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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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299 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

A Texture-Polarization Method for Estimating Convective/Stratiform Precipitation Area Coverage from Passive Microwave Radiometer Data

Observational and modeling studies have described the relationships between convective/stratiform rain proportion and the vertical distributions of vertical motion, latent heating, and moistening in mesoscale convective systems. Therefore, remote sensing techniques which can quantify the relative areal proportion of convective and stratiform, rainfall can provide useful information regarding the dynamic and thermodynamic processes in these systems. In the present study, two methods for deducing the convective/stratiform areal extent of precipitation from satellite passive microwave radiometer measurements are combined to yield an improved method. If sufficient microwave scattering by ice-phase precipitating hydrometeors is detected, the method relies mainly on the degree of polarization in oblique-view, 85.5 GHz radiances to estimate the area fraction of convective rain within the radiometer footprint. In situations where ice scattering is minimal, the method draws mostly on texture information in radiometer imagery at lower microwave frequencies to estimate the convective area fraction. Based upon observations of ten convective systems over ocean and nine systems over land, instantaneous 0.5 degree resolution estimates of convective area fraction from the Tropical Rainfall Measuring Mission Microwave Imager (TRMM TMI) are compared to nearly coincident estimates from the TRMM Precipitation Radar (TRMM PR). The TMI convective area fraction estimates are slightly low-biased with respect to the PR, with TMI-PR correlations of 0.78 and 0.84 over ocean and land backgrounds, respectively. TMI monthly-average convective area percentages in the tropics and subtropics from February 1998 exhibit the greatest values along the ITCZ and in continental regions of the summer (southern) hemisphere. Although convective area percentages. from the TMI are systematically lower than those from the PR, monthly rain patterns derived from the TMI and PR rain algorithms are very similar. TMI rain depths are significantly higher than corresponding rain depths from the PR in the ITCZ, but are similar in magnitude elsewhere.

Olson, William S.↗
NASA NTRS2006

A Numerical Study of Hurricane Erin (2001): Model Verification and Storm Evolution - Part 1

The fifth-generation Pennsylvania State University National Center for Atmospheric Research (PSU NCAR) Mesoscale Model (MM5) is used to simulate Hurricane Erin (2001) at high resolution (4-km spacing) from its early development as a tropical depression on 7 September 2001, through a period of rapid intensification into a strong hurricane (8 9 September), and finally into a stage during which it maintains its intensity on 10 September. These three stages of formation, intensification, and maintenance in the simulation are in good agreement with the observed evolution of Erin. The simulation shows that during the formation and early portions of the intensification stages, intensification is favored because the environmental wind shear is weak and the system moves over a warm tongue of water. As Erin intensifies, the wind shear gradually increases with the approach of an upper-level trough and strengthening of a low-level high pressure system. By 10 September, the wind shear peaks and begins to decrease, the storm moves over slightly cooler waters, and the intensification ends. Important structural changes occur at this time as the outer precipitation shifts from the northeastern and eastern sides to the western side of the eye. A secondary wind maximum and an outer eyewall begin to develop as precipitation begins to surround the entire eye. The simulation is used to investigate the role of vertical wind shear in the changes of the precipitation structure that took place between 9 and 10 September by examining the effects of changes in storm-relative flow and changes in the shear-induced tilt. Qualitative agreement is found between the divergence pattern and advection of vorticity by the relative flow with convergence (divergence) generally associated with asymmetric inflow (outflow) in the eyewall region. The shift in the outer precipitation is consistent with a shift in the low-level relative inflow from the northeastern to the northwestern side of the storm. The changes in the relative flow are associated with changes in the environmental winds as the hurricane moves relative to the upper trough and the low-level high pressure system. Examination of the shear-induced tilt of the vortex shows that the change in the tilt direction is greater than that of the shear direction as the tilt shifts from a northerly orientation to northwesterly. Consistent with theory for adiabatic vortices, the maximum low-level convergence and upper-level divergence (and the maximum upward motion) occurs in the direction of tilt. Consequently, both mechanisms may play roles in the changes in the precipitation pattern.

