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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2025

Enhancing Turbulent Mixing and Microphysical Uniformity in a Tall Convection‐Cloud Chamber Through Idealized Heterogeneity of Boundaries

A large convection cloud chamber has been proposed for exploring aerosol–cloud–drizzle interactions under well‐controlled turbulent conditions. Recent theoretical and numerical studies suggest that a convection cloud chamber with two heated and two cooled sidewalls can significantly enhance the liquid water content and thus benefit drizzle initiation. However, a chamber with such a sidewall configuration develops stable stratification and extremely weak turbulence therein. In this study, we conduct large‐eddy simulations of a tall convection chamber with five different sidewall configurations consisting of alternating warm and cold patches. For each configuration, the total surface area of warm patches equals that of cold patches, resulting in the same expected cloud‐free supersaturation based on a flux budget model. Results show that changing the sidewall configuration, while keeping all other factors constant, can substantially enhance turbulent mixing and improve the uniformity of thermodynamic and cloud microphysical properties in the bulk region of the chamber. In addition, turbulence strength is positively correlated with liquid water content and negatively correlated with cloud droplet number concentration, consistent with theoretical predictions. Our results highlight the advantage of building a large cloud chamber using modular patches with individually controllable temperature and humidity to achieve well‐mixed conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA)

With their extensive coverage, marine low clouds greatly impact global climate. Presently, marine low clouds are poorly represented in global climate models, and the response of marine low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. In addition, the ENA is periodically impacted by continental aerosols, making it an excellent location to study the cloud condensation nuclei (CCN) budget in a remote marine region periodically perturbed by anthropogenic emissions, and to investigate the impacts of long-range transport of aerosols on remote marine clouds. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) campaign was motivated by the need of comprehensive in-situ measurements for improving the understanding of marine boundary layer CCN budget, cloud and drizzle microphysics, and the impact of aerosol on marine low cloud and precipitation. The airborne deployments took place from June 21 to July 20, 2017 and January 15 to February 18, 2018 in the Azores. The flights were designed to maximize the synergy between in-situ airborne measurements and ongoing long-term observations at a ground site. Here we present measurements, observation strategy, meteorological conditions during the campaign, and preliminary findings. Lastly, we discuss future analyses and modeling studies that improve the understanding and representation of marine boundary layer aerosols, clouds, precipitation, and the interactions among them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improved Diagnosis of Precipitation Type with LightGBM Machine Learning

Abstract Existing precipitation-type algorithms have difficulty discerning the occurrence of freezing rain and ice pellets. These inherent biases are not only problematic in operational forecasting but also complicate the development of model-based precipitation-type climatologies. To address these issues, this paper introduces a novel light gradient-boosting machine (LightGBM)-based machine learning precipitation-type algorithm that utilizes reanalysis and surface observations. By comparing it with the Bourgouin precipitation-type algorithm as a baseline, we demonstrate that our algorithm improves the critical success index (CSI) for all examined precipitation types. Moreover, when compared with the precipitation-type diagnosis in reanalysis, our algorithm exhibits increased F1 scores for snow, freezing rain, and ice pellets. Subsequently, we utilize the algorithm to compute a freezing-rain climatology over the eastern United States. The resulting climatology pattern aligns well with observations; however, a significant mean bias is observed. We interpret this bias to be influenced by both the algorithm itself and assumptions regarding precipitation processes, which include biases associated with freezing drizzle, precipitation occurrence, and regional synoptic weather patterns. To mitigate the overall bias, we propose increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 , as it better reflects the precision of precipitation observations. This adjustment yields a substantial reduction in the overall bias. Finally, given the strong performance of LightGBM in predicting mixed precipitation episodes, we anticipate that the algorithm can be effectively utilized in operational settings and for diagnosing precipitation types in climate model outputs. Significance Statement Freezing rain can have significant impacts on transportation and infrastructure, making accurate prediction of precipitation types crucial. In this study, we use a machine learning method known as LightGBM to predict precipitation types. We show that the new algorithm performs better than the existing methods for all precipitation types examined. Additionally, we compute a freezing-rain climatology over the eastern United States. Although the resulting climatology pattern corresponds well to observations, the algorithm overpredicts freezing-rain occurrence. We argue that this bias can be substantially reduced by increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 . Overall, this work highlights the potential of the LightGBM algorithm for both weather forecasting and diagnosing precipitation types in climate models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

