation of supercooled liquid water near cloud topFurther parameterization developments targeting the convection at cloud top are needed to reproduce the turbulence‐microphysics interplay [ABSTRACT FROM AUTHOR]

Abstract The cloud parameterizations of the LMDZ6A climate model (the atmospheric component of the IPSL‐CM6 Earth system model) are entirely described, and the global cloud distribution and cloud radiative effects are evaluated against the CALIPSO‐CloudSat and CERES observations. The cloud parameterizations in recent versions of LMDZ favor an object‐oriented approach for convection, with two distinct parameterizations for shallow and deep convection and a coupling between convection and cloud description through the specification of the subgrid‐scale distribution of water. Compared to the previous version of the model (LMDZ5A), LMDZ6A better represents the low‐level cloud distribution in the tropical belt, and low‐level cloud reflectance and cover are closer to the PARASOL and CALIPSO‐GOCCP observations. Mid‐level clouds, which were mostly missing in LMDZ5A, are now better represented globally. The distribution of cloud liquid and ice in mixed‐phase clouds is also in better agreement with the observations. Among identified deficiencies, low‐level cloud covers are too high in mid‐latitude to high‐latitude regions, and high‐level cloud covers are biased low globally. However, the cloud global distribution is significantly improved, and progress has been made in the tuning of the model, resulting in a radiative balance in close agreement with the CERES observations. Improved tuning also revealed structural biases in LMDZ6A, which are currently being addressed through a series of new physical and radiative parameterizations for the next version of LMDZ.

One of the largest uncertainties in numerical weather prediction and climate models is the representation of mixed‐phase clouds. With the aim of understanding how the supercooled liquid fraction (SLF) in clouds with temperature from −40°C to 0°C is related to temperature, geographical location, and cloud type, our analysis contains a comparison of four satellite‐based datasets (one derived from active and three from passive satellite sensors), and focuses on SLF distribution near‐globally, but also stratified by latitude and continental/maritime regions. Despite the warm bias in cloud top temperature of the passive sensor compared to the active sensor and the phase mismatch in collocated data, all datasets indicate, at the same height‐level, an increase of SLF with cloud optical thickness, and generally larger SLF in the Southern Hemisphere than in the Northern Hemisphere (up to about 20% difference), with the exception of continental low‐level clouds, for which the opposite is true. Plain Language Summary: In mixed‐phase clouds, hydrometeors consisting of ice and supercooled liquid water (i.e., water below 0°C) can exist simultaneously. In the mixed‐phase temperature range (−40°C to 0°C), ice‐nucleating particles (e.g., mineral dusts, biological aerosol particles) are needed for glaciation to be possible. The partitioning into liquid and ice depends not only on the ice‐nucleating particles, but also, for example, on cloud dynamics and ice multiplication processes, influencing in turn the lifetime and the precipitation type of these clouds, and the Earth‐atmosphere energy balance locally and globally. In this study, we show ice and liquid partitioning for different cloud types, comparing four satellite‐based datasets. This allows us to identify robustly their common trends despite their differences. Our results show on average less ice in the Northern than in the Southern Hemisphere when considering all clouds together, and that the larger the cloud optical thickness, the less ice when treating the cloud types separately. The partitioning of cloud types over sea and over land in both hemispheres show less ice in the Southern than in the Northern Hemisphere for high‐level and mid‐level clouds, but the opposite for low‐level clouds over land. This might be due to differences in aerosol composition and distribution. Key Points: Despite phase and temperature mismatches, the retrievals based on passive and active satellite sensors qualitatively agree on the followingSupercooled liquid fraction is larger in the Southern Hemisphere than in the Northern Hemisphere, except for continental low‐level cloudsIn clouds with temperatures from −40°C to 0°C at the same height‐level, supercooled liquid fraction increases with cloud optical thickness [ABSTRACT FROM AUTHOR]

