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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Incorporating JULES into NASA's Land Information System (LIS) and Investigations of Land-Atmosphere Coupling

NASA's Land Information System (LIS; lis.gsfc.nasa.gov) is a flexible land surface modeling and data assimilation framework developed over the past decade with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. LIS features a high performance and flexible design, and operates on an ensemble of land surface models for extension over user-specified regional or global domains. The extensible interfaces of LIS allow the incorporation of new domains, land surface models (LSMs), land surface parameters, meteorological inputs, data assimilation and optimization algorithms. In addition, LIS has also been demonstrated for parameter estimation and uncertainty estimation, and has been coupled to the Weather Research and Forecasting (WRF) mesoscale model. A visiting fellowship is currently underway to implement JULES into LIS and to undertake some fundamental science on the feedbacks between the land surface and the atmosphere. An overview of the LIS system, features, and sample results will be presented in an effort to engage the community in the potential advantages of LIS-JULES for a range of applications. Ongoing efforts to develop a framework for diagnosing land-atmosphere coupling will also be presented using the suite of LSM and PBL schemes available in LIS and WRF along with observations from the U. S .. Southern Great Plains. This methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Santanello, Joseph↗
NASA NTRS1986

A report on the upper-level wind conditions preceding and during the Shuttle Challenger (STS 51L) explosion

The prelaunch, launch, and postlaunch synoptic-scale weather conditions on January 28, 1986 are described. Particular consideration is given to upper-level jet streams, vertical wind shear, and the possible effect of shear-induced turbulence on Cape Canaveral at the time of the Shuttle launch. General data revealing the relations between wind shear and turbulence and jet streams are discussed. The NWS operational and surface radiosonde data, visible and IR GOES imagery, and total ozone data obtained from TOMS on Nimbus-7 are analyzed. Numerical simulations of the weather conditions were conducted. The simulations and observational data are compared, and the data reveal the juxtaposition of two distinct jet-stream systems (a polar front jet and a subtropical jet) over north-central Florida the morning of the launch. Recommendations for improving the observing system at Cape Canaveral are discussed.

Uccellini, Louis W.↗
DOE OSTI2014

Internal energy dissipation of gamma-ray bursts observed with Swift: Precursors, prompt gamma-rays, extended emission, and late X-ray flares

We jointly analyze the gamma-ray burst (GRB) data observed with Burst Alert Telescope (BAT) and X-ray Telescope on board the Swift mission to present a global view on the internal energy dissipation processes in GRBs, including precursors, prompt gamma-ray emission, extended soft gamma-ray emission, and late X-ray flares. The Bayesian block method is utilized to analyze the BAT light curves to identify various emission episodes. Our results suggest that these emission components likely share the same physical origin, which is the repeated activation of the GRB central engine. What we observe in the gamma-ray band may be a small part of more extended underlying activities. The precursor emission, which is detected in about 10% of Swift GRBs, is preferably detected in those GRBs that have a massive star core-collapse origin. The soft extended emission tail, on the other hand, is preferably detected in those GRBs that have a compact star merger origin. Bright X-ray emission is detected during the BAT quiescent phases prior to subsequent gamma-ray peaks, implying that X-ray emission may be detectable prior the BAT trigger time. Future GRB alert instruments with soft X-ray capability are essential for revealing the early stages of GRB central engine activities, and shedding light on jet composition and the jet launching mechanism in GRBs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Search for Higgs boson off-shell production in proton-proton collisions at 7 and 8 TeV and derivation of constraints on its total decay width

A search is presented for the Higgs boson off-shell production in gluon fusion and vector boson fusion processes with the Higgs boson decaying into a WW pair and the W bosons decaying leptonically. The data observed in this analysis are used to constrain the Higgs boson total decay width. The analysis is based on the data collected by the CMS experiment at the LHC, corresponding to integrated luminosities of 4.9 inverse femtobarns at a centre-of-mass energy of 7 TeV and 19.4 inverse femtobarns at 8 TeV, respectively. An observed (expected) upper limit on the off-shell Higgs boson event yield normalised to the standard model prediction of 2.4 (6.2) is obtained at the 95% CL for the gluon fusion process and of 19.3 (34.4) for the vector boson fusion process. Observed and expected limits on the total width of 26 and 66 MeV are found, respectively, at the 95% confidence level (CL). These limits are combined with the previous result in the ZZ channel leading to observed and expected 95% CL upper limits on the width of 13 and 26 MeV, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2008

Interpolating Fields of Carbon Monoxide Data Using a Hybrid Statistical-Physical Model

Atmospheric Carbon Monoxide (CO) is a pollutant gas of which the US congress has mandated regular monitoring, and satellite sensors can be used to retrieve regional concentrations of CO over several vertical layers. However, CO at cloudy locations cannot be observed and have to be estimated from the observed data set, resulting in an interpolation problem. The current state-of-the-art solution is to combine prior information, computed by a deterministic physical model, with observations. However, the deterministic model may introduce uncertainties that do not derive from the data. While sharing certain features with the physical model, this paper presents a Bayesian hierarchical model for interpolating CO on a 3-dimensional spatial grid, across time. To our knowledge such a model has not been considered before. The model is applied to a hypothetical air-quality monitoring scenario, and is compared to existing interpolation methods. The results provide motivation for the use of the statistical model for regional to local applications.

