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Abstract. Aerosols affect cirrus formation and evolution, yet quantificationof these effects remain difficult based on in situ observations due to thecomplexity of nucleation mechanisms and large variabilities in icemicrophysical properties. This work employed a method to distinguish fiveevolution phases of cirrus clouds based on in situ aircraft-basedobservations from seven U.S. National Science Foundation (NSF) and five NASAflight campaigns. Both homogeneous and heterogeneous nucleation werecaptured in the 1 Hz aircraft observations, inferred from the distributionsof relative humidity in the nucleation phase. Using linear regressions toquantify the correlations between cirrus microphysical properties andaerosol number concentrations, we found that ice water content (IWC) and icecrystal number concentration (Ni) show strong positive correlations withlarger aerosols (>500 nm) in the nucleation phase, indicatingstrong contributions of heterogeneous nucleation when ice crystals firststart to nucleate. For the later growth phase, IWC and Ni show similarpositive correlations with larger and smaller (i.e., >100 nm)aerosols, possibly due to fewer remaining ice-nucleating particles in thelater growth phase that allows more homogeneous nucleation to occur. Both200 m and 100 km observations were compared with the nudged simulations fromthe National Center for Atmospheric Research (NCAR) Community AtmosphereModel version 6 (CAM6). Simulated aerosol indirect effects are weaker thanthe observations for both larger and smaller aerosols for in situ cirrus,while the simulated aerosol indirect effects are closer to observations inconvective cirrus. The results also indicate that simulations overestimatehomogeneous freezing, underestimate heterogeneous nucleation andunderestimate the continuous formation and growth of ice crystals as cirrusclouds evolve. Observations show positive correlations of IWC, Ni and icecrystal mean diameter (Di) with respect to Na in both the Northern and SouthernHemisphere (NH and SH), while the simulations show negative correlations inthe SH. The observations also show higher increases of IWC and Ni in the SHunder the same increase of Na than those shown in the NH, indicating highersensitivity of cirrus microphysical properties to increases of Na in the SHthan the NH. The simulations underestimate IWC by a factor of 3–30 in theearly/later growth phase, indicating that the low bias of simulated IWC wasdue to insufficient continuous ice particle formation and growth. Sucha hypothesis is consistent with the model biases of lower frequencies of icesupersaturation and lower vertical velocity standard deviation in theearly/later growth phases. Overall, these findings show that aircraftobservations can capture both heterogeneous and homogeneous nucleation, andtheir contributions vary as cirrus clouds evolve. Future model developmentis also recommended to evaluate and improve the representation of watervapor and vertical velocity on the sub-grid scale to resolve theinsufficient ice particle formation and growth after the initial nucleationevent. 

Aerosols affect cirrus formation and evolution, yet quantification of these effects remain difficult based on in-situ observations due to the complexity of nucleation mechanisms and large variabilities in ice microphysical properties. This work employed a method to distinguish five evolution phases of cirrus clouds based on in-situ aircraft-based observations from seven U.S. National Science Foundation (NSF) and five NASA flight campaigns. Both homogeneous and heterogeneous nucleation were captured in the 1-Hz aircraft observations, inferred from the distributions of relative humidity in the nucleation phase. Using linear regressions to quantify the correlations between cirrus microphysical properties and aerosol number concentrations, we found that ice water content (IWC) and ice crystal number concentration (Ni) show strong positive correlations with larger aerosols (> 500 nm) in the nucleation phase, indicating strong contributions of heterogeneous nucleation when ice crystals first start to nucleate. For the later growth phase, IWC and Ni show similar positive correlations with larger and smaller (i.e., > 100 nm) aerosols, possibly due to fewer remaining ice nucleating particles in the later growth phase that allows more homogeneous nucleation to occur. Both 200-m and 100-km observations were compared with the nudged simulations from the National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 6 (CAM6). Simulated aerosol indirect effects are weaker than the observations for both larger and smaller aerosols. Observations show stronger aerosol indirect effects (i.e., positive correlations between IWC, Ni and Na) in the Southern Hemisphere (SH) compared with the Northern Hemisphere (NH), while the simulations show negative correlations in the SH. The simulations underestimate IWC by a factor of 3 – 30 in the early/later growth phase, indicating that the low bias of simulated IWC was due to insufficient ice particle growth. Such hypothesis is consistent with the model biases of lower frequencies of ice supersaturation and lower vertical velocity standard deviation in the early/later growth phases. Overall, these findings show that aircraft observations can capture the competitions between heterogeneous and homogeneous nucleation, and their contributions vary as cirrus clouds evolve. Future model development is also recommended to evaluate and improve the representation of water vapor and vertical velocity on the sub-grid scale to resolve the insufficient ice particle growth. 