A Technique for Estimating Liquid Droplet Diameter and Liquid Water Content in Stratocumulus Clouds Using Radar and Lidar Measurements

This paper describes a technique for estimating the liquid water content (LWC) and a characteristic particle diameter in stratocumulus clouds using radar and lidar observations. The uncertainty in LWC estimate from radar and lidar measurements is significantly reduced once the characteristic particle diameter is known. The technique is independent of the drop size distribution. It is applicable for a broad range of W-band reflectivity Z between -30 and 0 dBZ and all values of lidar backscatter β observations. No partitioning of cloud or drizzle is required on the basis of an arbitrary threshold of Z as in prior studies. A method for estimating droplet diameter and LWC was derived from the electromagnetic simulations of radar and lidar observations. In situ stratocumulus cloud and drizzle probe spectra were input to the electromagnetic simulation. The retrieved droplet diameter and LWC were validated using in situ measurements from the southeastern Pacific Ocean. The retrieval method was applied to radar and lidar measurements from the northeastern Pacific. Uncertainty in the retrieved droplet diameter and LWC that are due to the measurement errors in radar and lidar backscatter measurements are 7% and 14%, respectively. The retrieved LWC was validated using the concurrent G-band radiometer estimates of the liquid water path.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessment of Precipitating Marine Stratocumulus Clouds in the E3SMv1 Atmosphere Model: A Case Study from the ARM MAGIC Field Campaign

This paper presents a process-oriented evaluation of precipitating stratocumulus and its transition to cumulus in version 1 of the Energy Exascale Earth System Model (E3SMv1) using comprehensive case-study observations from a field campaign of the Atmospheric Radiation Measurement program (ARM). The E3SMv1 single-column model (SCM) of the marine boundary layer and its low clouds and precipitation are compared to observations including subcloud drizzle retrievals from a combination of Doppler radar and lidar backscatter measurements. Additionally, the SCM is also compared to a large-eddy simulation (LES) of the same case. The combination of advanced remote sensing observations and LES is a powerful framework to evaluate the physical parameterizations of large-scale models. Given the observed large-scale environment, the E3SMv1 SCM realistically represents the evolution of clouds and boundary layer structure during the stratocumulus-to-cumulus transition. The model well simulates the liquid water path and its diurnal cycle in the stratocumulus period as well as the two-layer vertical thermodynamic structure and lower cloud fraction in the transition period. E3SMv1’s success in simulating the cloud in the stratocumulus period permitted examination of its precipitation processes. Here problems were identified with E3SMv1 producing an unrealistically small subcloud precipitation fraction, an unrealistic double peak in the vertical profiles of precipitation mass, and drizzle that evaporates too close to the surface. Further model diagnostics determined that these unrealistic characteristics resulted from an overly long microphysics time step and an unrealistic parameterization of the precipitation fraction. These results imply that careful consideration of these issues is needed in order to better simulate precipitation processes in marine stratocumulus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

On CCN Effects upon Convective Cold Pool Timing and Features

Abstract Cold pools produced by deep convection can initiate new convection, and their representation in larger-scale weather and climate models could improve prediction of the extent and timing of upscale growth. Cold pools originate from latent cooling from precipitation changing phase, but little attention has been paid to microphysical influences on cold pool characteristics, particularly CCN effects. Datasets obtained from the CACTI and RELAMPAGO field campaigns, along with idealized numerical modeling, are utilized to investigate the hypothesis that convective storms forming in higher-CCN environments generate their first surface rainfall later, delaying cold pool initiation. Aircraft observations of CCN and shallow convection on 9 days do suggest a CCN effect. Those ingesting more CCN contained fewer drizzle drops, although a decreased cloud depth with increasing CCN was also likely a limiting factor. In three of those cases that later developed into deep convection, the timing of cold pool onset was not ubiquitously delayed in environments with more CCN. Idealized numerical simulations suggest that an ordinary thunderstorm can experience small delays in cold pool onset with increasing CCN due to changes in graupel production, but CCN effects on the cold pool from a supercell thunderstorm can be easily overpowered by its unique dynamics. A strong inverse relationship between cold pool strength, expansion rate, and depth with increasing CCN is suggested by the results of the ordinary thunderstorm simulation. Further consideration of CCN appears warranted for future cold pool parameterization development, but other environmental factors affecting storm morphology and precipitation cannot be ignored.

