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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 451 records · Page 25

Mesoscale Organization in Cumulus-Coupled Stratocumulus

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

54 ENVIRONMENTAL SCIENCES↗

Comparison of Three Multicylinder Icing Meters and Critique of Multicylinder Method

Three multicylinder cloud meters, fundamentally similar but differing in important details, were compared in use at the Mount Washington Observatory. Determinations of liquid water content were found to agree within the limits of the probable error, but the two instruments designed by the National Advisory Committee for Aeronautics indicated larger drop sizes than did the Observatory's instrument, apparently because of spurious ice catch on the rather rough surface of the larger cylinders. Comparisons of drop-size distribution were largely indeterminate., In a critique of the method, the probable error of determination of liquid water content was found to be +/-8 percent; of drop size, +/-6 percent; and of drop-size distribution, about +/-0.7 unit of the modulus of distribution. Of the systematic errors, run-off of unfrozen water is most important, blow-off and erosion seldom being hampering. Revision of collection-efficiency computations for cylinders in clouds with distributed drop sizes was found necessary and also revision of one of the correction-factor graphs heretofore used. The assumption of constant ice density in deriving cylinder size was found to be permissible for cylinders 1 inch or more in diameter.

Howell, Wallace E.↗

The spectral correlation of functional clouds: a statistical test for theoretical models

We compute the spectral correlation function (SCF) of CO J=1-0 maps of moleculary cloud complexes. The SCF is a power law over approximately an order of magnitude in spatial separation in every map. The power law slope of the SCF, its normalization, and the spectral line width averaged over the whole map, are computed for all the observational maps.

turbulence kinematics↗

The Martian polar cap - Radiative effects of ozone, clouds, and airborne dust

The solar and thermal flux striking the polar cap of Mars is computed for various ozone, dust, and cloud abundances and for three solar zenith angles. Ozone does not significantly affect the total energy budget of the polar cap. Hence the observed hemispherical asymmetry in ozone abundance causes only an insignificant hemispherical asymmetry in the polar caps. Vertical optical depths of dust and cloud ranging from zero to 1 cause little change in the total flux absorbed by the polar cap near its edge but increase the absorbed flux significantly as one travels poleward. Hemispherical asymmetries in dust abundance, cloud cover, and surface pressure combine to cause a significant hemispherical asymmetry in the total flux absorbed by the residual polar caps, which helps to explain the dichotomy in the residual polar caps on Mars. Other processes which affect the energy budget of the polar cap are proposed and reviewed, particularly with respect to their interaction with the radiative effects of clouds and dust.

Lindner, Bernhard Lee↗

A Multi-Scale Modeling System with Unified Physics

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique.

Tao, Wei-Kuo↗

Classification of Cloud Particle Imagery and Thermodynamics (COCPIT): A New Databasing Tool for the Characterization of Cloud Particle Images Captured During DOE Field Campaigns

The Department of Energy for decades has explored the earth system and atmosphere through research and deployment of in-situ and remote sensing platforms during field campaigns. Among these datasets exists a vast supply of cloud particle images that provide visual insight into the complex microphysics in the clouds that span our globe. The millions of images collected over decades of deployments provides a unique opportunity to further our understanding of our atmosphere down to the crystal size. This work over the past 5 years has sought to organize these images into digestible datasets that can then be used by scientists to further our understanding of microphysics. A machine learning model was developed that categorizes over 1.5 million images across 11 weather events with over 90% accuracy according to particle type. The database was then extended to include dimensional characteristics of the particle as well as co-location of environmental properties, such as temperature and water content. Then, to initialize the connection between these data and our understanding of how crystals form and grow, weather research and forecasting simulations were run to generate the growth histories of the classified crystals. This research culminates with 2 databases per event: (1) a database of all classified crystals and their dimensional and environmental properties and (2) simulated growth histories of each crystal. Finally, a user interface was created to allow researchers to explore data statistics.

54 ENVIRONMENTAL SCIENCES↗

Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

Cloud Computing↗

Light scattering by ice clouds in the visible and infrared - A theoretical study.

