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All sourcesNASA NTRSDOE OSTI
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 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 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 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↗
DOE OSTI2021

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors

Cloud drop number concentrations (N d ) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosoloptical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak inspring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH),low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol–N d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N d .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying albedo susceptibility biases in shallow clouds

The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. The problem is confounded by the fact that aerosol particles influence clouds locally and that averaging to larger spatial and/or temporal scales carries biases that depend on the heterogeneity and spatial correlation of the interacting fields and the nonlinearity of the responses. Mimicking commonly applied satellite data analyses for calculation of albedo susceptibility S o , we quantify S o aggregation biases using an ensemble of 127 large eddy simulations of marine stratocumulus. We explore the cloud field properties that control this spatial aggregation bias and quantify the bias for a large range of shallow stratocumulus cloud conditions manifesting a variety of morphologies and ranges of cloud fractions. We show that S o spatial aggregation biases can be on the order of hundreds of percent, depending on the methodology. Key uncertainties emanate from the typically applied adiabatic drop concentration N d retrieval, the correlation between aerosol and cloud fields, and the extent to which averaging reduces the variance in cloud albedo A c and N d . So biases are more often positive than negative and are highly correlated with biases in the liquid water path adjustment. Temporal aggregation biases are shown to offset spatial aggregation biases. Both spatial and temporal biases have significant implications for observationally based assessments of aerosol indirect effects and our inferences of underlying aerosol–cloud–radiation effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Identifying synoptic controls on boundary layer thermodynamic and cloud properties in a regional forecast model

Although most of our understanding of boundary layer cloudiness is based on idealized, subtropical, barotropic marine environments, boundary layer clouds exist across a range of conditions. In this study, we use the Naval Research Laboratory's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) and an automated cold-front-relative analysis framework to explore the boundary layer structure associated with low clouds across a transect through the cold front of a midlatitude synoptic cyclone. The model credibly captures boundary layer structure in line with conceptual models of midlatitude cyclones and ground-based observations at Graciosa Island in the Azores. The warm sector is conditionally unstable, with clouds that are too shallow and with too little liquid water, compared to cloud property retrievals from satellite and surface-based instruments. The cold-frontal region exhibits convection associated with weak stability and ascent. Northwest of the cold front, the boundary layer is well mixed, deeper, and capped by a strong inversion maintained by large-scale subsidence. Simulated clouds in frontal and post-frontal regions are mostly too thick, with too much liquid water and too little cloud base drizzle. The post-frontal clouds are associated with grid-scale updrafts, which appear to be the model's attempt to represent mesoscale organization of cellular convection typically observed in the cold sector of midlatitude cyclones. The deep, well-mixed post-frontal boundary layers and cloudiness are maintained by strong surface fluxes, as in cold air outbreaks. Our analysis framework serves as a unique approach to model verification, and our results offer insights into differences in boundary layer cloud behavior between subtropical and synoptic cold-sector regimes.

Eissner, Jordan M. [Univ. of Kansas, Lawrence, KS ↗
DOE OSTI2025

Cloud processing of dimethyl sulfide (DMS) oxidation products limits sulfur dioxide (SO 2 ) and carbonyl sulfide (OCS) production in the eastern North Atlantic marine boundary layer

Dimethyl sulfide (DMS) is the major sulfur species emitted from the ocean. The gas-phase oxidation of DMS by hydroxyl radicals proceeds through the stable, soluble intermediate hydroperoxymethyl thioformate (HPMTF), eventually forming carbonyl sulfide (OCS) and sulfur dioxide (SO 2 ). Recent work has shown that HPMTF is efficiently lost to marine boundary layer (MBL) clouds, thus arresting OCS and SO 2 production and their contributions to new-particle formation and growth events. To date, no long-term field studies exist to assess the extent to which frequent cloud processing impacts the fate of HPMTF. Here, we present 6 weeks of measurements of the cloud fraction and the marine sulfur species methanethiol, DMS, and HPMTF made at the Atmospheric Radiation Measurement (ARM) research facility on Graciosa Island, Azores, Portugal. Using an observationally constrained chemical box model, we determine that cloud loss is the dominant sink of HPMTF in this region of the MBL during the study, accounting for 79 %–91 % of HPMTF loss on average. When accounting for HPMTF uptake to clouds, we calculate campaign average reductions in DMS-derived MBL SO 2 and OCS of 52 %–60 % and 80 %–92 % for the study period. Using yearly measurements of the site- and satellite-measured 3D cloud fraction and DMS climatology, we infer that HPMTF cloud loss is the dominant sink of HPMTF in the eastern North Atlantic during all seasons and occurs on timescales faster than what is prescribed in global chemical transport models. Accurately resolving this rapid loss of HPMTF to clouds has important implications for constraining drivers of MBL new-particle formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Occurrence of seeding multi-layer clouds in the Arctic from ground-based observations

