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At least 595 records · Page 33

Translucent molecular clouds: Theory and observations

Few suitable stars behind molecular clouds have been identified. A limited survey was performed of interstellar lines toward highly reddened stars in the southern sky, using the ESO 1.4 m CAT telescope with a Reticon detector, and the Cerro Tololo 4 m telescope equipped with a GEC charge coupled device (CCD) detector. Because of the reduced extinction at longer wavelengths, molecules were searched for with transitions in the red part of the spectrum such as C2 and CN. For some lines-of-sight for which C2 was detected, the 4300 A line of CH was also observed. Absorption lines of interstellar C2 around 8750 A were detected in the spectra of about 1/4 of the 36 observed stars. The inferred C2 column densities range between 10 to the 13th power and 10 to the 14th power sq. cm., and are up to an order of magnitude larger than those found for diffuse clouds. The observed column densities of CH correlate very well with those of C2 over this range. In contrast, the measured column densities of CN vary by orders of magnitude between the various regions, and they do not correlate with those of C2 and CH. The observed rotational population distribution of C2 also provides information about the physical conditions in the clouds. Models of translucent molecular clouds have been constructed along the lines described by van Dishoeck and Black (1986) for diffuse clouds. The models compute accurately the fractions of atomic and molecular hydrogen as functions of depth into the clouds, as well as the excitation of H2 by ultraviolet pumping. They also incorporate a detailed treatment of the photodissociation processes of the molecules (cf. van Dishoeck 1986), which play an important role in the chemistry up to depths of about 3 mag.

Vandishoeck, E. F.↗

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Tao, W. K.↗

A modeling analysis program for the JPL table mountain Io sodium cloud data

Research in the third and final year of this project is divided into three main areas: (1) completion of data processing and calibration for 34 of the 1981 Region B/C images, selected from the massive JPL sodium cloud data set; (2) identification and examination of the basic features and observed changes in the morphological characteristics of the sodium cloud images; and (3) successful physical interpretation of these basic features and observed changes using the highly developed numerical sodium cloud model at AER. The modeling analysis has led to a number of definite conclusions regarding the local structure of Io's atmosphere, the gas escape mechanism at Io, and the presence of an east-west electric field and a System III longitudinal asymmetry in the plasma torus. Large scale stability, as well as some smaller scale time variability for both the sodium cloud and the structure of the plasma torus over a several year time period are also discussed.

Smyth, William H.↗

The ultraviolet absorber on Venus - Amorphous sulfur

It is pointed out that the identity of the chemical species responsible for the yellow coloration of the clouds of Venus and for the dark features which dapple the planet at ultraviolet wavelengths has long been a mystery. Independent pieces of evidence, discovered recently, suggest now that amorphous sulfur is the so-called UV absorber. A review of earlier ideas and controversies is presented, and attention is given to a new physical-chemical model of the Venus clouds which shows that sulfur should form there. A description is provided of physical characteristics of the cloud particles that, in comparison with model predictions, indicate the presence of sulfur. Optical data suggesting that elemental sulfur occurs in the clouds is discussed, and cloud morphological evidence for sulfur is considered.

Toon, O. B.↗

Changes in IDP mineralogy and composition by terrestrial factors

Major objectives in the study of interplanetary dust particles (IDP's) are to constrain the physical and chemical conditions in the early solar system, to characterize the particles making up the zodiacal cloud, and to infer the physical, chemical, mineralogical, and isotopic properties of IDP parent bodies: the comets and the asteroids. However, the effects of terrestrial interactions alter the properties of some IDP's from those of the zodiacal cloud particles. The interactions can be separated into four distinct phases: near-earth gravitational segregation, atmospheric entry deceleration, stratospheric residence, and the collection/curation process.

Flynn, George J.↗

The energetics of molecular clouds. I - Methods of analysis and application to the S255 molecular cloud

Observations of the S255 molecular cloud in the radio lines of CO, (C-13)O, and H2O as well as in the IR region from 12 to 20 microns are presented. These results show that an extended molecular cloud is associated with the optically visible H II regions S255 - S257, both the kinetic temperature and molecular density are enhanced in an area centered on a compact near-IR source, this source is also coincident with an OH and an H2O maser (within the errors), and the IR source exhibits the silicon absorption feature. First-order techniques which allow physical properties of molecular clouds to be estimated and the energetics of the gas and dust in the clouds to be analyzed are developed and applied to S255. It is concluded that: (1) the gas cooling rate is much less than the dust cooling rate; (2) the primary energy flow is in the IR through dust emission over a range of temperatures; (3) the near-IR source is apparently responsible for the local peak in gas kinetic temperature; and (4) the exciting stars of nearby H II regions appear to be the primary heat sources for the overall molecular cloud.

