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DOE OSTI2021

Turbulence in The Marine Boundary Layer and Air Motions Below Stratocumulus Clouds at the ARM Eastern North Atlantic Site

Marine stratocumulus clouds are intimately coupled to the turbulence in the boundary layer and drizzle is known to be ubiquitous within them. Six years of data collected at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic site are utilized to characterize turbulence in the marine boundary layer and air motions below stratocumulus clouds. Profiles of variance of vertical velocity binned by wind direction (wdir) yielded that the boundary layer measurements are affected by the island when the wdir is between 90° and 310° (measured clockwise from North where air is coming from). Data collected during the marine conditions (wdir<90 or wdir>310) showed that the variance of vertical velocity was higher during the winter months than during the summer months due to higher cloudiness, wind speeds, and surface fluxes. Furthermore, during marine conditions the variance of vertical velocity and cloud fraction exhibited a distinct diurnal cycle with higher values during the nighttime than during the daytime. Detailed analysis of 32 cases of drizzling marine stratocumulus clouds showed that for a similar amount of radiative cooling at the cloud top, within the sub-cloud layer 1) drizzle increasingly falls within downdrafts with increasing rain rates, 2) the strength of the downdrafts increases with increasing rain rates, and 3) the correlation between vertical air motion and rain rate is highest in the middle of the sub-cloud layer. The results presented herein have implications for climatological and model evaluation studies conducted at the ENA site, along with efforts of accurately representing drizzle-turbulence interactions in a range of atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Constraining microphysical processes of warm rain formulation using advanced spectral separations, an ensemble retrieval framework and machine learning techniques

Drizzle, a common feature of marine boundary layer clouds formed through collision coalescence, plays a key role in cloud microphysics and evolution. Yet, simultaneously retrieving cloud and drizzle properties from remote-sensing observations remains challenging because drizzle droplets often dominate radar signals, masking cloud contributions. The goal of the proposed research is to provide constraints for the process of autoconversion and accretion using ARM cloud measurements. Specifically, we provide concurrent retrievals of cloud and drizzle that allows users to derive corresponding autoconversion and accretion rates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

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

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

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Evidence for Natural Variability in Marine Stratocumulus Cloud Properties Due to Cloud-Aerosol

In this study, aircraft observations from the Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter are used to characterize the variability in drizzle, cloud, and aerosol properties associated with cloud rifts and the surrounding solid clouds observed off the coast of California. A flight made on 16 July 1999 provided measurements directly across an interface between solid and rift cloud conditions. Aircraft instrumentation allowed for measurements of aerosol, cloud droplet, and drizzle spectra. CCN concentrations were measured in addition to standard thermodynamic variables and the winds. A Forward Scatter Spectrometer Probe (FSSP) measured size distribution of cloud-sized droplets. A Cloud Imaging Probe (CIP) was used to measure distributions of drizzle-sized droplets. Aerosol distributions were obtained from a Cloud Aerosol Scatterprobe (CAS). The CAS probe measured aerosols, cloud droplets and drizzle-sized drops; for this study. The CAS probe was used to measure aerosols in the size range of 0.5 micron - 1 micron. Smaller aerosols were characterized using an Ultrafine Condensation Particle Counter (CPC) sensor. The CPC was used to measure particles with diameters greater than 0.003 micron. By subtracting different count concentrations measured with the CPC, this probe was capable of identifying ultrafine particles those falling in the size range of 3 nanometers - 7 nanometers that are believed to be associated with new particle production.

Albrecht, Bruce↗

NASA NTRS2021

Inference of Precipitation in Warm Stratiform Clouds using Remotely Sensed Observations of the Cloud Top Droplet Size Distribution

Drizzle is a common feature of warm stratiform clouds and it influences their radiative effects by modulating their physical properties and lifecycle. An important component of drizzle formation are processes that lead to a broadening of the droplet size distribution (DSD). Here, we examine observations of cloud and drizzle properties retrieved using colocated airborne measurements from the Research Scanning Polarimeter and the Third Generation Airborne Precipitation Radar. We observe a bimodal DSD as the aircraft transects drizzling open-cells whereby the larger mode reaches a maximum size near cloud center and the smaller mode remains relatively constant in size. We review similarities between our observations with droplet growth processes and their connections with precipitation onset. We estimate droplet sedimentation using the cloud top DSD and find a correlation with rain water path of 0.82. We also examine how changes in liquid water paths and droplet concentrations may act to enhance or suppress precipitation.

