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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Seasonal Variation in Martian Water Ice Cloud Particle Size

We employ the complete record of Mars limb-viewing observations by the Compact Reconnaissance Imaging Spectrometer, totaling 922 successful retrievals, to chart the seasonal variation in water ice cloud particle size. Low-latitude clouds exhibit particle size sorting with altitude at all seasons, with particles ranging from >3.0 m in effective radius to 1.01.5 m. However, at a given altitude, the ice particle size often varies through the year. Ice particle sizes in the tropics follow a different seasonal cycle than ice mixing ratio. North polar clouds have a complex seasonal cycle, with a sloped size profile with altitude as the polar hood cloud forms in early fall trending to a roughly uniform 1.5 m profile by the end of winter. These data are an important metric to validate and improve general circulation model microphysical routines and to better understand how martian water ice clouds influence the atmospheric radiative budget.

Scott D. Guzewich↗
DOE OSTI2025

Remote-sensing detectability of airborne Arctic dust

Remote-sensing (RS)-based estimates of Arctic dust are oftentimes overestimated due to a failure in separating out the dust contribution from that of spatially homogeneous clouds or low-altitude cloud-like plumes. A variety of illustrations are given with a particular emphasis on questionable claims of using brightness temperature differences (BTDs) as a signature indicator of Arctic dust transported from mid-latitude deserts or generated by local Arctic sources. While there is little dispute about the presence of both Asian and local dust across the Arctic, the direct RS detectability of airborne dust, as ascribed to satellite (MODIS and AVHRR) measurements of significantly negative brightness temperature differences at 11 and 12 µm (BTD 11–12 ), has been misrepresented in certain cases. While it is difficult to account for all examples of strongly negative BTD 11–12 values in the Arctic, it is unlikely that airborne dust plays a significant role. One much more likely contributor would be water clouds in the Arctic inversion layer. The RS detectability of the impact of Arctic dust (notably due to Arctic dust from local sources) can, however, be of significance. Sustained dust deposition can substantially decrease (visible to shortwave IR) snow and ice reflectance albedo (pan-chromatic reflectance) and the signal measured by satellite sensors. Significantly negative BTD 11–12 values would, however, only represent a limited area near the drainage basin sources according to our event-level case studies. The enhanced ice-nucleating particle (INP) role of local Arctic dust can, for example, induce significant changes in the properties of low-level mixed-phase clouds (cloud optical depth changes <~ 1) that can readily be detected by active and passive RS instruments. It is critical that the distinction between the RS detectability of airborne Arctic dust versus the RS detectability of the impacts of that dust be understood if we are to appropriately parameterize, for example, the radiative forcing influence of dust in this climate-sensitive region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Climatology of Cloud‐Land‐Surface Coupling Across Different ARM Sites

Land-atmosphere interactions play a critical role in the evolution and formation of low-level clouds. The different states of coupling between low-level clouds and the surface are uncertain, primarily over continental regions, where complex thermodynamics complicates their investigation. This study uses observations from the Atmospheric Radiation Measurement User Facility to explore cloud-surface coupling and perform a climatological analysis of this interaction in five countries across three continents. The results reveal consistent coupling thresholds and average percentages across the five sites, with coupled clouds accounting for 66% of the cases and decoupled clouds for 34%. Thermodynamic and dynamic evaluations show distinct differences between coupled and decoupled clouds. Coupled clouds are characterized by humid environments, in which vertical motions connect the surface and lower atmosphere to the cloud base, conditions that favor the formation of boundary layer clouds. Decoupled clouds prefer to occur in a drier and colder environment with vertical motions inside the boundary layer being detached from the cloud base, under which boundary layer clouds are hard to form. Coupled clouds peak during warmer hours and seasons, and vice versa for decoupled clouds. This study underscores the complexity of cloud-land-surface interactions and paves the way for further investigations into cloud formation and evolution under different atmospheric environments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Radiative Structures of Lycopodium-Air Flames in Low Gravity

Initially uniform clouds of fuel particulates in air sustain processes which may lead to particle cloud nonuniformities. In low gravity, flame-induced Kundt's Tube phenomena are observed to form regular patterns of nonuniform particle concentrations. Irregular patterns of particle concentrations also are observed to result from selected nonuniform mixing processes. Low gravity flame propagation for each of these classes of particle cloud flames has been found to depend importantly on the flame-generated infrared radiative fields. The spatial structures of these radiative fields are described. Application is made for the observed clases of lycopodium-air flames.