Evans, N. J., II↗

The abundance of CO in diffuse interstellar clouds - An ultraviolet survey

CO was detected in 17 directions and its upper limits were estimated in 21 directions by a UV survey carried out with the Copernicus satellite in the C-X 1088 A and E-X 1076 A lines toward 48 bright stars. The CO column densities range from 10 to the 12th to 10 to the 17th/sq cm and correlate with C I and H2. The tendency of the C I/CO ratio to be about 10 follows the ratio of particular atomic and molecular cross-sections and the physical parameters of interstellar clouds. Finally, the connection between UV observations in diffuse clouds and radio observations of (C-13)O in dark clouds is discussed.

Federman, S. R.↗

An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties

Atmospheric remote sensing with the O2 A-band has a relatively long history, but most of these studies were attempting to estimate surface pressure or cloud-top pressure. Recent conceptual studies have demonstrated the potential of spaceborne high spectral resolution O2 A-band spectrometers for retrieval of aerosol and cloud optical properties. The physical rationale of this new approach is that information on the scattering properties of the atmosphere is embedded in the detailed line structure of the O2 A-band reflected radiance spectrum. The key to extracting this information is to measure the radiance spectrum at very high spectral resolution. Instrument performance requirement studies indicate that, in addition to high spectral resolution, the successful retrieval of aerosol and cloud properties from A-band radiance spectra will also require high radiometric accuracy, instrument stability, and high signal-to-noise measurements. To experimentally assess the capabilities of this promising new remote sensing application, the NASA Langley Research Center is developing an airborne high spectral resolution A-band spectrometer. The spectrometer uses a plane holographic grating with a folded Littrow geometry to achieve high spectral resolution (0.5 cm-1) and low stray light in a compact package. This instrument will be flown in a series of field campaigns beginning in 2001 to evaluate the overall feasibility of this new technique. Results from these campaigns should be particularly valuable for future spaceborne applications of A-band spectrometers for aerosol and cloud retrievals.

Pitts, Michael↗

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of large-scale computational discovery carried through experimental validation remain scarce, especially for materials with product applicability. In this paper, we demonstrate how this vision became reality by first combining state-of-the-art artificial intelligence (AI) models and traditional physics-based models on cloud high performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. Focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade’s worth of collective knowledge in the field as a byproduct. By employing around one thousand virtual machines in the cloud, this process took less than 80 hours. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the Na x Li 3-x YCl 6 (0.5 ≤ x ≤ 2.5) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials are currently under experimental investigation that could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. We believe this unprecedented approach of synergistically integrating AI models and cloud HPC not only accelerates materials discovery but also showcases the potency of AI-guided experimentation in unlocking transformative scientific breakthroughs with real-world applications.

36 MATERIALS SCIENCE↗

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗

C3H2 observations as a diagnostic probe for molecular clouds

Recently the three-membered ring molecule, cyclopropenylidene, C3H2, has been identified in the laboratory and detected in molecular clouds by Thaddeus, Vrtilek and Gottlieb (1985). This molecule is wide-spread throughout the Galaxy and has been detected in 25 separate sources including cold dust clouds, circumstellar envelopes, HII regions, and the spiral arms observed against the Cas supernova remnant. In order to evaluate the potential of C3H2 as a diagnostic probe for molecular clouds, and to attempt to identify the most useful transitions, statistical equilibrium calculations were carried out for the lowest 24 levels of the ortho species and the lowest 10 levels of the para species. Many of the sources observed by Matthews and Irvine (1985) show evidence of being optically thick in the 1(10)-1(01) line. Consequently, the effects of radiative trapping should be incorporated into the equilibrium calculations. This was done using the Large Velocity Gradient approximation for a spherical cloud of uniform density. Some results of the calculations for T(K)=10K are given. Figures are presented which show contours of the logarithm of the ratio of peak line brightness temperatures for ortho-para pairs of lines at similar frequencies. It appears that the widespread nature of C3H2, the relatively large strength of its spectral lines, and their sensitivity to density and molecular abundance combine to make this a useful molecule for probing physical conditions in molecular clouds. The 1(10)-1(01) and 2(20)-2(11) K-band lines may be especially useful in this regard because of the ease with which they are observed and their unusual density-dependent emission/absorption properties.