Airborne mineral dust influences cloud occurrence and optical properties, which may provide a pathway for recent and future changes in dust concentration to alter the temperature at Earth's surface. However, despite prior suggestions that dust‐cloud interactions are an important control on the Earth's radiation balance, we find global mean cloud radiative effects to be insensitive to widespread dust changes. Here we simulate uniformly applied shifts in dust amount in a present‐day atmosphere using a version of the CAM5 atmosphere model (within CESM v1.2.2) modified to incorporate laboratory‐based ice nucleation parameterizations in stratiform clouds. Increasing and decreasing dustiness from current levels to paleoclimate extremes caused effective radiative forcings through clouds of +0.02 ± 0.01 and −0.05 ± 0.02 W/m2, respectively, with ranges of −0.26 to +0.13 W/m2 and −0.21 to +0.39 W/m2 from sensitivity tests. Our simulations suggest that these forcings are limited by several factors. Longwave and shortwave impacts largely cancel, particularly in mixed‐phase clouds, while in warm and cirrus clouds opposite responses between regions further reduce each global forcing. Additionally, changes in dustiness cause opposite forcings through aerosol indirect effects in mixed‐phase clouds as in cirrus, while in warm clouds indirect effects are weak at nearly all locations. Nevertheless, regional forcings and global impacts on longwave and shortwave radiation were found to be nonnegligible, suggesting that cloud‐mediated dust effects have significance in simulations of present and future climate. Plain Language Summary: Airborne desert dust can affect the ability of clouds to cool or warm Earth's surface and atmosphere. Past and future changes in dust amount are thought to influence the Earth's climate through dust's interactions with clouds, though the global‐scale importance of this effect is uncertain. Here we simulate changes in dust amount using the CESM v1.2.2 global climate model with modifications to represent dust impacts on ice crystal formation in line with observations. Simulations show that widespread dust changes have a limited impact on Earth's energy balance through dust‐cloud interactions. These impacts largely cancel from region‐to‐region and between different wavelengths of light. However, moderate regional impacts demonstrate that cloud responses to dust changes may be important for shaping present and future climate. Key Points: Dust emissions were found to influence ice crystal density in cirrus and mixed‐phase clouds, with smaller impacts on other cloud propertiesLarge changes in dust emissions did not strongly affect Earth's global radiative balance through semidirect or indirect effectsDust indirect and semidirect effects vary in sign between regions while indirect effect longwave and shortwave components largely cancel [ABSTRACT FROM AUTHOR]

Clouds containing supercooled water are important for both climate and weather, but our knowledge of which aerosol particle types nucleate ice in these clouds is far from complete. Combustion aerosols have strong anthropogenic sources, and if these aerosol types were to nucleate ice in clouds, they might exert a climate forcing. Here, we quantified the atmospheric ice‐nucleating particle (INP) concentrations during the United Kingdom's annual Bonfire Night celebrations, which are characterized by large amounts of combustion aerosol from bonfires and fireworks. We used three immersion mode techniques covering more than 6 orders of magnitude in INP concentration over the temperature range from −10°C to homogeneous freezing. We found no observable systematic change in the INP concentration on three separate nights, despite more than a factor of 10 increase in aerosol number concentrations, up to a factor of 10 increase in PM10 concentration, and more than a factor of 100 increase in black carbon (BC) mass concentration relative to pre‐event levels. This implies that BC and other combustion aerosol such as ash did not compete with the INPs present in the background air. Furthermore, the upper limit of the ice‐active site surface density, ns(T), of BC generated in these events was shown to be consistent with several other recent laboratory studies, showing a very low ice‐nucleating activity of BC. We conclude that combustion aerosol particles similar to those emitted on Bonfire Night are at most of secondary importance for the INP population relevant for mixed‐phase clouds in typical midlatitude terrestrial locations. Plain Language Summary: Liquid water droplets found in clouds can cool to well below 0°C while remaining in the liquid phase (this is known as supercooling). These supercooled droplets can remain liquid down to below around −33°C without freezing, unless there is a certain type of aerosol particle present: an ice‐nucleating particle (INP). Hence, INPs have the potential to drastically change the properties and lifetime of clouds, but the sources of INP in the atmosphere are poorly defined. In this study we measured the INP concentration before, during, and after a major combustion aerosol event in the United Kingdom, Bonfire Night. This celebration is characterized by bonfires (primarily made of waste wood, but also containing garden and household waste) and fireworks. We found that aerosol particles emitted during the celebration are not as effective at nucleating ice as aerosol particle already present in the atmosphere. We conclude that aerosol particles emitted from combustion processes such as those observed on Bonfire Night are not an important source of INPs. Key Points: Ice‐nucleating particle concentrations were unaffected by high aerosol loading during Bonfire Night celebrationsAerosol concentrations rose by up to a factor of 10 and black carbon by up to a factor of 100 during these bonfire and firework eventsOur limiting active site density for Bonfire Night black carbon is consistent with other recent work with low ice‐nucleating activities [ABSTRACT FROM AUTHOR]

