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DOE OSTI2021

Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity

Marine low clouds strongly cool the planet. How this cooling effect will respond to climate change is a leading source of uncertainty in climate sensitivity, the planetary warming resulting from CO 2 doubling. In this study, we observationally constrain this low cloud feedback at a near-global scale. Satellite observations are used to estimate the sensitivity of low clouds to interannual meteorological perturbations. Combined with model predictions of meteorological changes under greenhouse warming, this permits quantification of spatially resolved cloud feedbacks. We predict positive feedbacks from midlatitude low clouds and eastern ocean stratocumulus, nearly unchanged trade cumulus and a near-global marine low cloud feedback of 0.19 ± 0.12 W m -2 K -1 (90% confidence). These constraints imply a moderate climate sensitivity (~3 K). Despite improved midlatitude cloud feedback simulation by several current-generation climate models, their erroneously positive trade cumulus feedbacks produce unrealistically high climate sensitivities. Conversely, models simulating erroneously weak low cloud feedbacks produce unrealistically low climate sensitivities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment

In the framework of the Multidisciplinary drifting Observatory for the Study of Arctic Climate Polarstern expedition, the Leibniz Institute for Tropospheric Research, Leipzig, Germany, operated the shipborne OCEANET-Atmosphere facility for cloud and aerosol observations throughout the whole year. OCEANET-Atmosphere comprises, amongst others, a multiwavelength Raman lidar, a microwave radiometer, and an optical disdrometer. A cloud radar was operated aboard Polarstern by the US Atmospheric Radiation Measurement program. These measurements were processed by applying the so-called Cloudnet methodology to derive cloud properties. To gain a comprehensive view of the clouds, lidar and cloud radar capabilities for low- and high-altitude observations were combined. Cloudnet offers a variety of products with a spatiotemporal resolution of 30 s and 30 m, such as the target classification, and liquid and ice microphysical properties. Additionally, a lidar-based low-level stratus retrieval was applied for cloud detection below the lowest range gate of the cloud radar. Based on the presented dataset, e.g., studies on cloud formation processes and their radiative impact, and model evaluation studies can be conducted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Investigating the impact of cloud-radiative feedbacks on tropical precipitation extremes

Abstract Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The relationship between the dust and gas-phase co across the California molecular cloud

We present results of an extinction-CO line survey of the southeastern part of the California molecular cloud (CMC). Deep, wide-field, near-infrared images were used to construct a sensitive, relatively high resolution (∼0.5 arcmin) (NICEST) extinction map of the region. The same region was also surveyed in the {sup 12}CO(2–1), {sup 13}CO(2–1), and C{sup 18}O(2–1) emission lines at the same angular resolution. These data were used to investigate the relation between the molecular gas, traced by CO emission lines, and the dust column density, traced by extinction, on spatial scales of 0.04 pc across the cloud. We found strong spatial variations in the abundances of {sup 13}CO and C{sup 18}O that were correlated with variations in gas temperature, consistent with temperature-dependent CO depletion/desorption on dust grains. The {sup 13}CO-to-C{sup 18}O abundance ratio was found to increase with decreasing extinction, suggesting selective photodissociation of C{sup 18}O by the ambient UV radiation field. The effect is particularly pronounced in the vicinity of an embedded cluster where the UV radiation appears to have penetrated deeply (i.e., A{sub V} ≲ 15 mag) into the cloud. We derived the cloud-averaged X-factor to be 〈X{sub CO} 〉 = 2.53 × 10{sup 20} cm{sup −2}(K km s{sup −1}){sup −1}, a value somewhat higher than the Milky Way average. On sub-parsec scales we find there is no single empirical value of the {sup 12}CO X-factor that can characterize the molecular gas in cold (T{sub k} ≲ 15 K) cloud regions, with X{sub CO} ∝ A{sub V}{sup 0.74} for A{sub V} ≳ 3 mag. However, in regions containing relatively hot (T{sub ex} ≳ 25 K) molecular gas we find a clear correlation between W({sup 12}CO) and A{sub V} over a large (3 ≲ A{sub V} ≲ 25 mag) range of extinction. This results in a constant X{sub CO} = 1.5 × 10{sup 20} cm{sup −2} (K km s{sup −1}){sup −1} for the hot gas, a lower value than either the average for the CMC or the Milky Way. Overall we find an (inverse) correlation between X{sub CO} and T{sub ex} in the cloud with X{sub CO} ∝ T{sub ex} {sup −0.7}. This correlation suggests that the global X-factor of a giant molecular cloud may depend on the relative amounts of hot gas contained within the cloud.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Numerical simulations of turbulent molecular clouds regulated by reprocessed radiation feedback from nascent super star clusters