Wu, Liguang↗
NASA NTRS2003

A Numerical Study of Hurricane Erin (2001): Model Verification and Storm Evolution - Part 1

The Pennsylvania State University-National Center for Atmospheric Research mesoscale model MM5 is used to simulate Hurricane Erin (2001) at high resolution (4-km spacing) from its early development as a tropical depression on 7 September 2001, through a period of rapid intensification into a strong hurricane (8-9 September), and finally into a stage during which it maintains its intensity on 10 September. These three stages of development, intensification, and maintenance in the simulation are in good agreement with the observed evolution of Erin. The simulation shows that during the development and early portions of the intensification stages, intensification is favored because the environmental wind shear is weak and the system moves over a warm tongue of water. As Erin intensifies, the wind'shear gradually increases with the approach of an upper-level trough and strengthening of a low-level high pressure system. By 10 September, the wind shear peaks and begins to decrease, the storm moves over slightly cooler waters, and the intensification ends. Important structural changes occur at this time as the outer precipitation shift from the northeastern and eastern sides to the western side of the eye and precipitation begins to surround the entire eye to initiate the development of a secondary wind maximum and an outer eyewall. The simulation is used to investigate the role of vertical wind shear in the changes of the precipitation structure that took place between 9-10 September by examining the effects of both storm-relative flow changes and changes in the shear-induced tilt. Qualitative agreement is found between the divergence pattern and advection of vorticity by the relative flow with convergence (divergence) generally associated with asymmetric inflow (outflow) in the eyewall region. The shift in the outer precipitation is consistent with a shift in the low-level relative inflow from the northeastern to the northwestern side of the storm. The changes in the relative flow are associated with changes in the winds as the hurricane moves relative to the upper tough and the low-level high pressure system. Examination of the shear-induced tilt of the vortex shows that the change in the tilt direction is greater than that of the shear direction as the tilt shifts from a northerly orientation to northwesterly. Consistent with theory for adiabatic vortices, the maximum low-level convergence and upper-level divergence (and the maximum upward motion) occurs in the direction of tilt. Consequently, both mechanisms may play roles in the changes in the precipitation pattern.

Wu, Liquang↗
DOE OSTI2024

TRACER Perspectives on Gulf-Breeze and Bay-Breeze Circulations and Coastal Convection

Abstract This study explores gulf-breeze circulations (GBCs) and bay-breeze circulations (BBCs) in Houston–Galveston, investigating their characteristics, large-scale weather influences, and impacts on surface properties, boundary layer updrafts, and convective clouds. The results are derived from a combination of datasets, including satellite observations, ground-based measurements, and reanalysis datasets, using machine learning, changepoint detection method, and Lagrangian cell tracking. We find that anticyclonic synoptic patterns during the summer months (June–September) favor GBC/BBC formation and the associated convective cloud development, representing 74% of cases. The main Tracking Aerosol Convection Interactions Experiment (TRACER) site located close to the Galveston Bay is influenced by both GBC and BBC, with nearly half of the cases showing evident BBC features. The site experiences early frontal passages ranging from 1040 to 1630 local time (LT), with 1300 LT being the most frequent. These fronts are stronger than those observed at the ancillary site which is located further inland from the Galveston Bay, including larger changes in surface temperature, moisture, and wind speed. Furthermore, these fronts trigger boundary layer updrafts, likely promoting isolated convective precipitating cores that are short lived (average convective lifetime of 63 min) and slow moving (average propagation speed of 5 m s −1 ), primarily within 20–40 km from the coast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Barium titanate nanoparticles: Short-range lattice distortions with long-range cubic order

Barium titanate (BTO) nanoparticles (sizes 10 to 500 nm) exhibit a displacement of the Ti atom from the center of the Perovskite unit cell as inferred from synchrotron X-ray diffraction patterns (XRD) analyzed using atomic pair distribution functions (PDFs). Fits to PDFs acquired at temperatures of 20° to 220°C indicate that these Ti displacements (~ 0.1 Å) are comparable to or even greater than those in the bulk material. Moreover, these displacements persist at temperatures well above 120°C where the tetragonal to pseudo-cubic phase transition occurs in the bulk. Tetragonal Raman spectral lines were observed for all sizes of these BTO nanoparticles and confirm a distorted unit cell up to 120°C. Above 120°C, the small BTO nanoparticles (10, 50, 100 nm) continue to display tetragonal Raman lines, though with slowly decreasing amplitudes as the temperature rises. In contrast, the tetragonal Raman lines of large BTO nanoparticles (300, 400, 500 nm) disappear abruptly above 120°C, suggestive of bulk material. Indeed, fits to large-particle X-ray PDFs over the range 20-60 Å reveal a sharp, long-range structural change toward a cubic lattice at 120°C, again consistent with bulk material. This sharp, long-range structural change is absent in the small particles. In fact, laboratory XRD Bragg peak profiles for the small BTO particles appear to be singlets at 20°C, indicating that significant long-range cubic order already exists at room temperature. As temperature rises, this long-range cubic order is gradually reinforced as inferred from long-range fits of the small particle PDFs. By combining information from X-ray PDFs, Raman spectra, and Bragg peak profiles, we conclude that small BTO nanoparticles exhibit both short-range (unit-cell) distortion and long-range (mesoscale) cubic order from 20° to 220°C, while the large nanoparticles behave as bulk material, differing from small particles only by exhibiting long-range tetragonal order below 120°C and a mesoscale structural phase change at 120°C.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Mesoscale martensitic transformation in single crystals of topological defects