Berlad, A. L.↗
DOE OSTI2025

Assessing Clouds in GFDL's AM4.0 With Different Microphysical Parameterizations Using the Satellite Simulator Package COSP

We evaluate cloud simulations using satellite simulators against multiple observational data sets. These simulators have been run within the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0), as well as an alternative configuration where a fully two‐moment Morrison‐Gettelman cloud microphysical parameterization with prognostic precipitation (MG2) is applied, denoted as AM4‐MG2. The modeled cloud spatial distributions, vertical profiles, phase partitioning, cloud‐to‐precipitation transitions, and radiative effects compare reasonably well with satellite observations. Model biases include the under‐prediction of total and low‐level clouds, especially optically thin/intermediate clouds with cloud optical depth of less than 23, but the over‐prediction of thick clouds, indicating “too few, too bright” biases. These biases counteract each other, and give rise to reasonable estimates of cloud radiative effects. The underestimate of low‐level clouds is associated with too early and too frequent drizzle/precipitation formation. The precipitation bias is improved in AM4‐MG2, where the autoconversion scheme initiates the precipitation more realistically. There also exist discrepancies between models and observations for midlevel and high‐level clouds. Additional biases include the underestimate of liquid cloud fraction and the overestimate of ice cloud fraction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Ham, Seung-Hee↗
NASA NTRS1984

The rationale and suggested approaches for research geosynchronous satellite measurements for severe storm and mesoscale investigations

The measurements from current and planned geosynchronous satellites provide quantitative estimates of temperature and moisture profiles, surface temperature, wind, cloud properties, and precipitation. A number of significant observation characteristics remain, they include: (1) temperature and moisture profiles in cloudy areas; (2) high vertical profile resolution; (3) definitive precipitation area mapping and precipitation rate estimates on the convective cloud scale; (4) winds from low level cloud motions at night; (5) the determination of convective cloud structure; and (6) high resolution surface temperature determination. Four major new observing capabilities are proposed to overcome these deficiencies: a microwave sounder/imager, a high resolution visible and infrared imager, a high spectral resolution infrared sounder, and a total ozone mapper. It is suggested that the four sensors are flown together and used to support major mesoscale and short range forecasting field experiments.

Shenk, W. E.↗
NASA NTRS2009

Sensitivity of Photolysis Frequencies and Key Tropospheric Oxidants in a Global Model to Cloud Vertical Distributions and Optical Properties

Clouds affect tropospheric photochemistry through modification of solar radiation that determines photolysis frequencies. As a follow-up study to our recent assessment of the radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties (cloud optical depths (CODs) and cloud single scattering albedo), in a global 3-D chemical transport model (GEOS-Chem). GEOS-Chem was driven with a series of meteorological archives (GEOS1- STRAT, GEOS-3 and GEOS-4) generated by the NASA Goddard Earth Observing System data assimilation system. Clouds in GEOS1-STRAT and GEOS-3 have more similar vertical distributions (with substantially smaller CODs in GEOS1-STRAT) while those in GEOS-4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. With random vertical overlap for clouds, the model calculated changes in global mean OH (J(O1D), J(NO2)) due to the radiative effects of clouds in June are about 0.0% (0.4%, 0.9%), 0.8% (1.7%, 3.1%), and 7.3% (4.1%, 6.0%), for GEOS1-STRAT, GEOS-3 and GEOS-4, respectively; the geographic distributions of these quantities show much larger changes, with maximum decrease in OH concentrations of approx.15-35% near the midlatitude surface. The much larger global impact of clouds in GEOS-4 reflects the fact that more solar radiation is able to penetrate through the optically thin upper-tropospheric clouds, increasing backscattering from low-level clouds. Model simulations with each of the three cloud distributions all show that the change in the global burden of ozone due to clouds is less than 5%. Model perturbation experiments with GEOS-3, where the magnitude of 3-D CODs are progressively varied from -100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2) and OH3 concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs due to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the ultraviolet wavelengths.

Liu, Hongyu↗
NASA NTRS2011

Cloud Macroscopic Organization: Order Emerging from Randomness

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Yuan, Tianle↗
NASA NTRS2022

Physical and Chemical Conditions in the N113 Star-Forming Region in the Low-Metallicity Large Magellanic Cloud