Radiation feedback from young star clusters embedded in giant molecular clouds (GMCs) is believed to be important to the control of star formation. For the most massive and dense clouds, including those in which super star clusters (SSCs) are born, pressure from reprocessed radiation exerted on dust grains may disperse a significant portion of the cloud mass back into the interstellar medium. Using our radiation hydrodynamics code, Hyperion, we conduct a series of numerical simulations to test this idea. Our models follow the evolution of self-gravitating, strongly turbulent clouds in which collapsing regions are replaced by radiating sink particles representing stellar clusters. We evaluate the dependence of the star formation efficiency (SFE) on the size and mass of the cloud and κ, the opacity of the gas to infrared (IR) radiation. We find that the single most important parameter determining the evolutionary outcome is κ, with κ≳15 cm{sup 2} g{sup −1} needed to disrupt clouds. For κ=20−40 cm{sup 2} g{sup −1}, the resulting SFE = 50%−70% is similar to empirical estimates for some SSC-forming clouds. The opacities required for GMC disruption likely apply only in dust-enriched environments. We find that the subgrid model approach of boosting the direct radiation force L/c by a “trapping factor” equal to a cloud’s mean IR optical depth can overestimate the true radiation force by factors of ∼4−5. We conclude that feedback from reprocessed IR radiation alone is unlikely to significantly reduce star formation within GMCs unless their dust abundances or cluster light-to-mass ratios are enhanced.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Jupiter’s deep cloud structure revealed using Keck observations of spectrally resolved line shapes

Technique: We present a method to determine the pressure at which significant cloud opacity is present between 2 and 6 bars on Jupiter. We use (a) the strength of a Fraunhofer absorption line in a zone to determine the ratio of reflected sunlight to thermal emission, and (b) pressure-broadened line profiles of deuterated methane (CH{sub 3}D) at 4.66 μm to determine the location of clouds. We use radiative transfer models to constrain the altitude region of both the solar and thermal components of Jupiter’s 5 μm spectrum. Results: For nearly all latitudes on Jupiter the thermal component is large enough to constrain the deep cloud structure even when upper clouds are present. We find that hot spots, belts, and high latitudes have broader line profiles than do zones. Radiative transfer models show that hot spots in the North Equatorial Belt and South Equatorial Belt (SEB) typically do not have opaque clouds at pressures greater than 2 bars. The South Tropical Zone (STZ) at 32{sup ∘}S has an opaque cloud top between 4 and 5 bars. From thermochemical models this must be a water cloud. We measured the variation of the equivalent width of CH{sub 3}D with latitude for comparison with Jupiter’s belt-zone structure. We also constrained the vertical profile of H{sub 2}O in an SEB hot spot and in the STZ. The hot spot is very dry for P < 4.5 bars and then follows the H{sub 2}O profile observed by the Galileo Probe. The STZ has a saturated H{sub 2}O profile above its cloud top between 4 and 5 bars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A new method for measuring the 3D turbulent velocity dispersion of molecular clouds

ABSTRACT The structure and star formation activity of a molecular cloud are fundamentally linked to its internal turbulence. However, accurately measuring the turbulent velocity dispersion is challenging due to projection effects and observational limitations, such as telescope resolution, particularly for clouds that include non-turbulent motions, such as large-scale rotation. Here, we develop a new method to recover the 3D turbulent velocity dispersion (σv,3D) from position–position–velocity (PPV) data. We simulate a rotating, turbulent, collapsing molecular cloud, and compare its intrinsic σv,3D with three different measures of the velocity dispersion accessible in PPV space: (1) the spatial mean of the 2nd-moment map, σi, (2) the standard deviation of the gradient/rotation-corrected 1st-moment map, σ(c − grad), and (3) a combination of (1) and (2), called the ‘gradient-corrected parent velocity dispersion’, $\sigma _{\mathrm{(p}-\mathrm{grad)}}=(\sigma _{\mathrm{i}}^2+\sigma _{(\mathrm{c}-\mathrm{grad)}}^2)^{1/2}$. We show that the gradient correction is crucial in order to recover purely turbulent motions of the cloud, independent of the orientation of the cloud with respect to the line of sight. We find that with a suitable correction factor and appropriate filters applied to the moment maps, all three statistics can be used to recover σv,3D, with method 3 being the most robust and reliable. We determine the correction factor as a function of the telescope beam size for different levels of cloud rotation, and find that for a beam full width at half-maximum f and cloud radius R, the 3D turbulent velocity dispersion can best be recovered from the gradient-corrected parent velocity dispersion via $\sigma _{v,\mathrm{3D}}= \left[(-0.29\pm 0.26)\, f/R + 1.93 \pm 0.15\right] \sigma _{\mathrm{(p}-\mathrm{grad)}}$ for f/R < 1, independent of the level of cloud rotation or LOS orientation.