Abstract. Cirrus cloud radiative effects are largely affected byice microphysical properties, including ice water content (IWC), ice crystalnumber concentration (Ni) and mean diameter (Di). These characteristics varysignificantly due to thermodynamic, dynamical and aerosol conditions. Inthis work, a global-scale observation dataset is used to examine regionalvariations of cirrus cloud microphysical properties, as well as several keycontrolling factors, i.e., temperature, relative humidity with respect toice (RHi), vertical velocity (w) and aerosol number concentrations (Na).Results are compared with simulations from the National Center forAtmospheric Research (NCAR) Community Atmosphere Model version 6 (CAM6).Observed and simulated ice mass and number concentrations are constrained to≥62.5 µm to reduce potential uncertainty from shattered ice indata collection. The differences between simulations and observations arefound to vary with latitude and temperature. Comparing with averagedobservations at ∼100 km horizontal scale, simulations arefound to underestimate (overestimate) IWC by a factor of 3–10 in theNorthern (Southern) Hemisphere. Simulated Ni is overestimated in mostregions except the Northern Hemisphere midlatitudes. Simulated Di isunderestimated by a factor of 2, especially for warmer conditions(−50 to −40 ∘C), possibly due tomisrepresentation of ice particle growth/sedimentation. For RHi effects, thefrequency and magnitude of ice supersaturation are underestimated insimulations for clear-sky conditions. The simulated IWC and Ni show bimodaldistributions with maximum values at 100 % and 80 % RHi, differing fromthe unimodal distributions that peak at 100 % in the observations. For weffects, both observations and simulations show variances of w (σw) decreasing from the tropics to polar regions, but simulations show muchhigher σw for the in-cloud condition than the clear-sky condition.Compared with observations, simulations show weaker aerosol indirect effectswith a smaller increase of IWC and Di at higher Na. These findings provide anobservation-based guideline for improving simulated ice microphysicalproperties and their relationships with key controlling factors at variousgeographical locations. 

Abstract. Mixed-phase Southern Ocean clouds are challenging to simulate, and theirrepresentation in climate models is an important control on climatesensitivity. In particular, the amount of supercooled water and frozen massthat they contain in the present climate is a predictor of their planetaryfeedback in a warming climate. The recent Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) vastly increased theamount of in situ data available from mixed-phase Southern Ocean clouds usefulfor model evaluation. Bulk measurements distinguishing liquid and ice watercontent are not available from SOCRATES, so single-particle phaseclassifications from the Two-Dimensional Stereo (2D-S) probe are invaluablefor quantifying mixed-phase cloud properties. Motivated by the presence oflarge biases in existing phase discrimination algorithms, we develop a noveltechnique for single-particle phase classification of binary 2D-S images usinga random forest algorithm, which we refer to as the University of WashingtonIce–Liquid Discriminator (UWILD). UWILD uses 14 parameters computed frombinary image data, as well as particle inter-arrival time, to predict phase.We use liquid-only and ice-dominated time periods within the SOCRATES datasetas training and testing data. This novel approach to model training avoidsmajor pitfalls associated with using manually labeled data, including reducedmodel generalizability and high labor costs. We find that UWILD is wellcalibrated and has an overall accuracy of 95 % compared to72 % and 79 % for two existing phase classificationalgorithms that we compare it with. UWILD improves classifications of smallice crystals and large liquid drops in particular and has more flexibilitythan the other algorithms to identify both liquid-dominated and ice-dominatedregions within the SOCRATES dataset. UWILD misclassifies a small percentageof large liquid drops as ice. Such misclassified particles are typicallyassociated with model confidence below 75 % and can easily befiltered out of the dataset. UWILD phase classifications show that particleswith area-equivalent diameter (Deq)  < 0.17 mm are mostlyliquid at all temperatures sampled, down to −40 ∘C. Largerparticles (Deq>0.17 mm) are predominantly frozen at alltemperatures below 0 ∘C. Between 0 and 5 ∘C,there are roughly equal numbers of frozen and liquid mid-sized particles (0.170.33 mm) are mostly frozen. We also use UWILD's phaseclassifications to estimate sub-1 Hz phase heterogeneity, and we showexamples of meter-scale cloud phase heterogeneity in the SOCRATES dataset. 