Avery, L. W.↗

Cloud interactions and merging - Numerical simulations

A total of 48 numerical experiments have been performed to study cloud interactions adn merging by means of a two-dimensional multi-cell model. Two soundings of deep convection during GATE and two different magnitudes of large-scale lifting have been used as the initial conditions and as the main forcing on the model. Over two hundred groups of cloud systems with a life history of over sixty minutes have been generated under the influence of different combinations of the stratification and large-scale lifting. The results demonstrate the increase in convective activity and in amount of precipitation with increased intensity of large-scale lifting. The results also show increased occurrence of cloud merger with increased intensity of large-scale lifting. The most unfavorable environmental conditions for cloud merging are (1) less unstable stratification of the atmosphere and (2) weaker large-scale lifting. A total of fourteen cloud systems qualify as mergers. Two selected cases will be described dynamically and thermodynamically in this paper. Although these cloud mergers have been simulated under the influence of different synoptic-scale conditions, the major physical mechanism related to the cloud merging process is the same as that proposed by Simpson. Cumulus downdrafts and associated cold outflows play a dominant role in the merging process in all cases studied.

Tao, W.-K.↗

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗

Investigating Sensitivity to Saharan Dust in Tropical Cyclone Formation Using Nasa's Adjoint Model

As tropical cyclones develop from easterly waves coming of the coast of Africa they interact with dust from the Sahara desert. There is a long standing debate over whether this dust inhibits or advances the developing storm and how much influence it has. Dust can surround the storm and absorb incoming solar radiation, cooling the air below. As a result an energy source for the system is potentially diminished, inhibiting growth of the storm. Alternatively dust may interact with clouds through micro-physical processes, for example by causing more moisture to condense, potentially increasing the strength. As a result of climate change, concentrations and amount of dust in the atmosphere will likely change. It it is important to properly understand its effect on tropical storm formation. The adjoint of an atmospheric general circulation model provides a very powerful tool for investigating sensitivity to initial conditions. The National Aeronautics and Space Administration (NASA) has recently developed an adjoint version of the Goddard Earth Observing System version 5 (GEOS-5) dynamical core, convection scheme, cloud model and radiation schemes. This is extended so that the interaction between dust and radiation is also accounted for in the adjoint model. This provides a framework for examining the sensitivity to dust in the initial conditions. Specifically the set up allows for an investigation into the extent to which dust affects cyclone strength through absorption of radiation. In this work we investigate the validity of using an adjoint model for examining sensitivity to dust in hurricane formation. We present sensitivity results for a number of systems that developed during the Atlantic hurricane season of 2006. During this period there was a significant outbreak of Saharan dust and it is has been argued that this outbreak was responsible for the relatively calm season. This period was also covered by an extensive observation campaign. It is shown that the adjoint can provide insight into the sensitivity and reveals a relatively low sensitivity to dust compared to, for example, the thermodynamic variables. However a secondary sensitivity though moisture is seen. If dust dries the air it can significantly reduce the cyclone intensity through the moisture.

Tropical Cyclones↗

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) 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. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

Tao, Wei-Kuo↗

CO observations of dark clouds in Lupus

C-12O observations covering 170 square degrees toward the southern T Association Lupus have revealed the presence of an extended physically related complex of dark clouds which have recently formed low mass stars. The estimated mass of the clouds (about 30,000 solar masses) is comparable to that of the nearby Ophiuchus dust clouds. The Lupus clouds are projected onto a gap between two subgroups of the Scorpio-Centaurus OB association suggesting that this long accepted subgrouping may require reinterpretation.

Murphy, D. C.↗

Silicon chemistry in interstellar clouds

A new model of interstellar silicon chemistry is presented that explains the lack of SiO detections in cold clouds and contains an exponential temperature dependence for the SiO abundance. A key aspect of the model is the sensitivity of SiO production by neutral silicon reactions to density and temperature, which arises from the dependence of the rate coefficients on the population of the excited fine-structure levels of the silicon atom. As part of the explanation of the lack of SiO detections at low temperatures and densities, the model also emphasizes the small efficiencies of the production routes and the correspondingly long times needed to reach equilibrium. Measurements of the abundance of SiO, in conjunction with theory, can provide information on the physical properties of interstellar clouds such as the abundance of oxygen bearing molecules and the depletion of interstellar silicon.

Langer, William D.↗

CRADA Number NFE-20-08292 with Quantum Lock Technologies LLC (CRADA Final Report)

At Quantum Lock Technologies, our mission is to use future-proof hardware and software to bridge the gap between physical access control and cyber security. Physical security includes access to doors, lockboxes/containers, and machinery/robots. Connecting physical access control to the cloud allows for remote detection, fast ledger updates, and mobile or remote access. However, this also opens physical security up to the world of cyber-attacks. At Quantum Lock, we use quantum random number generation to generate completely random and unpredictable digital keys to be used by connected equipment in a facility. This quantum technology is then paired with end-to-end encryption and a one-time-key communication protocol to ensure the highest level of security. Through the Innovation Crossroads program at Oak Ridge National Laboratory, we have developed benchtop prototypes of our technology, connected with utility boards as our first target customers, and prepared for our first pilot with customers (target end of summer 2022).

97 MATHEMATICS AND COMPUTING↗