Liquid-crystal blue phases (BPs) are highly ordered at two levels. Molecules exhibit orientational order at nanometer length scales, while chirality leads to ordered arrays of double-twisted cylinders over micrometer scales. Past studies of polycrystalline BPs were challenged by the existence of grain boundaries between randomly oriented crystalline nanodomains. Here, the nucleation of BPs is controlled with precision by relying on chemically nanopatterned surfaces, leading to macroscopic single-crystal BP specimens where the dynamics of mesocrystal formation can be directly observed. Theory and experiments show that transitions between two BPs having a different network structure proceed through local reorganization of the crystalline array, without diffusion of the double-twisted cylinders. In solid crystals, martensitic transformations between crystal structures involve the concerted motion of a few atoms, without diffusion. The transformation between BPs, where crystal features arise in the submicron regime, is found to be martensitic in nature when one considers the collective behavior of the double-twist cylinders. Single-crystal BPs are shown to offer fertile grounds for the study of directed crystal nucleation and the controlled growth of soft matter.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Initial Atmospheric Transport of Particles

A new version of the Initial Atmospheric Transport (IAT) model has been developed. This report fully characterizes the new model. IAT is designed to model heat release into the atmosphere that contains contaminated particles. The heat release forms a buoyant puff or plume. Buoyancy is quickly dissipated in 10's to 100's of seconds through drag and entrainment of ambient air. The final location of contaminant particles in the atmosphere after dissipation of abnormal heat is an important input to long term transportation codes such as the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) code. Ultimately the settling of contaminants after long term transport provides a basis for estimating health consequences. In comparison to the old version, the new model includes explicit simulation of particles, newly formulated equations of motion for a rising puff, and a new plume model. The plume model releases many instances of a single puff along a single trajectory in a way that balances energy released over a longer period than would be appropriate for a single puff. The puff model has additions for vorticity, turbulence, virtual mass, drag, and entrainment. The particle model leads to direct interfacing between IAT and the long-term transport code HYSPLIT. Previously, particle locations were given a pattern based on IAT's puff trajectory with no particle simulation. Now, particles are explicitly simulated, and 3-D spatial distributions of particles are output based on final positions. Ballistic particles are thrown outward at high velocity from explosive events and tend to hit the ground before the end of the simulation. Non-ballistic particles tend to get pulled into the rising puff s ring of vorticity with some escaping to ambient conditions as buoyant energy dissipates. A new model verification and validation effort was made for the new plume model. The Wallops Island Solid Rocket Propellant (SRP) fire plume was extracted to a 3-D transient dataset. After calibration, the model performs better than previous single puff attempts. Even so, error levels in the process used to estimate location and ambient weather conditions approach 30%. This leads to the conclusion that unplanned photogrammetry evaluations of the IAT model are useful but not sufficiently accurate to quantify model parameters. Like previous attempts, the vertical motion entrainment parameters come out much too high in comparison to values for other studies in the literature. It is suspected that a new model of shear entrainment would alleviate this problem. Unfortunately, IAT already has more calibration parameters than the data comparisons thus far can resolve with statistical certainty. This underscores the need to verify and validate the IAT model using detailed CFD studies that allow ideal statistical comparison with the IAT model for hundreds of cases. Even so, validation by comparison to carefully planned experiments (i.e. with acceptable error levels) is also necessary because the dynamics of entrainment are at a sub-grid level for CFD. Though better validation and verification are most important, many new enhancements are still envisioned for future IAT development. These include particle rain out due to condensation and agglomeration of water, direct connection to the North American Mesoscale (NAM) weather dataset, dynamic weather conditions, including ambient particle entrainment into the puff, and detrainment at the puff to ambient mixing interface. In general, including detailed aerosol dynamics is the greatest coming challenge which will require an entire new sub-model in IAT. This is very important if contaminant particles change in such a way that they increase or decrease in their potential harm to the environment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗
DOE OSTI2019