Droplet size distribution↗

DOE OSTI2022

Evolution of Droplet Size Distributions During the Transition of an Ultraclean Stratocumulus Cloud System to Open Cell Structure: An LES Investigation Using Lagrangian Microphysics

Here, a state-of-the-art Lagrangian microphysics scheme is used in a large-eddy simulation to investigate the stratocumulus transition from closed to open cell structure. Processes controlling precipitation development, which is a key to the transition, are analyzed by leveraging unique benefits of Lagrangian microphysics, particularly the ability to track computational drops in the flow. Sufficient time is needed for coalescence growth of cloud drops to drizzle within the updraft-downdraft cycle of large eddies. This favors broad drop size distributions (DSDs) and drizzle growth in downdrafts, where drops are typically much older than in updrafts. During the closed cell stage, mean cloud drop radius is too small, and the DSDs are too narrow, so that the timescale for coalescence is much longer than the large eddy turnover time and drizzle growth is limited. The closed-to-open cell transition occurs when these timescales become comparable and the precipitation flux increases sharply.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Near-surface Density Currents Observed in the Southeast Pacific Stratocumulus-topped Marine Boundary Layer

Density currents (i.e. cold pools or outflows) beneath marine stratocumulus clouds are characterized using a 30-d data set of ship-based observations obtained during the 2008 Variability of American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) in the southeast Pacific. An objective method identifies 71 density current fronts using an air density criterion and isolates each density current’s core (peak density) and tail (dissipating) zone. Compared to front and core zones, most density current tails exhibited weaker density gradients and wind anomalies elongated about the axis of the mean wind. The mean cloud-level advection relative to the surface layer wind (1.9 m s-1) nearly matches the mean density current propagation speed (1.8 m s-1). The similarity in speeds allows drizzle cells to deposit tails in their wakes. Based on high-resolution scanning Doppler lidar data, prefrontal updrafts had a mean intensity of 0.91 m s-1, reached an average altitude of 800 m, and were often surmounted by low-lying shelf clouds not connected to the overlying stratocumulus cloud. Nearly 90% of density currents were identified when C-band radar estimated 30-km diameter areal average rain rates exceeded 1 mm d-1. Rather than peaking when rain rates are highest overnight, density current occurrence peaks between 0600 and 0800 local solar time when enhanced local drizzle co-occurs with shallow subcloud dry and stable layers. The dry layers may contribute to density current formation by enhancing subcloud evaporation of drizzle. Density currents preferentially occur in regions of open cells but also occur in regions of closed cells.

density currents↗

DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

DOE OSTI2025

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1958

A Flight Evaluation and Analysis of the Effect of Icing Conditions on the ZPG-2 Airship

A series of test flights was conducted by the U. S. Navy over a 3- year period to evaluate the effects of icing on the operation of the ZPG-2 airship. In supercooled. clouds, ice formed only on the forward edges of small protuberances and wires and presented no serious hazard to operation. Ice accretions of the glaze type which occurred in conditions described as freezing drizzle adversely affected various components to a somewhat greater extent. The results indicated, a need for protection of certain components such as antennas, propellers, and certain parts of the control system. The tests showed that icing of the large surface of the envelope occurred only in freezing rain or drizzle. Because of the infrequent occurrence of these conditions, the potential maximum severity could not be estimated from the test results. The increases in heaviness caused by icing in freezing rain and drizzle were substantial, but well within the operational capabilities of the airship. In order to estimate the potential operational significance of icing in freezing rain, theoretical calculations were used to estimate: (1) the rate of icing as a function of temperature and rainfall intensity, (2) the climatological probability of occurrence of various combinations of these variables, and (3) the significance of the warming influence of the ocean in alleviating freezing-rain conditions. The results of these calculations suggest that, although very heavy icing rates are possible in combinations of low temperature and high rainfall rate, the occurrence of such conditions is very infrequent in coastal areas and virtually impossible 200 or 300 miles offshore.