As Arctic sea ice cover diminishes, sea spray aerosols (SSA) have a larger potential to be emitted into the Arctic atmosphere. Emitted SSA can contain organic material, but how it affects the ability of particles to act as cloud condensation nuclei (CCN) is still not well understood. Here we measure the CCN‐derived hygroscopicity of three different types of aerosol particles: (1) Sea salt aerosols made from artificial seawater, (2) aerosol generated from artificial seawater spiked with diatom species cultured in the laboratory, and (3) aerosols made from samples of sea surface microlayer (SML) collected during field campaigns in the North Atlantic and Arctic Ocean. Samples are aerosolized using a sea spray simulation tank (plunging jet) or an atomizer. We show that SSA containing diatom and microlayer exhibit similar CCN activity to inorganic sea salt with a κ value of ∼1.0. Large‐eddy simulation (LES) is then used to evaluate the general role of aerosol hygroscopicity in governing mixed‐phase low‐level cloud properties in the high Arctic. For accumulation mode aerosol, the simulated mixed‐phase cloud properties do not depend strongly on κ, unless the values are lower than 0.4. For Aitken mode aerosol, the hygroscopicity is more important; the particles can sustain the cloud if the hygroscopicity is equal to or higher than 0.4, but not otherwise. The experimental and model results combined suggest that the internal mixing of biogenic organic components in SSA does not have a substantial impact on the cloud droplet activation process and the cloud lifetime in Arctic mixed‐phase clouds. Key Points: CCN activity of aerosolized Arctic sea surface microlayer and diatom cultures is similar to sea saltFor accumulation mode aerosols, the simulated cloud properties do not depend strongly on κ unless κ is <0.4Aitken mode aerosols can sustain the simulated Arctic cloud, but only if κ is high, in this specific case ≥0.4 [ABSTRACT FROM AUTHOR]

Large‐eddy simulations (LESs) that explicitly resolve boundary layer (BL) turbulence and clouds are used to explore the sensitivity of idealized Arctic BL clouds to climate perturbations. The LESs focus on conditions resembling springtime, when surface heat fluxes over sea ice are weak, and the cloud radiative effect is dominated by the long‐wave effect. In the LES, the condensed water path increases with BL temperature and free‐tropospheric relative humidity, but it decreases with inversion strength. The dependencies of cloud properties on environmental variables exhibited by the LES can largely be reproduced by a mixed‐layer model. Mixed‐layer model analysis shows that the liquid water path increases with warming because the liquid water gradient increase under warming overcompensates for geometric cloud thinning. This response contrasts with the response of subtropical stratocumulus to warming, whose liquid water path decreases as the clouds thin geometrically under warming. The results suggest that methods used to explain the response of lower‐latitude BL clouds to climate change can also elucidate changes in idealized Arctic BL clouds, although subtropical and Arctic clouds occupy different thermodynamic regimes. [ABSTRACT FROM AUTHOR]