Atomically Defined Edge-Doping of Graphene Nanoribbons for Mesoscale Electronics

The outstanding transformative potential of graphene, an infinite two-dimensional sheet of carbon atoms tightly packed into a honeycomb lattice, has been recognized mostly due to its exceptionally high electric conductivity, thermal conductivity, and tensile strength. These undeniably very desirable properties, however, represent only a very small facet of the true potential of all-sp2 carbon materials and its promise to revolutionize the field of molecular electronics. Graphene's most unusual characteristics emerge when the infinite macroscopic sheet is scaled down to nanometer dimensions. The exploration, realization, and implementation of these truly exotic magnetic and electronic properties rely on the development of innovative synthetic strategies that provide atomically precise control over the self-assembly of mesoscale objects. While traditional device architectures based on inorganic semiconductors have been fabricated using a top-down approach, we pursued a diametrically opposite strategy. Our design of a new generation of high-performance electronic materials relies on a modular bottom-up strategy. This highly multidisciplinary research program has been rooted in the synthesis of functional organic materials with precisely defined properties, their controlled assembly into hierarchical structures, and the evaluation of their performance at the molecular and the macroscopic scale. A part of this research program we have developed the chemical tools required to synthesize and to fine-tune the physical properties of graphene nanoribbons (GNR) with atomic precision. We further demonstrated that the innovative techniques and the expanded knowledge can be used to rationally tailor desired physical properties and function into nanometer-scale carbon-based electronic devices; e.g. transistors as logic gates in computing, data storage media based on electrically gated spin valves, or molecular amplifiers, all functionally integrated in atomically defined GNRs. We demonstrated the design and experimental realization of a rationally engineered graphene nanoribbon superlattice that hosts a 1D array of symmetry-protected topological states. We developed a hierarchical bottom-up fabrication strategy for graphene nanoribbons that preferentially exhibit a single heterojunction interface rather than a random statistical sequence of junctions along the ribbon. We reported the bottom-up synthesis of a series of atomically precise graphene nanoribbons featuring trigonal planar heteroatom dopants (nitrogen, oxygen, and sulfur) along the edges that induce a narrowing of the intrinsic band gap by ~0.2–0.3 eV per dopant atom. We reported the bottom-up synthesis of a graphene nanoribbon heterostructure featuring a highly tunable porphyrin quantum dot embedded at the center of a solution processable graphene nanoribbon. We reported a new technique for fabricating bottom-up graphene nanoribbon heterojunctions through a late-stage chemical transformation that results in atomically sharp heterojunction structures from a single precursor. We demonstrated the intrinsic performance enhancement of a composite material comprised of gold nanoparticles (AuNPs) embedded in a bottom-up synthesized graphene nanoribbon matrix for the electrocatalytic reduction of CO 2 . We developed a scalable, solution-based approach toward the synthesis of an exotic class of polycyclic aromatic hydrocarbons that exhibit unusual electronic and magnetic properties in the ground state. We reported the bottom-up synthesis and characterization of atomically-defined graphene nanoribbons featuring a regioregular pattern of group III dopant atoms (boron) along the backbone of the ribbon.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments, and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Self-Supervised Cloud Classification

Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive understanding of cloud morphology is critical for continued improvement of our atmospheric modeling and prediction capabilities moving forward. Deep learning has recently accelerated our ability to study clouds using satellite remote sensing, and machine learning classifiers have enabled detailed studies of cloud morphology. A major limitation of deep learning approaches to this problem, however, is the large number of hand-labeled samples that are required for training. This work applies a recently developed self-supervised learning scheme to train a deep convolutional neural network (CNN) to map marine cloud imagery to vector embeddings that capture information about mesoscale cloud morphology and can be used for satellite image classification. The model is evaluated against existing cloud classification datasets and several use cases are demonstrated, including training cloud classifiers with very few labeled samples, interrogation of the CNN’s learned internal feature representations, cross-instrument application, and resilience against sensor calibration drift and changing scene brightness. The self-supervised approach learns meaningful internal representations of cloud structures and achieves comparable classification accuracy to supervised deep learning methods without the expense of creating large hand-annotated training datasets. Significance Statement Marine clouds heavily influence Earth’s weather and climate, and improved understanding of marine clouds is required to improve our atmospheric modeling capabilities and physical understanding of the atmosphere. Recently, deep learning has emerged as a powerful research tool that can be used to identify and study specific marine cloud types in the vast number of images collected by Earth-observing satellites. While powerful, these approaches require hand-labeling of training data, which is prohibitively time intensive. This study evaluates a recently developed self-supervised deep learning method that does not require human-labeled training data for processing images of clouds. We show that the trained algorithm performs competitively with algorithms trained on hand-labeled data for image classification tasks. We also discuss potential downstream uses and demonstrate some exciting features of the approach including application to multiple satellite instruments, resilience against changing image brightness, and its learned internal representations of cloud types. The self-supervised technique removes one of the major hurdles for applying deep learning to very large atmospheric datasets.

54 ENVIRONMENTAL SCIENCES↗