Meteorology & Atmospheric Sciences↗
DOE OSTI2016

Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) Science Plan

With their extensive coverage, low clouds greatly impact global climate. Presently, low clouds are poorly represented in global climate models (GCMs), and the response of low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The poor representations of low clouds in GCMs are in part due to inadequate observations of their microphysical and macrophysical structures, radiative effects, and the associated aerosol distribution and budget in regions where the aerosol impact is the greatest. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary-layer (MBL) clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. Boundary-layer aerosol in the ENA region is influenced by a variety of sources, leading to strong variations in cloud condensation nuclei (CCN) concentration and aerosol optical properties. Recently a permanent ENA site was established by the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility on Graciosa Island in the Azores, providing invaluable information on MBL aerosol and low clouds. At the same time, the vertical structures and horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol, the radiative properties, precipitation efficiency, and lifecycle of MBL clouds, and the cloud response to aerosol perturbations. Much of this data can be obtained only through aircraft-based measurements. In addition, the interconnected aerosol and cloud processes are best investigated by a study involving simultaneous in situ aerosol, cloud, and thermodynamics measurements. Furthermore, in situ measurements are also necessary for validating and improving ground-based retrieval algorithms at the ENA site. This project is motivated by the need for comprehensive in situ characterizations of boundary-layer structure, and associated vertical distributions and horizontal variabilities of low clouds and aerosol over the Azores. ARM Aerial Facility (AAF) Gulfstream-1 (G-1) aircraft will be deployed at the ENA site during two intensive operational periods (IOPs) of early summer (June to July) of 2017 and winter (January to February) of 2018, respectively. Deployments during both seasons allow for examination of key aerosol and cloud processes under a variety of representative meteorological and cloud conditions. The science themes for the deployments include: 1) Budget of MBL CCN and its seasonal variation; 2) Effects of aerosol on cloud and precipitation; 3) Cloud microphysical and macrophysical structures, and entrainment mixing; 4) Advancing retrievals of turbulence, cloud, and drizzle; and 5) Model evaluation and processes studies. A key advantage of the deployments is the strong synergy between the measurements onboard the G-1 and the routine measurements at the ENA site, including state-of-the-art profiling and scanning radars. The 3D cloud structures provided by the scanning radars will put the detailed in situ measurements into mesoscale and cloud lifecycle contexts. On the other hand, high quality in situ measurements will enable validation and improvements of ground-based retrieval algorithms at the ENA site, leading to high-quality and statistically robust data sets from the routine measurements. The deployments, combined with the routine measurements at the ENA site, will have a long lasting impact on the research and modeling of low clouds and aerosols in the remote marine environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Combined High Spectral Resolution Lidar and Millimeter Wavelength Radar Measurement of Ice Crystal Precipitation