Cirrus cloud radiative effects are largely affected by ice microphysical properties, including ice water content (IWC), ice crystal number concentration (Ni) and mean diameter (Di). These characteristics vary significantly due to thermodynamic, dynamical and aerosol conditions. In this work, a global-scale observation dataset is used to examine regional variations of cirrus cloud microphysical properties, as well as several key controlling factors, i.e., temperature, relative humidity with respect to ice (RHi), vertical velocity (w), and aerosol number concentrations (Na). Results are compared with simulations from the National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 6 (CAM6). The differences between simulations and observations are found to vary with latitude and temperature. Specifically, simulations are found to underestimate IWC by a factor of 5–30 in all regions. Simulated Ni is overestimated in most regions except Northern Hemisphere midlatitude and polar regions. Simulated Di is underestimated, especially for warmer conditions (−50 °C to −40 °C) and higher Na, possibly due to less effective ice particle growth/sedimentation and weaker aerosol indirect effects, respectively. For RHi effects, the frequency and magnitude of ice supersaturation is underestimated in simulations for clear-sky conditions, and the simulated IWC and Ni show maximum values at 80 % RHi instead of 110 % as observed. For w effects, both observations and simulations show variances of w (σw) decreasing from tropics to polar regions, but simulations show much higher σw for in-cloud condition than clear-sky condition. These findings provide an observation-based guideline for improving simulated ice microphysical properties and their relationships with key controlling factors at various geographical locations. 

Single‐ and multi‐layer clouds are commonly observed over the Southern Ocean in varying synoptic settings, yet few studies have characterized and contrasted their properties. This study provides a statistical analysis of the microphysical properties of single‐ and multi‐layer clouds using in‐situ observations acquired during the Southern Ocean Cloud‐Radiation Aerosol Transport Experimental Study. The relative frequencies of ice‐containing samples (i.e., mixed and ice phase) for multi‐layer clouds are 0.05–0.25 greater than for single‐layer clouds, depending on cloud layer height. In multi‐layer clouds, the lowest cloud layers have the highest ice‐containing sample frequencies, which decrease with increasing cloud layer height up to the third highest cloud layer. This suggests a prominent seeder‐feeder mechanism over the region. Ice nucleating particle (cloud condensation nuclei) concentrations are positively (negatively) correlated with ice‐containing sample frequencies in select cases. Differences in microphysical properties are observed for single‐ and multi‐layer clouds. Drop concentrations (size distributions) are greater (narrower) for single‐layer clouds compared with the lowest multi‐layer clouds. When differentiating cloud layers by top (single‐ and highest multi‐layer clouds) and non‐top layers (underlying multi‐layer clouds), total particle size distributions (including liquid and ice) are similarly broader for non‐top cloud layers. Additionally, drop concentrations in coupled environments are approximately double those in decoupled environments.

 

Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new‐generation GCMs predict too much liquid and too little ice in mixed‐phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparison with observational data obtained during the Southern Ocean Cloud Radiation and Aerosol Transport Experimental Study, this study addresses a key uncertainty in the Community Earth System Model version 2 (CESM2) related to cloud phase, namely ice formation in pristine remote SO clouds. It is found that sea spray organic aerosols (SSOAs) are the most important type of ice nucleating particles (INPs) over the SO with concentrations 1 order of magnitude higher than those of dust INPs based on measurements and CESM2 simulations. Secondary ice production (SIP) which includes riming splintering, rain droplet shattering, and ice‐ice collisional fragmentation as implemented in CESM2 is the dominant ice production process in moderately cold clouds with cloud temperatures greater than −20°C. SIP enhances the in‐cloud ice number concentrations (Ni) by 1–3 orders of magnitude and predicts more mixed‐phase (with percentage occurrence increased from 15% to 21%), in better agreement with the observations. This study highlights the importance of accurately representing the cloud phase over the pristine remote SO by considering the ice nucleation of SSOA and SIP processes, which are currently missing in most GCM cloud microphysics parameterizations.

 

A comparative analysis between observational data from McMurdo Station, Antarctica and the Community Atmosphere Model version 6 (CAM6) simulation is performed focusing on cloud characteristics and their thermodynamic conditions. Ka‐band Zenith Radar (KAZR) and High Spectral Resolution Lidar (HSRL) retrievals are used as the basis of cloud fraction and cloud phase identifications. Radiosondes released at 12‐h increments provide atmospheric profiles for evaluating the simulated thermodynamic conditions. Our findings show that the CAM6 simulation consistently overestimates (underestimates) cloud fraction above (below) 3 km in four seasons of a year. Normalized by total in‐cloud samples, ice and mixed phase occurrence frequencies are underestimated and liquid phase frequency is overestimated by the model at cloud fractions above 0.6, while at cloud fractions below 0.6 ice phase frequency is overestimated and liquid‐containing phase frequency is underestimated by the model. The cloud fraction biases are closely associated with concurrent biases in relative humidity (RH), that is, high (low) RH biases above (below) 2 km. Frequencies of correctly simulating ice and liquid‐containing phase increase when the absolute biases of RH decrease. Cloud fraction biases also show a positive correlation with RH biases. Water vapor mixing ratio biases are the primary contributor to RH biases, and hence, likely a key factor controlling the cloud biases. This diagnosis of the evident shortfalls of representations of cloud characteristics in CAM6 simulation at McMurdo Station brings new insight in improving the governing model physics therein.