The Large Magellanic Cloud (LMC) is the nearest (~50 kpc) star-forming galaxy characterized by a low metallicity (Z~0.3-0.5 Z⨀) similar to galaxies during the early phases of their assembly. As a result, star formation studies in the LMC provide a stepping stone to understanding star formation at earlier epochs of the universe where these processes cannot be directly observed. N113 is one of the most prominent star-forming regions in the LMC hosting one of the most massive giant molecular clouds.N113 is small enough to be imaged in its entirety, but large enough to showcase many important phenomena such as multiple generations of stars, stellar feedback, and different environments. We present our findings from an investigation of the early stages of star formation in the N113 region using the Atacama Large Millimeter/submillimeter Array (ALMA)molecular line data probing a wide density range: 12CO, 13CO, and C18O (2-1), 13COand C18O (1-0), HCN (1-0), HCO+ (1-0), H13CN (1-0) and (3-2), H13CO+ (1-0) and (3-2), CS (2-1) and (5-4), as well as 1.3 mm and 3 mm continuum. We used the Python package quick clump to identify molecular clumps. We utilized the multiline non-LTE fitting tool based on models from RADEX developed by Finn et al. (2021, ApJ, 917, 106)to construct the CO, HCN, HCO+, and CS temperature and column density, and the H2density maps of N113. We constructed a catalog of molecular clumps including their physical properties, chemical abundances, sizes, velocities, and velocity dispersions. To establish the evolutionary status of the clumps, their positions were compared with previously identified young stellar objects (YSOs) from the Spitzer/SAGE and Herschel/HERITAGE surveys, as well as water and OH masers. We compared the properties of the clumps in N113 to those in the Galaxy and other regions in the LMC to assess the impact of the environment (e.g., metallicity, stellar feedback) on the star formation process.

Jonathon Noswitz↗
NASA NTRSDate not supplied

A Neural Network Parametrization of Volumetric Cloud Fraction Profiles Using Satellite Observations and MERRA-2 Reanalysis Meteorological Data

Clouds play a crucial role in regulating the hydrologic cycle and Earth's radiative energy budget, yet they are often poorly represented in global climate models (GCMs). This study applies deep machine learning techniques to develop a physical parameterization of volumetric cloud fraction (VCF), the fraction of a 3-D grid volume occupied by clouds using satellite lidar-radar measurements. The neural network (NN) captures the complicated relationships between observed VCF profiles and collocated meteorological variables from MERRA-2 reanalysis data. Our results show that the NN model, particularly a sequence-to-sequence long short-term memory (LSTM) network with a sixfactor loss function, effectively learns the underlying cloud physical processes. The NN model outperforms MERRA-2 reanalysis in representing low-level clouds in tropical and subtropical regions and low- and middle-level clouds over midlatitude storm-track regions, and also improves VCF histograms. These improvements are reflected in the vertical distributions of zonally, meridionally, and globally averaged VCFs, geographic distributions of low-, middle-, and high-level clouds, and seasonal variations in monthly-mean VCF. Furthermore, the NN predictions effectively capture the El Niño-Southern Oscillation (ENSO) effects and other interannual variations. The NN parameterization is further evaluated through a sensitivity analysis, in which a single predictor is perturbed at a time. This reveals that relative humidity (RH) is the dominant factor influencing variations in globally averaged VCF at low and middle altitudes, followed by temperature. At higher altitudes, temperature becomes the primary driver of VCF through its effect on RH. Changes in wind components had minimal impact on globally averaged VCF.

Shan Zeng↗
NASA NTRS2007

Simulation of Boundary-Layer Cumulus and Stratocumulus Clouds using a Cloud-Resolving Model With Low- and Third-Order Turbulence Closures

The effects of subgrid-scale condensation and transport become more important as the grid spacings increase from those typically used in large-eddy simulation (LES) to those typically used in cloud-resolving models (CRMs). Incorporation of these effects can be achieved by a joint probability density function approach that utilizes higher-order moments of thermodynamic and dynamic variables. This study examines how well shallow cumulus and stratocumulus clouds are simulated by two versions of a CRM that is implemented with low-order and third-order turbulence closures (LOC and TOC) when a typical CRM horizontal resolution is used and what roles the subgrid-scale and resolved-scale processes play as the horizontal grid spacing of the CRM becomes finer. Cumulus clouds were mostly produced through subgrid-scale transport processes while stratocumulus clouds were produced through both subgrid-scale and resolved-scale processes in the TOC version of the CRM when a typical CRM grid spacing is used. The LOC version of the CRM relied upon resolved-scale circulations to produce both cumulus and stratocumulus clouds, due to small subgrid-scale transports. The mean profiles of thermodynamic variables, cloud fraction and liquid water content exhibit significant differences between the two versions of the CRM, with the TOC results agreeing better with the LES than the LOC results. The characteristics, temporal evolution and mean profiles of shallow cumulus and stratocumulus clouds are weakly dependent upon the horizontal grid spacing used in the TOC CRM. However, the ratio of the subgrid-scale to resolved-scale fluxes becomes smaller as the horizontal grid spacing decreases. The subcloud-layer fluxes are mostly due to the resolved scales when a grid spacing less than or equal to 1 km is used. The overall results of the TOC simulations suggest that a 1-km grid spacing is a good choice for CRM simulation of shallow cumulus and stratocumulus.