The cloud parameterizations of the LMDZ6A climate model (the atmospheric component of the IPSL‐CM6 Earth system model) are entirely described, and the global cloud distribution and cloud radiative effects are evaluated against the CALIPSO‐CloudSat and CERES observations. The cloud parameterizations in recent versions of LMDZ favor an object‐oriented approach for convection, with two distinct parameterizations for shallow and deep convection and a coupling between convection and cloud description through the specification of the subgrid‐scale distribution of water. Compared to the previous version of the model (LMDZ5A), LMDZ6A better represents the low‐level cloud distribution in the tropical belt, and low‐level cloud reflectance and cover are closer to the PARASOL and CALIPSO‐GOCCP observations. Mid‐level clouds, which were mostly missing in LMDZ5A, are now better represented globally. The distribution of cloud liquid and ice in mixed‐phase clouds is also in better agreement with the observations. Among identified deficiencies, low‐level cloud covers are too high in mid‐latitude to high‐latitude regions, and high‐level cloud covers are biased low globally. However, the cloud global distribution is significantly improved, and progress has been made in the tuning of the model, resulting in a radiative balance in close agreement with the CERES observations. Improved tuning also revealed structural biases in LMDZ6A, which are currently being addressed through a series of new physical and radiative parameterizations for the next version of LMDZ. Plain Language Summary: This paper describes the representation of clouds in the latest version of LMDZ, which is a French atmospheric model used for climate change projections. Along with other international climate models, it serves as a basis for the IPCC (Intergovernmental Panel on Climate Change) report by contributing to the CMIP project (Climate Model Intercomparison Project). Clouds are especially important in the climate system because they reflect a lot of sunlight and also absorb and emit a lot of infrared radiation. They can either amplify or reduce the current global warming depending on their change in opacity, altitude, and detailed properties. It is therefore essential to represent them accurately in climate models. The main physical equations used to compute cloud properties in LMDZ are introduced, and the model results are compared to various satellite observations. It reveals that low‐level and mid‐level clouds are in better agreement with the observations than before but that high‐level clouds remain difficult to simulate realistically. Ongoing developments aimed at solving these remaining deficiencies are finally described. Key Points: Cloud parameterizations of the LMDZ6A climate model are entirely describedLow‐level and mid‐level cloud distribution and radiative effects are improved compared to LMDZ5ALMDZ6A is better tuned than LMDZ5A, and knowledge of its structural deficiencies has been gained [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosol plays an important role in the Earth's climate system because it absorbs solar radiation and therefore potentially warms the climate; however, BC can also act as a seed for cloud particles, which may offset much of its warming potential. If BC acts as an ice nucleating particle (INP), BC could affect the lifetime, albedo, and radiative properties of clouds containing both supercooled liquid water droplets and ice particles (mixedphase clouds). Over 40% of global BC emissions are from biomass burning; however, the ability of biomass burning BC to act as an INP in mixed-phase cloud conditions is almost entirely unconstrained. To provide these observational constraints, we measured the contribution of BC to INP concentrations ([INP]) in real-world prescribed burns and wildfires. We found that BC contributes, at most, 10% to [INP] during these burns. From this, we developed a parameterization for biomass burning BC and combined it with a BC parameterization previously used for fossil fuel emissions. Applying these parameterizations to global model output, we find that the contribution of BC to potential [INP] relevant to mixed-phase clouds is ~5% on a global average. [ABSTRACT FROM AUTHOR]

Abundant mixed-phase clouds exist over the Arctic and the Tibetan Plateau. Salient differences in their seasonal cycle and in their vertical structure and cloud radiative effects (CREs, which includes shortwave CRE, longwave CRE and net CRE) imply different influences on the climate system. The maximum incidence of mixed-phase clouds appears during the late spring and early winter over the Arctic Ocean, but it appears during the summer over the Tibetan Plateau. The surface mixed-phase-cloud-induced CRE exerts a strong warming effect over the Arctic during the cold season (from September to May), in contrast to the strong cooling effect over the Tibetan Plateau during the summer. The existence of temperature inversion over the Arctic Ocean confines the mixed-phase clouds and associated cloud hydrometeors and vertical radiative heating profile at the near surface, while over the Tibetan Plateau there is no such a temperature inversion, and hence the cloud-induced atmospheric heating profile exhibits both larger vertical contrast and more seasonal variation over the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The representation of mixed-phase cloud optical properties in models is a critical problem in cloud modeling studies. Ice and liquid water co-existing in a cloud layer result in significantly different cloud optical properties from those of liquid water and ice clouds. However, it is not clear as to how mixed-phase cloud optical properties are affected by various microphysical factors, including the effective particle size, ice volume fraction, and ice particle shape. In this paper, the optical properties (extinction efficiency, scattering efficiency, single scattering albedo, and asymmetry factor) of mixed-phase cloud were calculated assuming externally and internally mixed cloud particle models in a broad spectral range of 0.2–100 μm at various effective particle diameters and ice volume fraction conditions. The influences of various microphysical factors on optical properties were comprehensively examined. For the externally mixed cloud particles, the shapes of ice crystals were found to become more important as the ice volume fraction increases. Compared with the mixed-phase cloud with larger effective diameter, the shape of ice crystals has a greater impact on the optical properties of the mixed-phase cloud with a smaller effective diameter (