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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

First EarthCARE CPR Observations of Dynamics–Microphysics Coupling in Marine Cold‐Air Outbreak Clouds

Marine cold-air outbreak (MCAO) clouds begin as shallow cloud streets near the ice edge and evolve into broken open-cell convection downstream. Their rapid transitions in cloud structure and microphysics are closely linked to vertical motions, but this interplay has not previously been observed from space. The EarthCARE satellite, carrying the first spaceborne Doppler radar (Cloud Profiling Radar, CPR), now measures hydrometeor sedimentation velocity and vertical air motion. Using CPR observations over the Norwegian and Barents Seas (December 2024–May 2025), we analyze MCAO and non-MCAO clouds. We find that strong updrafts in MCAO clouds coincide with larger supercooled liquid water (SLW) path (LWP). These conditions are accompanied by increases in sedimentation velocity and its vertical gradient, reflecting rapid riming-driven ice growth. In contrast, non-MCAO clouds show lower riming efficiency at similar LWP due to relatively weaker dynamical support. This emphasizes the importance of dynamics in shaping polar cloud structure and microphysics.

Kim, Jiseob [McGill Univ., Montreal, QC (Canada)] ↗
NASA NTRS1986

Senstitivity analysis of horizontal heat and vapor transfer coefficients for a cloud-topped marine boundary layer during cold-air outbreaks

The effects of external parameters on the surface heat and vapor fluxes into the marine atmospheric boundary layer (MABL) during cold-air outbreaks are investigated using the numerical model of Stage and Businger (1981a). These fluxes are nondimensionalized using the horizontal heat (g1) and vapor (g2) transfer coefficient method first suggested by Chou and Atlas (1982) and further formulated by Stage (1983a). In order to simplify the problem, the boundary layer is assumed to be well mixed and horizontally homogeneous, and to have linear shoreline soundings of equivalent potential temperature and mixing ratio. Modifications of initial surface flux estimates, time step limitation, and termination conditions are made to the MABL model to obtain accurate computations. The dependence of g1 and g2 in the cloud topped boundary layer on the external parameters (wind speed, divergence, sea surface temperature, radiative sky temperature, cloud top radiation cooling, and initial shoreline soundings of temperature, and mixing ratio) is studied by a sensitivity analysis, which shows that the uncertainties of horizontal transfer coefficients caused by changes in the parameters are reasonably small.

Chang, Y. V.↗
NASA NTRS1983

Factors influencing the marine boundary layer during a cold-air outbreak

The model for the cloud-topped marine boundary layer during a cold air outbreak developed by Stage and Businger (1981a) is used in conjunction with a test profile based on a fall outbreak episode over Lake Ontario to study factors influencing marine boundary-layer evolution. Sensitivity tests are done which show changes in layer evolution resulting from variation of wind speed, radiative sky temperature, water surface temperature, humidity of the shoreline sounding and divergence. The behavior of the layer in the presence of a region of cold-water upwelling near the shore is also investigated. It is found that the main effect of the upwelling region is to delay modification of the boundary-layer air.

Stage, S. A.↗
NASA NTRS1991

Aspects of the evolution of the marine boundary layer during cold-air outbreaks off the southeast coast of the United States

Remote sensing and in situ measurements that were obtained in February 1986 were combined with the results from a boundary-layer model to study aspects of the evolution of the maine boundary layer (MBL) during two cold-air outbreaks (CAO) off the southeast coast of the United States. Maximum total heat fluxes occurred over the Gulf Stream northeast of Cape Hatteras where very cold, dry air encountered the Gulf Stream and where the wind speeds were very large. Maximum 6-h values for the total heat flux were as high as 2015 W/m. The magnitude of the area-average heat flux in the MBL was influenced not only by the surface air and dewpoint temperatures and the surface wind speeds off the coast but also by the area covered by Gulf Stream water (sea surface temperature greater than 22 C). The heat flux distribution off the coast rapidly produced large horizontal temperature and humidity differences over distances on the order of 100 km.