Computations of the intensity and linear polarization for single scattering by ice clouds have been made based on the assumption that the particles in ice clouds can be approximated by long circular cylinders which are allowed to be polydispersive as well as arbitrarily oriented in space. The results of two models of optically thin ice clouds are presented and compared with those for polydisperse ice spheres. The two models for ice cylinders are assumed to be either uniformly or randomly oriented in a horizontal plane. Four different wavelengths, 0.7, 3, 3.5 and 6.05 microns, are employed in the light scattering computations. It is found that, compared to ice spheres, long ice cylinders scatter more light in the region with scattering angles near 90 deg, at the expense of scattering in both the forward and backward directions. The glory and cloudbows, which occur in light scattered by spherical particles, are either lost (the glory) or largely reduced and distorted (the cloudbows in the case of cylinders). It is probable that for more irregular particles the cloudbows would also disappear. These differences in scattering by spherical and non-spherical scatterers therefore provide useful information for the differentiation between the ice and liquid phase of cloud particles.

Liou, K.-N.↗

Efficient estimation of the modified Gromov–Hausdorff distance between unweighted graphs

Abstract Gromov–Hausdorff distances measure shape difference between the objects representable as compact metric spaces, e.g. point clouds, manifolds, or graphs. Computing any Gromov–Hausdorff distance is equivalent to solving an NP-hard optimization problem, deeming the notion impractical for applications. In this paper we propose a polynomial algorithm for estimating the so-called modified Gromov–Hausdorff (mGH) distance, a relaxation of the standard Gromov–Hausdorff (GH) distance with similar topological properties. We implement the algorithm for the case of compact metric spaces induced by unweighted graphs as part of Python library , and demonstrate its performance on real-world and synthetic networks. The algorithm finds the mGH distances exactly on most graphs with the scale-free property. We use the computed mGH distances to successfully detect outliers in real-world social and computer networks.

Oles, Vladyslav (ORCID:0000000188727463)↗

Workflow Provenance in the Computing Continuum for Responsible, Trustworthy, and Energy-Efficient AI

As Artificial Intelligence (AI) becomes more pervasive in our society, it is crucial to develop, deploy, and assess Responsible and Trustworthy AI (RTAI) models, i.e., those that consider not only accuracy but also other aspects, such as explainability, fairness, and energy efficiency. Workflow provenance data have historically enabled critical capabilities towards RTAI. Provenance data derivation paths contribute to responsible workflows through transparency in tracking artifacts and resource consumption. Provenance data are well-known for their trustworthiness helping explainability, reproducibility, and accountability. However, there are complex challenges to achieve RTAI, which are further complicated by the heterogeneous infrastructure in the computing continuum (Edge-Cloud-HPC) used to develop and deploy models. As a result, a significant research and development gap remains between workflow provenance data management and RTAI. In this paper, we present a vision of the pivotal role of workflow provenance in supporting RTAI and discuss related challenges. We present a schematic view between RTAI and provenance, and highlight open research directions.

Santos Souza, Renan↗

Effect of atmospheric scattering and surface reflection on upwelling solar radiation

A study is presented of the solar radiation transfer in the complete earth-atmosphere system, and numerical results are compared with satellite data obtained during the Earth Radiation Budget Experiment on Nimbus 6, in August, 1975. Emphasis is placed on the upwelling radiance distribution at the top of the atmosphere, assumed to be at 50 km. The numerical technique is based on the finite difference method, which includes azimuth and spectral variations for the entire solar wavelength range. Detailed solar properties, atmospheric physical properties, and optical properties are used. However, since the property descriptions are based on a trade-off between accuracy and computational realities, aerosol and cloud optical properties are treated with simple approximations. The radiative transfer model is in good agreement with the satellite radiance observations. The method provides a valuable tool in analyzing satellite- and ground-based radiation budget measurements and in designing instrumentation.