Lewis, Willilam↗

NASA NTRS1993

Modeling marine boundary-layer clouds with a two-layer model: A one-dimensional simulation

A two-layer model of the marine boundary layer is described. The model is used to simulate both stratocumulus and shallow cumulus clouds in downstream simulations. Over cold sea surfaces, the model predicts a relatively uniform structure in the boundary layer with 90%-100% cloud fraction. Over warm sea surfaces, the model predicts a relatively strong decoupled and conditionally unstable structure with a cloud fraction between 30% and 60%. A strong large-scale divergence considerably limits the height of the boundary layer and decreases relative humidity in the upper part of the cloud layer; thus, a low cloud fraction results. The efffects of drizzle on the boundary-layer structure and cloud fraction are also studied with downstream simulations. It is found that drizzle dries and stabilizes the cloud layer and tends to decouple the cloud from the subcloud layer. Consequently, solid stratocumulus clouds may break up and the cloud fraction may decrease because of drizzle.

Wang, Shouping↗

NASA NTRS2003

Limits to the Indirect Aerosol Forcing in Stratocumulus

The indirect radiative forcing of aerosols is poorly constrained by the observational data underlying the simple cloud parameterizations in GCMs. signal of cloud response to increased aerosol concentrations from meteorological noise. Recent satellite observations indicate a significant decrease of cloud water in ship tracks, in contrast to an ensemble of in situ measurements showing no average change in cloud water relative to the surrounding clouds. Both results contradict the expectation of cloud water increasing in polluted clouds. We find through large-eddy simulations of stratocumulus that the trend in the satellite data is likely an artifact of sampling only overcast clouds. The simulations instead show cloud cover increasing with droplet concentrations. The simulations also show that increases in cloud water from suppressing drizzle by increased droplet concentrations are favored at night or at extremely low droplet concentrations. At typical droplet concentrations we find that the Twomey effect on cloud albedo is amplified very little by the secondary indirect effect of drizzle suppression, largely because the absorption of solar radiation by cloud water reduces boundary-layer mixing in the daytime and thereby restricts any possible increase in cloud water from drizzle suppression. The cloud and boundary layer respond to radiative heating variations on a time scale of hours, and on longer time scales respond to imbalances between large-scale horizontal advection and the entrainment of inversion air. We analyze the co-varying response of cloud water, cloud thickness, width of droplet size distributions, and dispersion of the optical depth, as well as the overall response of cloud albedo, to changes in droplet concentrations. We also dissect the underlying physical mechanisms through sensitivity studies. Ship tracks represent an ideal natural laboratory to extricate the

Ackerman, Andrew↗

NASA NTRS2008

Aerosol and Cloud Microphysical Characteristics of Rifts and Gradients in Maritime Stratocumulus Clouds

A cloud rift is characterized as a large-scale, persistent area of broken, low reflectivity stratocumulus clouds usually surrounded by a solid deck of stratocumulus. A rift observed off the coast of Monterey Bay, California on 16 July 1999 was studied to compare the aerosol and cloud microphysical properties in the rift with those of the surrounding solid stratus deck. Variables measured from an instrumented aircraft included temperature, water vapor, and cloud liquid water. These measurements characterized the thermodynamic properties of the solid deck and rift areas. Microphysical measurements made included aerosol, cloud drop and drizzle drop concentrations and cloud condensation nuclei (CCN) concentrations. The microphysical characteristics in a solid stratus deck differ substantially from those of a broken, cellular rift where cloud droplet concentrations are a factor of 2 lower than those in the solid cloud. Further, CCN concentrations were found to be about 3 times greater in the solid cloud area compared with those in the rift and aerosol concentrations showed a similar difference as well. Although drizzle was observed near cloud top in parts of the solid stratus cloud, the largest drizzle rates were associated with the broken clouds within the rift area. In addition to marked differences in particle concentrations, evidence of a mesoscale circulation near the solid cloud rift boundary is presented. This mesoscale circulation provides a mechanism for maintaining a rift, but further study is required to understand the initiation of a rift and the conditions that may cause it to fill.