Vukovich, Fred M.↗
NASA NTRSDate not supplied

An LES Survey of Cold-Air Outbreaks Spanning ACTIVATE and COMBLE

Two recent field campaigns offer unique new opportunities to survey coupled aerosol and cloud processes operating within cold-air outbreaks (CAOs). NASA's 2019-2023 Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project provided airborne in situ and remote sensing observations in multiple CAOs off the central US Eastern Seaboard. Contemporaneously, DOE's 2019-2020 Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) provided continuous ground-based in situ and remote sensing measurements during hundreds of hours of CAO conditions at two sites flanking the Norwegian Sea. Here we highlight lessons learned from contrasting sets of aerosol-aware Lagrangian large-eddy simulation case studies derived from each campaign, as well as outstanding uncertainties. Cases simulated include all of the most extensively sampled CAO flights during ACTIVATE, and a wide range of CAO strengths and mesoscale structures during COMBLE. Each case study is also suitable for simulation with large-scale models in single-column model mode or with a limited-domain approach using periodic boundary conditions. We seek to address the central question: what microphysical process pathways control the Lagrangian evolution of surface and top-of-atmosphere radiative fluxes under ACTIVATE and COMBLE conditions? Many science team members, co-investigators, and collaborators will be gratefully acknowledged in association with their contributions to making this work possible.

cold-air outbreaks↗
NASA NTRS1991

Heat fluxes and roll circulations over the western Gulf Stream during an intense cold-air outbreak

Turbulence and heat fluxes in the marine atmospheric boundary layer (MABL) for three aircraft stacks near the western Gulf Stream front, observed during the Genesis of Atlantic Lows Experiment (GALE) January 28, 1986 cold-air outbreak, has been studied using mixed-layer scaling. The GOES image and stability parameter indicates that these three stacks were in the roll vortex regime. The turbulence structure in the MABL is studied for this case, as well as the significance of roll vortices to heat fluxes. The roll circulations are shown to contribute significantly to the sensible (temperature) and latent heat (moisture) fluxes with importance increasing upward. The results suggest that the entrainment at the MABL top might affect the the budgets of temperature and humidity fluxes in the lower MABL, but not in the unstable surface layer.

Chou, Shu-Hsien↗
DOE OSTI2026

Exposing and Reducing Biases of Simulating Mixed-Phase Clouds in the Convection-Permitting E3SM Atmosphere Model: Lessons From an Arctic Cold-Air Outbreak

Mixed-phase clouds modulate the water and energy cycles of high-latitude regions, yet their liquid-ice phase partitioning has long been poorly simulated in climate models. Here, simulations of Arctic mixed-phase clouds by the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) are assessed against large-eddy simulations, satellite data, and ground-based observations during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment field campaign. SCREAM simulates nearly completely frozen clouds, which is attributed largely to the unreasonably strong Wegener–Bergeron–Findeisen (WBF) process that converts liquid to ice excessively and partly to the early over-abundant ice production at cold temperatures from a temperature-deterministic deposition ice nucleation scheme. Assuming no subgrid variation for the WBF process in the original formulation particularly conflicts with the instantaneous saturation adjustment assumption in the condensation scheme that assumes subgrid variability, leading to exaggerated WBF process rates. A proposed simple physically-based improvement on the treatment of subgrid cloud overlap substantially increases supercooled liquid water content and notably improves cloud-top phase partitioning, aligning better with observations. Improvement of supercooled liquid water content also converges with increasing horizontal resolution. The deposition ice nucleation scheme is found responsible for a falsely-produced ice cloud aloft that is not observed, biasing the simulated cloud radiative effects and top-of-atmosphere radiative fluxes. This study identifies key deficiencies in cloud parameterizations that continue to challenge convection-permitting models.