Stewart, Madeleine↗
DOE OSTI2025

Automated nuclear cloud feature extraction from film

Chemical, biological, radiological, nuclear, and explosives incidents require rapid detection and characterization for appropriate response. For a nuclear detonation, visible-light cameras may be used to locate the cloud and characterize fallout deposition when coupled with numerical models. Films from the United States’ nuclear testing era compose the only sizeable collection of imagery depicting high-yield detonations. These films offer unique insights into characteristics of flows involving scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models for nuclear fallout transport, either as part of emergency response or forensic activities. In this work, we implement modern computer vision and machine learning techniques to identify and track the cloud automatically and subsequently determine the time dependence of some of its features. We trained a ResNet-18 image classifier on hundreds of images to categorize nuclear cloud morphology. Each category or cloud regime is determined by early cloud evolution and is associated to constitutive properties of the flow, such as distribution of vorticity. Next, we identified keypoint features using the KAZE algorithm and tracked these keypoints in the images, allowing us to determine the dimensions and velocities of the cloud across film frames. These measurements converted to real-world units provide valuable experimental data that can be used in the development and validation of nuclear cloud models. We compared the results of this method against manual cloud rise measurements from two different films. In one, our automated method accelerated the feature extraction process without sacrificing measurement accuracy.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
DOE OSTI2016

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve our understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, we are still in poor understanding of (1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, (2) the feedback between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and (3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol-cloud interactions, and discusses the significances of aerosol impacts on raditative forcing and precipitation extremes associated with different cloud systems. Despite significant understanding has been gained about aerosol impacts on the main cloud types, there are still many unknowns especially associated with various deep convective systems. Therefore, large efforts are needed to escalate our understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties, cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed

Fan, Jiwen↗
DOE OSTI2018

Improvement of the Simulation of Cloud Longwave Scattering in Broadband Radiative Transfer Models

Abstract Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Improving the Simulation of Tropical Convective Cloud-Top Heights in CAM5 with CloudSat Observations

Using 4 years of CloudSat data, the simulation of tropical convective cloud-top heights (CCTH) above 6 km simulated by the convection scheme in the Community Atmosphere Model, version 5 (CAM5), is evaluated. Compared to CloudSat observations, CAM5 underestimates CCTH by more than 2 km on average. Further analysis of model results suggests that the dilute CAPE calculation, which has been incorporated into the convective parameterization since CAM4, is a main factor restricting CCTH to much lower levels. After removing this restriction, more convective clouds develop into higher altitudes, although convective clouds with tops above 12 km are still underestimated significantly. The environmental conditions under which convection develops in CAM5 are compared with CloudSat observations for convection with similar CCTHs. It is shown that the model atmosphere is much more unstable compared to CloudSat observations, and there is too much entrainment in CAM5. Since CCTHs are closely associated with cloud radiative forcing, the impacts of CCTH on model simulation are further investigated. Results show that the change of CCTH has important impacts on cloud radiative forcing and precipitation. With increased CCTHs, there is more cloud radiative forcing in tropical Africa and the eastern Pacific, but less cloud radiative forcing in the western Pacific. The contribution to total convective precipitation from convection with cloud tops above 9 km is also increased substantially.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Fast Transverse Beam Instability Caused by Electron Cloud Trapped in Combined Function Magnets