Sharon, Tarah M.↗

DOE OSTI2013

Improving Bulk Microphysics Parameterizations in Simulations of Aerosol Effects

To improve the microphysical parameterizations for simulations of the aerosol indirect effect (AIE) in regional and global climate models, a double-moment bulk microphysical scheme presently implemented in the Weather Research and Forecasting (WRF) model is modified and the results are compared against atmospheric observations and simulations produced by a spectral bin microphysical scheme (SBM). Rather than using prescribed aerosols as in the original bulk scheme (Bulk-OR), a prognostic doublemoment aerosol representation is introduced to predict both the aerosol number concentration and mass mixing ratio (Bulk-2M). The impacts of the parameterizations of diffusional growth and autoconversion and the selection of the embryonic raindrop radius on the performance of the bulk microphysical scheme are also evaluated. Sensitivity modeling experiments are performed for two distinct cloud regimes, maritime warm stratocumulus clouds (SC) over southeast Pacific Ocean from the VOCALS project and continental deep convective clouds (DCC) in the southeast of China from the Department of Energy/ARM Mobile Facility (DOE/AMF) - China field campaign. The results from Bulk-2M exhibit a much better agreement in the cloud number concentration and effective droplet radius in both the SC and DCC cases with those from SBM and field measurements than those from Bulk-OR. In the SC case particularly, Bulk-2M reproduces the observed drizzle precipitation, which is largely inhibited in Bulk-OR. Bulk-2M predicts enhanced precipitation and invigorated convection with increased aerosol loading in the DCC case, consistent with the SBM simulation, while Bulk-OR predicts the opposite behaviors. Sensitivity experiments using four different types of autoconversion schemes reveal that the autoconversion parameterization is crucial in determining the raindrop number, mass concentration, and drizzle formation for warm 2 stratocumulus clouds. An embryonic raindrop size of 40 μm is determined as a more realistic setting in the autoconversion parameterization. The saturation adjustment employed in calculating condensation/evaporation in the bulk scheme is identified as the main factor responsible for the large discrepancies in predicting cloud water in the SC case, suggesting that an explicit calculation of diffusion growth with predicted supersaturation is necessary for further improvements of the bulk microphysics scheme. Lastly, a larger rain evaporation rate below cloud is found in the bulk scheme in comparison to the SBM simulation, which could contribute to a lower surface precipitation in the bulk scheme.

aerosol↗

DOE OSTI2011

Examination of turbulent entrainment-mixing mechanisms using a combined approach

Turbulent entrainment-mixing mechanisms are investigated by applying a combined approach to the aircraft measurements of three drizzling and two nondrizzling stratocumulus clouds collected over the U.S. Department of Energy's Atmospheric Radiation Measurement Southern Great Plains site during the March 2000 cloud Intensive Observation Period. Microphysical analysis shows that the inhomogeneous entrainment-mixing process occurs much more frequently than the homogeneous counterpart, and most cases of the inhomogeneous entrainment-mixing process are close to the extreme scenario, having drastically varying cloud droplet concentration but roughly constant volume-mean radius. It is also found that the inhomogeneous entrainment-mixing process can occur both near the cloud top and in the middle level of a cloud, and in both the nondrizzling clouds and nondrizzling legs in the drizzling clouds. A new dimensionless number, the scale number, is introduced as a dynamical measure for different entrainment-mixing processes, with a larger scale number corresponding to a higher degree of homogeneous entrainment mixing. Further empirical analysis shows that the scale number that separates the homogeneous from the inhomogeneous entrainment-mixing process is around 50, and most legs have smaller scale numbers. Thermodynamic analysis shows that sampling average of filament structures finer than the instrumental spatial resolution also contributes to the dominance of inhomogeneous entrainment-mixing mechanism. The combined microphysical-dynamical-thermodynamic analysis sheds new light on developing parameterization of entrainment-mixing processes and their microphysical and radiative effects in large-scale models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Cloud-Scale Droplet Number Sensitivity to Liquid Water Path in Marine Stratocumulus