Geosciences↗
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 NTRS1988

Genesis of Atlantic Lows Experiment (GALE) - An overview

The field phase of the Genesis of Atlantic Lows Experiment (GALE) was conducted from 15 January to 15 March 1986. The objectives of GALE were to study mesoscale and air-sea interaction processes in East Coast winter storms, with particular emphasis on their contributions to cyclogenesis. This project area, specail observing systems, and field operations are described. There were thirteen special observing periods during the field phase including eight cases of cyclogenesis. Meterological and oceanographic phenomena on which special observations were collected include: cyclogenesis, rainbands, cold fronts, coastal fronts, cold-air damming, jets streaks, tropopause folding, low-level jets, cold-air outbreaks, lightning and marine boundary layer interactions with Gulf Stream and mid-shelf oceanic fronts. Preliminary research findings and operational implications are presented. GALE data documents are listed. The GALE data set is open to all interested scientists.

Dirks, R. A.↗
NASA NTRS2022

Dilution of Boundary Layer Cloud Condensation Nucleus Concentrations by Free Tropospheric Entrainment During Marine Cold Air Outbreaks

Recent aircraft measurements over the northwest Atlantic enable an investigation of how entrainment from the free troposphere (FT) impacts cloud condensation nucleus (CCN) concentrations in the marine boundary layer (MBL) during cold-air outbreaks (CAOs), motivated by the role of CCN in mediating transitions from closed to open-cell regimes. Observations compiled over eight flights indicate predominantly far lesser CCN concentrations in the FT than in the MBL. For one flight, a fetch-dependent MBL-mean CCN budget is compiled from estimates of sea-surface fluxes, entrainment of FT air, and hydrometeor collision-coalescence, based on in-situ and remote-sensing measurements. Results indicate a dominant role of FT entrainment in reducing MBL CCN concentrations, consistent with satellite-observed trends in droplet number concentration upwind of CAO cloud-regime transitions over the northwest Atlantic. Relatively scant CCN may widely be associated with FT dry intrusions, and should accelerate cloud-regime transitions where underlying MBL air is CCN-rich, thereby reducing regional albedo.

Boundary Layer Cloud Condensation Nucleus Concentr↗
NASA NTRS2022

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

Postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario

Jingyi Chen↗
NASA NTRS1986

The structure of the unstable marine boundary layer viewed by lidar and aircraft observations

The marine atmospheric boundary layer (MABL) during a cold-air outbreak off the Atlantic coast between New York and Virginia on January 20, 1983 is characterized on the basis of airborne lidar observations, vertical soundings (potential temperature, vapor mixing ratio, relative humidity, and wind), and horizontal (770-m) temperature records. The data are presented in tables and graphs and analyzed in detail. The organization of the MABL is defined by 1-2-km-scale roll vortices with up and downdrafts of 2-4 m/s at 210 m; north-south orientation of the roll axes (parallel to the low-level winds); rising arms coinciding with updrafts rich in moisture, aerosols, and heat; and 150-200-m (peak-to-trough) undulations of the inversion. Consideration is given to problems inherent in the interpretation of lidar data for MABL studies.

Atlas, D.↗
NASA NTRS1989

Bivariate conditional sampling of buoyancy flux during an intense cold-air outbreak

The joint frequency distribution technique was used to analyze buoyancy fluxes in the marine atmospheric boundary layer (MABL) for the cloud street regime noted during the Genesis of Atlantic Lows Experiment. It is found that for the lower half of the MABL, the buoyancy flux is mainly generated by the rising thermals and the sinking compensating ambient air, and is mainly consumed by the entrainment and detrainment of thermals, penetrative convection, and the entrainment from the MABL top. If the buoyancy flux is primarily driven by the temperature flux, these buoyancy-flux generating processes should be the same for the lower boundary layers over land and ocean. The results of the scale analysis of the buoyancy flux agree well with those obtained for mesoscale cellular convection during the Air-Mass Transformation Experiment.