Suttles, J. T.↗

Comments on satellite meteorology from geostationary satellites

Examples of the use of geostationary satellites in meteorology are given. Studies of the rate of change of cumulus clouds and cloud systems and wind parameter determination from cloud motions are reviewed. Computer processed imagery products are also discussed.

Vonderhaar, T. H.↗

Progress toward the origin of the solar system

In recent years, considerable progress has been made toward understanding the origin of the solar system. There exists a broad consensus that the planets are derived from a nebular disk which formed with the sun itself. There are, however, disagreements regarding the assumed mass of the solar nebula. Estimates range from a few percent of the sun's mass, the minimum required to make the planets, up to one solar mass. The two extremes lead to very different models of planet formation. The general problem of star formation is considered, taking into account the production of a circumsolar disk nebula due to angular momentum in the protostellar cloud. Collapse of a rotating cloud is modeled by computer codes. Attention is given to the chemical evidence concerning the solar nebula, relations regarding planetesimals and terrestrial planets, and protoplanets and giant planets.

Weidenschilling, S. J.↗

The energy distributions of B supergiants in the Large Magellanic Cloud

It is shown that line-blanketed, LTE, plane-parallel model atmosphere calculations provide excellent fits to the ultraviolet-through-visual energy distributions of B supergiants in the Large Magellanic Cloud. The models were computed using Kurucz's (1979) ATLAS atmosphere program, but with lower gravities than were contained in Kurucz's published model grid. The ultraviolet continua of low gravity stars are found to be sensitive to changes in temperature and gravity. Measurements of Teff and log g for ten LMC B supergiants from model atmosphere fits to the energy distributions yield estimates of their radii, luminosities, and masses. Model atmosphere fits suggest that the late B supergiants have significantly lower masses than the earlier B types of the same luminosity, contrary to stellar evolution theory which predicts that B supergiants are in a post-core hydrogen burning phase and should evolve very quickly and at essentially constant mass.

Fitzpatrick, Edward L.↗

SHDOM

SHDOM is a general purpose, publicly available, three-dimensional atmospheric radiative transfer model. SHDOM is an explicit method, which means it solves for the whole radiation field, as distinct from Monte Carlo methods which solve for particular radiative outputs. SHDOM is particularly well suited for remote sensing applications, where it can compute outgoing radiances at many angles from a cloud field at virtually no extra cost. SHDOM is not appropriate for calculating domain average quantities for which Monte Carlo methods excel. The I3RC intercomparison offers an opportunity to explore the pros and cons of SHDOM and Monte Carlo models on some real world inhomogeneous cloud fields. Specifically, we wish to determine the computer resources required to achieve a particular accuracy for a certain number of outputs using SHDOM and Monte Carlo models. This will help guide modelers on the appropriate choice of SHDOM or Monte Carlo for their applications. To emphasize the importance of this accuracy versus CPU time tradeoff, we are submitting two SHDOM entries (low and high resolution) in the I3RC.

Evans, K. Franklin↗

Cloud Detection Using Measured and Modeled State Parameters

In this study, hourly RUC analyses were used to examine the differences between RH and temperature values from RUC reanalysis data and from radiosonde atmospheric profiles obtained at the ARM SCF. The results show that the temperature observations from the SONDE and RUC are highly correlated. The RHs are also well-correlated, but the SONDE values generally exceed those from RUC. Inside cloud layers, the RH from RUC is 2-14% lower than the RH from SONDE for all RUC layers. Although the layer mean RH within clouds is much greater than the layer mean RH outside cloud or in the clear-sky, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either dataset. For overcast clouds, it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer is roughly 90% for the Vaisala RS80-15LH radisonde and 80% for RUC data. While for the partial cloud (cloud amount is less than 90%), the RH thresholds of SONDE are close to RUC for a given probability in upper tropospheric layers. The probabilities of detecting clouds at a given RH and temperature should be useful for a variety of application such as the development of new cloud parameterizations or for estimating the vertical profile of cloudiness underneath a given cloud observed from the satellite to construct a 3-D cloud data set for computing atmospheric radiative heating profiles or determining potential aircraft icing conditions.

Yi, Y.↗