The goal of this research has been to improve measurements of snowfall using a combination of millimeter-wavelength radar and High Spectral Resolution Lidar (HSRL) Observations. Snowflakes are large compared to the 532nm HSRL wavelength and small compared to the 3.2 and 8.6 mm wavelength radars used in this study. This places the particles in the optical scattering regime of the HSRL, where extinction cross-section is proportional to the projected area of the particles, and in the Rayleigh regime for the radar, where the backscatter cross-section is proportional to the mass-squared of the particles. Forming a ratio of the radar measured cross-section to the HSRL measured cross section eliminates any dependence on the number of scattering particles, yielding a quantity proportional to the average mass-squared of the snowflakes over the average area of the flakes. Using simultaneous radar measurements of particle fall velocities, which are dependent particle mass and cross-sectional area it is possible to derive the average mass of the snow flakes, and with the radar measured fall velocities compute the snowfall rate. Since this retrieval requires the optical extinction cross-section we began by considering errors this quantity. The HSRL is particularly good at measuring the backscatter cross-section. In previous studies of snowfall in the high Arctic were able to estimate the extinction cross-section directly as a fixed ratio to the backscatter cross-section. Measurements acquired in the STORMVEX experiment in Colorado showed that this approach was not valid in mid-latitude snowfalls and that direct measurement of the extinction cross-section is required. Attempts to measure the extinction directly uncovered shortcomings in thermal regulation and mechanical stability of the newly deployed DOE HSRL systems. These problems were largely mitigated by modifications installed in both of the DOE systems. We also investigated other sources of error in the HSRL direct measurement of extinction (see appendix II of this report). We also developed improved algorithms to extract extinction from the HSRL data. These have been installed in the standard HSRL data processing software and are now available to all users of HSRL data. Validation of snowfall measurements has proven difficult due to the unreliability of conventional snowfall measurements coupled with the complexity of considering the vast variety of snowflake geometries. It was difficult to tell how well the algorithm’s approach to accommodating differences in snowflakes was working without good measurements for comparison. As a result, we decided to apply this approach to the somewhat simpler, but scientifically important, problem of drizzle measurement. Here the particle shape is known and the conventional measurement are more reliable. These algorithms where successfully applied to drizzle data acquired during the ARM MAGIC study of marine stratus clouds between California and Hawaii (see Appendix I). This technique is likely to become a powerful tool for studying lifetime of the climatically important marine stratus clouds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

ARM Thermodynamic Cloud Phase (THERMOCLDPHASE) Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Thermodynamic Cloud Phase (THERMOCLDPHASE) Value-Added Product (VAP) provides vertically resolved thermodynamic cloud phase classifications (Zhang and Levin 2024). This VAP applies the multi-sensor methodology introduced by Shupe (2007) to identify cloud phase at the pixel level as liquid, drizzle, liquid + drizzle, rain, ice, snow, or mixed-phase. In addition, the VAP determines the overall cloud layer phase—classified as liquid, mixed-phase, or ice—based on the fraction of ice-containing pixels within the entire layer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

G-Band Radar Demonstration for Microphysics Field Campaign Report

The G-Band Radar Demonstration for Microphysics (GRDM) campaign took place at the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) from March 15 to April 30, 2024. This was a deployment of two of NASA’s Jet Propulsion Laboratory (JPL) radars and one radar from Brookhaven National Laboratory to demonstrate the utility of high-frequency millimeter-wave radars for remote sensing of stratocumulus microphysical properties. The radars were deployed on the Ellen Browning Scripps Memorial Pier alongside the AMF instruments (Figure 1). The radars include a Ka-band (35 GHz), W-band (94 GHz), and four G-band (158, 165, 174, and 240 GHz) channels. The 240 GHz and W-band channels provide complete Doppler spectra, which are useful for advanced analysis. The 158-175 GHz channels are sensitive to the water vapor profile and are useful for attenuation correction. These radars complement the high-sensitivity ARM KAZR. The goal of the deployment was to observe drizzling stratocumulus and demonstrate the capabilities of the multifrequency radar data set to constrain profiles of liquid water content and drizzle drop characteristic size. The data are still being analyzed. The methodology to derive the cloud and precipitation parameters will exploit differential attenuation and differential reflectivity between low-frequency (Ka-band) and high-frequency (G-band) channels. The method will also exploit the capability of the G-band observations to constrain the attenuation due to water vapor. These observations will quantify the capabilities and limitations of the emerging technology of G-band radars for constraint stratocumulus cloud microphysics, which are key to constraining aerosol-cloud-precipitation interactions and low-cloud climate feedback.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Marine Boundary Layer Cloud Boundaries and Phase Estimation Using Airborne Radar and In Situ Measurements During the SOCRATES Campaign over Southern Ocean

The Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) was an aircraft-based campaign (15 January–26 February 2018) that deployed in situ probes and remote sensors to investigate low-level clouds over the Southern Ocean (SO). A novel methodology was developed to identify cloud boundaries and classify cloud phases in single-layer, low-level marine boundary layer (MBL) clouds below 3 km using the HIAPER Cloud Radar (HCR) and in situ measurements. The cloud base and top heights derived from HCR reflectivity, Doppler velocity, and spectrum width measurements agreed well with corresponding lidar-based and in situ estimates of cloud boundaries, with mean differences below 100 m. A liquid water content–reflectivity (LWC-Z) relationship, LWC = 0.70Z0.29, was derived to retrieve the LWC and liquid water path (LWP) from HCR profiles. The cloud phase was classified using HCR measurements, temperature, and LWP, yielding 40.6% liquid, 18.3% mixed-phase, and 5.1% ice samples, along with drizzle (29.1%), rain (3.2%), and snow (3.7%) for drizzling cloud cases. The classification algorithm demonstrates good consistency with established methods. This study provides a framework for the boundary and phase detection of MBL clouds, offering insights into SO cloud microphysics and supporting future efforts in satellite retrievals and climate model evaluation.

MBL clouds over Southern Ocean↗
DOE OSTI2012

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptual model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

On the reversibility of transitions between closed and open cellular convection

The two-way transition between closed and open cellular convection is addressed in an idealized cloud-resolving modeling framework. A series of cloud-resolving simulations shows that the transition between closed and open cellular states is asymmetrical and characterized by a rapid ("runaway") transition from the closed- to the open-cell state but slower recovery to the closed-cell state. Given that precipitation initiates the closed–open cell transition and that the recovery requires a suppression of the precipitation, we apply an ad hoc time-varying drop concentration to initiate and suppress precipitation. We show that the asymmetry in the two-way transition occurs even for very rapid drop concentration replenishment. The primary barrier to recovery is the loss in turbulence kinetic energy (TKE) associated with the loss in cloud water (and associated radiative cooling) and the vertical stratification of the boundary layer during the open-cell period. In transitioning from the open to the closed state, the system faces the task of replenishing cloud water fast enough to counter precipitation losses, such that it can generate radiative cooling and TKE. It is hampered by a stable layer below cloud base that has to be overcome before water vapor can be transported more efficiently into the cloud layer. Recovery to the closed-cell state is slower when radiative cooling is inefficient such as in the presence of free tropospheric clouds or after sunrise, when it is hampered by the absorption of shortwave radiation. Tests suggest that recovery to the closed-cell state is faster when the drizzle is smaller in amount and of shorter duration, i.e., when the precipitation causes less boundary layer stratification. Cloud-resolving model results on recovery rates are supported by simulations with a simple predator–prey dynamical system analogue. It is suggested that the observed closing of open cells by ship effluent likely occurs when aerosol intrusions are large, when contact comes prior to the heaviest drizzle in the early morning hours, and when the free troposphere is cloud free.

Feingold, G.↗
DOE OSTI2016

Marine boundary layer structure as observed by A-train satellites

Abstract. The marine boundary layer (MBL) structure is important to the marine low cloud processes, and the exchange of heat, momentum, and moisture between oceans and the low atmosphere. This study examines the MBL structure over the eastern Pacific region and further explores the controlling factors of MBL structure over the global oceans with a new 4-year satellite-based data set. The MBL top (boundary layer height, BLH) and the mixing layer height (MLH) were identified using the MBL aerosol lidar backscattering from the CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations). Results showed that the MBL is generally decoupled with MLH ∕ BLH ratio ranging from ∼ 0.5 to ∼ 0.8 over the eastern Pacific Ocean region. The MBL decoupling magnitude is mainly controlled by estimated inversion strength (EIS), which in turn controls the cloud top entrainment process. The systematic differences between drizzling and non-drizzling stratocumulus tops also show dependence on EIS. This may be related to the meso-scale circulations or gravity wave in the MBL. Further analysis indicates that the MBL shows a similar decoupled structure for clear-sky and cumulus-cloud-topped conditions, but is better mixed under stratiform cloud breakup and overcast conditions.

54 ENVIRONMENTAL SCIENCES↗