Chou, Shu-Hsien↗
NASA NTRS2021

On Assessing ERA5 and MERRA2 Representations of Cold-Air Outbreaks Across the Gulf Stream

The warm Gulf Stream sea surface temperatures (SSTs) strongly impact the evolution of winter clouds behind atmospheric cold fronts. Such cloud evolution remains challenging to model. The Gulf Stream is too wide within the ERA5 and MERRA2 reanalyses, affecting the turbulent surface fluxes. Known problems within the ERA5 boundary layer (too-dry and too-cool with too strong westerlies), ascertained primarily from ACTIVATE 2020 campaign aircraft dropsondes and secondarily from older buoy measurements, reinforce surface flux biases. In contrast, MERRA2 winter surface winds and air-sea temperature/humidity differences are slightly too weak, producing surface fluxes that are too low. Reanalyses boundary layer heights in the strongly-forced winter cold-air-outbreak regime are realistic, whereas late-summer quiescent stable boundary layers are too shallow. Nevertheless, the reanalysis biases are small, and reanalyses adequately support their use for initializing higher-resolution cloud process modeling studies of cold-air outbreaks.

Gulf stream↗
DOE OSTI2026

Mesoscale Organization in Cumulus-Coupled Stratocumulus

Marine cloud systems cover a substantial portion of the world’s oceans. Most of these clouds form relatively close to the ocean surface, typically within one to two kilometers, a region referred to by meteorologists as the marine boundary layer. They are composed predominantly of liquid water, although ice particles can occur in mid- and high-latitude marine clouds during winter. In satellite imagery, these clouds appear bright against the darker ocean surface below, reflecting a large fraction of incoming sunlight back into space that would otherwise warm the ocean. Because marine boundary layer clouds cover such an extensive area of the ocean, they exert a significant influence on Earth’s overall transfer of solar energy absorbed by the surface and thermal energy emitted to space, a balance known as the planetary radiation budget. Marine boundary layer clouds are typically thin, and their formation and dissipation depend on a delicate balance between processes acting at the ocean surface below and the warm, dry air above. They are notoriously difficult to simulate accurately in weather forecast models, which often produce too few marine low clouds in midlatitudes and clouds in tropical regions that are excessively bright, meaning they reflect too much solar radiation. The marine boundary layer is frequently characterized by widespread overcast cloud cover that often transitions from a continuous, single-layer deck to more broken cloud fields toward the tropics. These transitions typically proceed through an intermediate stage in which shallow, broken clouds form beneath the overlying stratiform cloud deck. Once broken clouds develop below the overcast, they frequently self-organize into cloud clusters known as marine boundary layer convective complexes (MBLCCs), although the mechanisms governing the formation and organization of MBLCCs remain poorly understood. Accurately representing these transitions in long-range weather forecast models is essential because they influence the properties of air masses advected over the continental United States and Europe, and they become increasingly important for forecasts on seasonal and longer timescales. We employed two complementary approaches to investigate the processes controlling MBLCCs and their impact on marine cloud cover. Long-term observations from the U.S. Department of Energy’s Eastern North Atlantic (ENA) Observatory provided a unique dataset that allowed us to characterize fundamental properties of MBLCCs, including their typical size and frequency of occurrence. These observations were combined with high-resolution numerical simulations performed on supercomputers to examine the evolution of MBLCCs during cold-air outbreaks over the ENA region.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A study of the evolution of the surface heat flux off the southeast coast of the United States during a cold air outbreak using satellite remote sensing data

Attention is given to the contribution of the marine boundary layer to storm development via a study of the evolution of the spatial distribution of the heat flux during a cold-air outburst (CAO) which occurred during the GALE Field Program period in a 550,000-sq-km area off the southeast coast of the United States. The study focuses on a CAO that occurred in the period February 24-26, 1986. During the CAO, the area averaged total surface heat flux ranged from 190 W/sq m to 1114 W/sq m. The high value was characterized by a lower average surface air and dew-point temperatures and a higher average surface wind speed. In general, the surface heat flux increased as the sea-surface temperatures on the continental shelf increased. It reached the maximum over the Gulf Stream, and then decreased over the eastern portions of the Gulf Stream and over the Sargasso Sea. The configuration conforms with some of the earlier findings of Bane and Osgoode (1989) and Blanton et al. (1989).

Vukovich, Fred M.↗