Electron cloud instabilities affect the performance of many circular high-intensity particle accelerators. They usually have a fast growth rate and might lead to an increase of the transverse emittance and beam loss. A peculiar example of such an instability is observed in the Fermilab Recycler proton storage ring. Although this instability might pose a challenge for future intensity upgrades, its nature had not been completely understood. The phenomena has been studied experimentally by comparing the dynamics of stable and unstable beam, numerically by simulating the build-up of the electron cloud and its interaction with the beam, and analytically by constructing a model of an electron cloud driven instability with the electrons trapped in combined function dipoles. Stabilization of the beam by a clearing bunch reveals that the instability is caused by the electron cloud, trapped in beam optics magnets. Measurements of microwave propagation confirm the presence of the cloud in the combined function dipoles. Numerical simulations show that up to 10$^{-2}$ of the particles can be trapped by their magnetic field. Since the process of electron cloud build-up is exponential, once trapped this amount of electrons significantly increases the density of the cloud on the next revolution. In a combined function dipole this multi-turn accumulation allows the electron cloud reaching final intensities orders of magnitude greater than in a pure dipole. The estimated fast instability growth rate of about 30 revolutions and low mode frequency of 0.4 MHz are consistent with experimental observations and agree with the simulations. The created instability model allows investigating the beam stability for the future intensity upgrades.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

A Multi-Instrument Cloud Condensation Nuclei Spectrum Product (Final Technical Report)

A wealth of observational data exists on the characteristics of atmospheric particulate matter, over multiple years, at the DOE ARM Southern Great Plains (SGP) Central Facility site. This site is located in a region of the country that frequently experiences weather extremes, and that is removed from many local sources of pollution but is affected by transported smoke, dust, and urban emissions. The relationships between particulate matter, cloud formation and evolution, and precipitation are therefore of strong interest, and are being explored via modeling on a variety of scales. These models require as input detailed information on the characteristics of particles capable of serving as the nuclei for cloud formation. Sufficient data exist to be able to put together a picture of the nature of the total aerosol and the cloud condensation nuclei (CCN) subset, and their variability, through merged data products. This study was aimed at exploiting the multiple measurement types at SGP to develop the first such multi-year estimates. Further, the resulting data were analyzed to understand temporal patterns ranging from hourly to seasonal, thereby gaining insights into the particle sources affecting the atmosphere in this region. DOE-funded datasets that were analyzed in this study include total particle number concentrations, submicron aerosol scattering coefficients, dry aerosol size distributions, and more recently, time-resolved submicron aerosol chemical composition. Data are also available for the number concentrations of particles that are activated in a cloud condensation nucleus instrument at a series of setpoint supersaturations, providing direct observations of the number concentrations of “CCN”. This variable is the quantity that is generally desired for inclusion in numerical models that seek to represent and predict the impacts of varying aerosol characteristics on the formation and microphysical properties of clouds. One limitation of the use of direct CCN observations is that they are not available for supersaturations larger than about 1%, which is insufficient for deep convection and may be insufficient even for shallow convection, depending on the nature of the available CCN and the dynamics of the cloud. We developed a data-based approach to representing the full aerosol size spectrum with size-dependent hygroscopicity, and used this to extrapolate CCN spectra beyond the limited measurements. Five years of SGP aerosol data (2009 -2013) were analyzed. As a side product of our work, we identified and communicated several previously-unflagged data quality issues. The resulting merged aerosol distributions, along with fits for seasonal averages, were published and submitted to the ARM archive as a special value-added product (VAP; submitted as a PI product). CCN spectra were computed for the same data period and will similarly be published and submitted to the archive for use by the community. We also note that our methodologies and findings have been discussed at several Joint ARM User Facility/Atmospheric System Research (ASR) Principal Investigators Meetings and that recent ARM/ASR aerosol data reporting strategies have included similar ideas for data merging, indicating that this work has had a lasting impact on ARM aerosol data acquisition and reporting. The proposed work advances the science of the interactions of aerosols, clouds and precipitation, with direct application to improve representation of such interactions for clouds in regional and global climate models. The archived data will continue to serve research studies in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Use of Remote Sensing and In-Situ Observations to Develop and Evaluate Improved Representations of Convection and Clouds for the ACME Model