Studies of Arctic clouds often focus on low-level single-layer clouds (SLCs). Here, we use combined observations of soundings and cloud radar during the MOSAiC, ACSE, and AO2018 research cruises as well as from long-term observations at Ny-Ålesund, Svalbard and Utqiagvik, Alaska to investigate the occurrence of SLCs and multi-layer clouds (MLCs) in the Arctic and to assess the rate of ice-crystal seeding in cold MLCs. MOSAiC observations show cloudy conditions in between 70 % and 90 % of sounding-radar cases. SLCs show occurrence rates of 30 % to 40 % with the highest value of 45 % during October. Cold MLCs are most abundant from November to June (40 % to 55 % of cases). Seeding occurs in about half to two thirds of the identified cold MLCs during MOSAiC for which the sub-saturated layer extends between 100 and 1000 m. The seeding rate increases by as much as 20 percentage points as the assumed size of the falling ice crystals is increased from 100 to 400 µm. The observations reveal a stable rate of cloud-free conditions of around 20 % over the covered latitude range. Cloud occurrence during MOSAiC and at Ny-Ålesund in July, when the geographical distance between observations was minimal, shows reasonable agreement. Comparisons of MOSAiC and other research cruises to the central Arctic also indicate consistent occurrence rates of different cloud types despite the likely effect of year-to-year variability. The comparison of data from ship campaigns and land sites suggests that the latter are not necessarily a good indicator of cloud occurrence in the high Arctic.

Achtert, Peggy [Leipzig Univ. (Germany); Meteorolo↗
DOE OSTI2024

Detection of small drizzle droplets in a large cloud chamber using ultrahigh-resolution radar

Abstract. A large convection–cloud chamber has the potential to produce drizzle-sized droplets, thus offering a new opportunity to investigate aerosol–cloud–drizzle interactions at a fundamental level under controlled environmental conditions. One key measurement requirement is the development of methods to detect the low-concentration drizzle drops in such a large cloud chamber. In particular, remote sensing methods may overcome some limitations of in situ methods. Here, the potential of an ultrahigh-resolution radar to detect the radar return signal of a small drizzle droplet against the cloud droplet background signal is investigated. It is found that using a small sampling volume is critical to drizzle detection in a cloud chamber to allow a drizzle drop in the radar sampling volume to dominate over the background cloud droplet signal. For instance, a radar volume of 1 cubic centimeter (cm3) would enable the detection of drizzle embryos with diameter larger than 40 µm. However, the probability of drizzle sampling also decreases as the sample volume reduces, leading to a longer observation time. Thus, the selection of radar volume should consider both the signal power and the drizzle occurrence probability. Finally, observations from the Pi Convection–Cloud Chamber are used to demonstrate the single-drizzle-particle detection concept using small radar volume. The results presented in this study also suggest new applications of ultrahigh-resolution cloud radar for atmospheric sensing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Bertrand, Leah (ORCID:0009000001607558)↗
DOE OSTI2022

Evaluation of a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments

This research introduces a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The scheme employs a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) to efficiently simulate aerosol activation, the vertical profile of supersaturation, and the activated cloud droplet number concentration (CDNC) near the cloud base. The calculated maximum supersaturation values using the QDGE scheme were compared with multiple parcel model simulations under various aerosol and environmental conditions. The differences are all below 0.18 %, indicating good performance and accuracy of the QDGE scheme. We evaluated the QDGE scheme by specifying observed environmental thermodynamic variables and aerosol information from 31 cloud cases as input and comparing the simulated CDNC with cloud observations. The average of mean relative error ($\overline{MRE}$) of the simulated CDNC for cloud cases in each campaign ranges from 17.30 % in Brazil to 25.90 % in China, indicating that the QDGE scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Additionally, we carried out an error analysis by calculating the maximum information coefficient (MIC) between the MRE and input variables for the individual campaigns and all cloud cases. MIC values were then sorted by aerosol properties, pollution level, environmental humidity, and dynamic condition according to their relative importance to MRE. Based on the error analysis, we found that the magnitude of MRE is more relevant to the specification of input aerosol pollution level in marine regions and aerosol hygroscopicity in continental regions than to other variables in the simulation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Conference on Cloud Physics, Tucson, Ariz., October 21-24, 1974, Proceedings

Condensation and ice nucleation processes are considered, taking into account measurements of cloud nuclei and aerosol size spectra in the semiarid Southwest, the formation of sulfates and the enhancement of cloud condensation nuclei in clouds, biogenic sources of atmospheric ice nuclei, and the experimental determination of the deposition coefficient of water vapor onto ice. Other topics discussed are related to precipitation growth processes, the role of ice in cloud systems, cloud modeling, measurements in Colorado hailstorms during the national hail research experiment, cloud measurements, and measurement techniques. Attention is also given to cloud electrification, zero-gravity experiments, and the control of cloud development by larger scale motions. Individual items are announced in this issue.

Source record↗