Xu, Kuan-Man↗
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↗
NASA NTRS1977

Primeval gas clouds and the low-energy X-ray background

A model for the appearance of the all-sky low-energy X-ray background on a fine angular scale is presented which is based on primeval hot gas clouds associated with the formation of clusters of galaxies according to the Sunyaev-Zel'dovich (1972) model. It is noted that the background could have both granular and diffuse components if it is due to such gas clouds. The observed appearance of the granular component is predicted along with the observable characteristics of collapsing protoclusters. The effects of distant X-ray-emitting QSOs, radio galaxies, and normal galaxies on the observations are considered, and these sources are shown not to interfere with the possibility of observing the protoclusters. It is concluded that if sufficient heating occurred in an intracluster medium within some clusters of galaxies at the protocluster epoch, the ensemble properties of protoclusters could be observed with an X-ray telescope, and the time at which protoclusters formed could perhaps be estimated.

Kellogg, E. M.↗
NASA NTRS1988

The Nimbus-7 Global Cloud Climatology

The Nimbus-7 Global Cloud Climatology (N7GCC) has been produced from measurements made between April 1979 and March 1985 using the Temperature Humidity IR Radiometer and the Total Ozone Mapping Spectrometer on the Nimbus-7 satellite. The N7GCC gives, near local noon and midnight, the fractional area covered by high-level, middle-level, and low-altitude clouds, and the total fractional area covered by all clouds. Statistics for cirrus, deep convective, and warm low-altitude clouds and the cloud and clear-sky radiances with correlative surface temperatures are also included. The N7GCC is compared with other cloud data sets, including the International Satellite Cloud Climatology Project.

Hwang, Paul H.↗
DOE OSTI2025

Evaluating Entrainment–Mixing Characteristics through Direct Comparisons of Drop Size Distributions Using In Situ Observations from ACE-ENA

Abstract Constraining the impacts of entrainment and associated mixing (i.e., entrainment–mixing) on cloud properties continues to be difficult, partly due to observational uncertainties as well as a lacking consensus of which methodologies for diagnosing entrainment–mixing are most appropriate. This study introduces a novel method to evaluate the presence and degree of inhomogeneous and homogeneous mixing using ∼100 h of in situ observations from a research aircraft over the northeastern Atlantic. Specifically, drop size distributions are compared between regions containing negligible and significant entrainment for select flight legs, making a direct characterization of the degree of homogeneous and inhomogeneous mixing possible. A measure of drop concentration variance is used as a proxy variable to diagnose entrainment–mixing. Results correspond well with entrainment–mixing metrics, showing lower Damköhler numbers where drop size distributions shift toward smaller drop sizes (i.e., inhomogeneous mixing) and greater transition length scales where drop size distributions do not (i.e., homogeneous mixing). Inhomogeneous mixing occurs in most samples from Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) (regardless of homogeneous mixing frequencies increasing with increasing spatial resolution from ∼100 to ∼10 m) and is associated with decreased drop size relative dispersion and both greater aerosol and drop concentrations compared with homogeneous mixing. Precipitating clouds have a greater frequency of homogeneous mixing compared with nonprecipitating clouds. The proposed methodology is similarly applied to in situ observations of southeast Pacific stratocumulus, shallow convective clouds over central Oklahoma and low-level clouds over the Southern Ocean. All four locations are primarily dominated by inhomogeneous mixing with minimal variability among each region.

Clouds↗
NASA NTRS2005

Extinction coefficients from lidar observations in ice clouds compared to in-situ measurements from the Cloud Integrating Nephelometer during CRYSTAL-FACE

This paper presents a comparison of volume extinction coefficients in tropical ice clouds retrieved from two instruments : the 532-nm Cloud Physics Lidar (CPL), and the in-situ probe Cloud Integrating Nephelometer (CIN). Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements in ice clouds up to 17km. Coincident observations from three cloud cases are compared : one synoptically-generated cirrus cloud of low optical depth, and two ice clouds located on top of convective systems. Emphasis is put on the vertical variability of the extinction coefficient. Results show small differences on small spatial scales (approx. 100m) in retrievals from both instruments. Lidar retrievals also show higher extinction coefficients in the synoptic cirrus case, while the opposite tendency is observed in convective cloud systems. These differences are generally variations around the average profile given by the CPL though, and general trends on larger spatial scales are usually well reproduced. A good agreement exists between the two instruments, with an average difference of less than 16% on optical depth retrievals.

Noel, Vincent↗