The overachieving goal of the whole CMDV-MCS project is to improve understanding of warm season continental convection and to develop treatments of convection and microphysics capable of representing mesoscale convective systems (MCSs) features in large-scale models. Our tasks for this project contributing to the overachieving goal include: (1) Improve the ice nucleation formulation for MG2 and P3 cloud microphysics schemes; (2) Improve the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM; and (3) Test the performance of improved ice microphysics in E3SM with observation data. In this project, we have (1) Improved the ice nucleation parameterization for MG2 and P3 in E3SM by implementing two advanced empirical parameterizations with connection to aerosols. The two deterministic heterogeneous ice nucleation parameterizations (i.e., DeMott et al., 2015; Niemand et al., 2012) were merged with the MG2 and P3 cloud microphysics schemes in E3SM. Long-term simulations were conducted to examine the impacts of these new parameterizations on simulated cloud properties; (2) Improved the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM. We evaluated the double Gaussian PDF of vertical velocity simulated by the Cloud Layers Unified By Binormals (CLUBB) and the sub-column vertical velocity sampled from the Subgrid Importance Latin Hypercube Sampler (SILHS) in E3SM. We introduced the vertical velocity variance induced by topographic gravity waves for ice nucleation and droplet activation; and (3) Tested the performance of improved ice microphysics in E3SM with observation data. We tested the new treatments of ice nucleation in the single column model (SCM) mode for the stratiform mixed-phase clouds observed during 9-10 October 2004 in the DOE ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) and for the convective clouds observed on 20 May 2011 in the Midlatitude Continental Convective Clouds Experiment (MC3E). Modeled ice nucleating particles (INPs) concentrations were compared against observations collected around the globe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Marine Shallow Cloud Adjustments to the Presence of Shortwave-Absorbing Aerosols: Advancing Understanding Through a Combined Analysis of Lasic Datasets and Process Modeling (Final Report)

This is a final report for this award, whose purpose was to support the analysis of data emanating from the LASIC (Layered Atlantic Smoke Interaction with Clouds) campaign. (Layered Atlantic Smoke Interactions with Clouds) is a strategy to improve our understanding of aged carbonaceous aerosol, its seasonal evolution, and the mechanisms by which clouds adjust to the presence of the aerosol. The observational strategy centers on deploying the AMF1 cloud, aerosol, and atmospheric profiling instrumentation to Ascension Island, located within the trade-wind shallow cumulus regime (14.50W, 80S) 3000 km offshore of continental Africa. The location is within the latitude zone of the maximum outflow of aerosol, with the deepening boundary layer known to entrain free-tropospheric smoke. The primary activities for LASIC are: 1) to improve current knowledge on aged biomass burning aerosol and its radiative properties as a function of the seasonal cycle; 2) to use surface-based remote sensing to sensitively interrogate the atmosphere for the relative vertical location of aerosol and clouds; 3) to improve our understanding of the cloud adjustments to the presence of shortwave-absorbing aerosol within the vertical column, both through aerosol-radiation and through aerosol-cloud interactions; 4) to aid low cloud parameterization efforts for climate models. This award serves to further these activities and includes a sub-award to Dr. Pablo Saide at UCLA for activities 3) and 4).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

“Evaluation of boundary layer cloud processes in an advanced parameterization for global models” (Final Report)

Low clouds over the ocean are a critical component of our planet’s energy budget because they emit almost as much energy as the surface while being much more reflective than the ocean, resulting in a strong net cooling effect. Despite their importance, low marine clouds remain a persistent source of uncertainty in future climate projections. This project explored how the dynamics, thermodynamics and spatial organization of low clouds is represented in a particular physical simplification, or parameterization, of small-scale air motions and cloud processes commonly employed in global atmospheric models used for short-term weather and longer-term earth system prediction. The overall goal was to develop long-term observational products to constrain numerical model representations of turbulence and cloud processes using observations from the US Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program’s Eastern North Atlantic (ENA) site. These constraints were then used to demonstrate the type of information that can be gained from confronting simulations with the observations and we assessed the performance of a parameterization in simulating periods of low clouds at ENA. Finally, we used detailed computational fluid dynamics simulations of turbulence and cloud properties to evaluate general physical assumptions embedded in simplified representations of clouds and turbulence for global models of the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Freezing Processes in Southern Ocean Mixed Phase Clouds (Final Technical Report)

Southern Ocean (SO) low-level clouds remain a challenge for Earth system models to represent accurately. This project utilized DOE ARM observations and the Community Atmosphere Model (CAM) to improve process-level understanding of aerosol-cloud interactions and cloud microphysics for SO mixed-phase clouds. Specifically, our efforts include two main topics: 1) investigate the SO aerosol, cloud condensation nuclei (CCN), and ice nucleating particle (INP) population based on observations and determine predictive skill of simulating SO INPs, and 2) assess the ice formation pathways, including ice nucleation and secondary ice production, in SO mixed phase clouds utilizing a combination of observations and modeling tools. Studies focused on SO aerosol and INP resulted four manuscripts. Ice formation pathways in SO mixed phase clouds were investigated, revealing observed evidence of SIP active across all mixed phase temperatures. However, a key finding of this project is that despite significant progress in predicting SO INPs, the role of INP variability in SO cloud phase, precipitation, and radiative properties remain unknown due to challenges in microphysics parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