Cloud droplet number concentration (N c ) is retrieved from remotely observed marine stratocumulus cloud liquid water path (LWP), cloud optical depth (τ c ), and cloud thickness, using an optical model that assumes liquid water content (LWC) increases linearly from cloud base. Assuming that LWC is vertically uniform would underestimate τ c by 5% and N c by 14%. Individual retrievals of N c from 10-min averages vary by orders of magnitude from long-term averages. Surface cloud condensation nuclei (CCN) number concentration N CCN is weakly but significantly correlated with N c (R = 0.3) for the day leading and 6 hr following N c . Consistent with coalescence and drizzle scavenging cloud droplets, lag correlations show that N c decreases for 1 hr after the peak area-average rain rate. Greater observed LWP for lower N c [d(log N c )/d(log LWP) = 2.3] is consistent with enhanced entrainment drying of clouds with greater N c and consistent with removal of N c by thicker clouds with more coalescence and drizzle. Stronger precipitation in clouds with greater N c is the opposite sensitivity as expected were LWP to be controlled by the “cloud lifetime” indirect aerosol effect. The strong sensitivity of N c to LWP suggests that cloud dynamic and thermodynamic forcings drive macrophysical variability that controls N c in southeastern tropical Pacific stratocumulus clouds. Regressions are relatively insensitive to assumptions about the covariance of errors among the sensors.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Mixed-phase clouds and precipitation in Southern Ocean cyclones and cloud systems observed poleward of 64°S by ship-based cloud radar and lidar

Mixed-phase clouds (MPCs), composed of both liquid and ice, are prevalent in Southern Ocean cyclones. A characterisation 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 mid-level MPCs, with cloud tops between 2 and 6 km. Mid-level 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 mid-level 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. Additionally, periods of supercooled drizzle lasting up to two hours 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.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Maritime Aerosol and CCN Profiles Derived From Ship₋Based Measurements Over Eastern North Pacific During MAGIC

Atmospheric aerosols are widely recognized to give rise to a substantial radiative forcing to the climate by scattering and absorbing radiation and by modifying the microphysical, lifetime, and radiative properties of clouds. During the Marine ARM GPCI Investigation of Clouds (MAGIC) over the Eastern North Pacific (ENP), the ship-based measured cloud condensation nuclei (CCN) concentration at 0.2% supersaturation (N CCN,0.2 ) and condensation nuclei concentration (N CN ) had mean values of 116.7 and 219.4 cm ⁻3 , with the highest concentrations found closest to LA due to an increase in aerosol sources. Moving westward, both N CCN,0.2 and N CN gradually decreased until stabilizing near 100 cm ⁻3 and 200 cm ⁻3 , respectively. Using the methods proposed by Ghan and Collins (2004), https://doi.org/10.1175/1520-0426(2004)021<0387:uoisdt>2.0.co;2 and Ghan et al. (2006), https://doi.org/10.1029/2004jd005752, N CCN,0.2 profiles are retrieved using the surface measured N CCN,0.2 as a constraint. For coupled conditions, correlations between the retrieved N CCN,0.2 profiles and cloud-droplet number concentration (N C ) increase from 0.26 at the surface to 0.38 near cloud base, particularly true for non-drizzling clouds. Although the correlations are lower than expected, the percentage increase (46.2%) is encouraging. Finally, the relationships between cloud breakup (CB) and the stratocumulus to cumulus transition (SCT) with environmental conditions and associated aerosols are also studied. The decreased N CN trend east of CB is mainly caused by precipitation scavenging, while the increased N CN trend west of CB is strongly associated with the increased surface wind speed and fewer drizzle events. A further study is needed using high-resolution models to simulate these events.

54 ENVIRONMENTAL SCIENCES↗