Arellano, A. A.↗
NASA NTRS2010

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

Wang, Yao↗
DOE OSTI2021

Simple, low-cost and accurate data-driven geophysical forecasting with learned kernels

Modelling geophysical processes as low-dimensional dynamical systems and regressing their vector field from data is a promising approach for learning emulators of such systems. We show that when the kernel of these emulators is also learned from data (using kernel flows, a variant of cross-validation), then the resulting data-driven models are not only faster than equation-based models but are easier to train than neural networks such as the long short-term memory neural network. In addition, they are also more accurate and predictive than the latter. When trained on geophysical observational data, for example the weekly averaged global sea-surface temperature, considerable gains are also observed by the proposed technique in comparison with classical partial differential equation-based models in terms of forecast computational cost and accuracy. When trained on publicly available re-analysis data for the daily temperature of the North American continent, we observe significant improvements over classical baselines such as climatology and persistence-based forecast techniques. Although our experiments concern specific examples, the proposed approach is general, and our results support the viability of kernel methods (with learned kernels) for interpretable and computationally efficient geophysical forecasting for a large diversity of processes.

58 GEOSCIENCES↗
DOE OSTI2015

Search for new phenomena in events with a photon and missing transverse momentum in p p collisions at s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in events with an energetic photon and large missing transverse momentum with the ATLAS experiment at the LHC are reported. Data were collected in proton-proton collisions at a center-of-mass energy of 8 TeV and correspond to an integrated luminosity of 20.3 fb⁻¹. The observed data are well described by the expected Standard Model backgrounds. The expected (observed) upper limit on the fiducial cross section for the production of events with a photon and large missing transverse momentum is 6.1 (5.3) fb at 95% confidence level. Exclusion limits are presented on models of new phenomena with large extra spatial dimensions, supersymmetric quarks, and direct pair production of dark-matter candidates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Search for new phenomena in events with a photon and missing transverse momentum in p p collisions at s = 8 TeV with the ATLAS detector

CERN-LHC. Results of a search for new phenomena in events with an energetic photon and large missing transverse momentum with the ATLAS experiment at the LHC are reported. Data were collected in proton--proton collisions at a center-of-mass energy of 8 TeV and correspond to an integrated luminosity of 20.3 fb-1. The observed data are well described by the expected Standard Model backgrounds. The expected (observed) upper limit on the fiducial cross section for the production of such events is 6.1 (5.3) fb at 95% confidence level. Exclusion limits are presented on models of new phenomena with large extra spatial dimensions, supersymmetric quarks, and direct pair production of dark-matter candidates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2019

Smart Handoffs: Preserving User Context Between Tools and Services Related to NASA's EOSDIS Data Archive

NASA's Earth Observing System Data and Information System (EOSDIS) is tasked with archiving and distributing Earth Observation data across a range of disciplines, including atmospheric science, oceanography, land processes, natural hazards, solar radiance and even socioeconomic aspects relating to the environment. Given the breadth of disciplines and depth of data that EOSDIS provides, the efficient and intuitive discovery and usage of data by a scientist is of paramount importance. An effective data gathering workflow may involve switching from general use discovery tools to a more bespoke services designed specifically for the scientist's discipline. Providing concrete interoperability between such tools could vastly improve the efficiency of a scientist's workflow.

Analytics↗
NASA NTRS1983

Purely coronal flare-like variations

Quasiperiodic X-ray, UV, microwave, and metric-wave variations after a solar flare on November 6, 1980 are reported and analyzed, based on observational data from SMM (HXRBS, UVSP, HXIS), GOES-2, the 100-m radiotelescope at Bonn, and the Nancay radioheliograph. The maxima of the 13 brightenings observed are listed and characterized; a comparison is made with a 'normal' flare at 17:26 UT on the same day. The HXIS and UVSP data are discussed in terms of the physical properties, X-ray flux, O V flux, and H-alpha flux. The variations are found to be mainly thermal and purely coronal, with no chromospheric (H-alpha) participation (in contrast to the 17:26 flare). Since strong X-ray emissions were observed which should have involved the chromosphere through magnetic-field-line heat conduction, it is proposed that the variations wre produced ina coronal plasmoid magnetically separate from the chromosphere. A mechanism for the evolution of such a plasmoid from the upper loops of a giant X-ray arch is discussed. An iterative HXIS-image-deconvolution process is presented in an appendix.

Svestka, Z.↗
NASA NTRS2002

Data Assimilation and Transport Modeling in Terrestrial and Planetary Atmospheres

Data assimilation is a blanket term used to describe a number of techniques for retrieving important physical parameters from observational data, subject to constraints imposed by prior knowledge (such as, in the case of meteorology, the primitive equations that govern atmospheric motion). Since these newly developed methods make efficient use of computational resources, they are of great importance in the interpretation of the voluminous datasets that are now produced by satellite missions. As proposed, these techniques have been applied to the study of the Martian and terrestrial atmospheres based on available satellite observations. In addition, a sophisticated hydrodynamic model (non-hydrostatic, and therefore applicable to the study of the interiors of the giant planets) has also been developed and successfully applied to the study of tidally induced motions in Jupiter.

Houben, Howard C.↗
DOE OSTI2017

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts: CRM Intercomparison of a Squall Line

A constrained model intercomparison study of a mid-latitude mesoscale squall line is performed using the Weather Research & Forecasting (WRF) model at 1-km horizontal grid spacing with eight cloud microphysics schemes, to understand specific processes that lead to the large spread of simulated cloud and precipitation at cloud-resolving scales, with a focus of this paper on convective cores. Various observational data are employed to evaluate the baseline simulations. All simulations tend to produce a wider convective area than observed, but a much narrower stratiform area, with most bulk schemes overpredicting radar reflectivity. The magnitudes of the virtual potential temperature drop, pressure rise, and the peak wind speed associated with the passage of the gust front are significantly smaller compared with the observations, suggesting simulated cool pools are weaker. Simulations also overestimate the vertical velocity and Ze in convective cores as compared with observational retrievals. The modeled updraft velocity and precipitation have a significant spread across the eight schemes even in this strongly dynamically-driven system. The spread of updraft velocity is attributed to the combined effects of the low-level perturbation pressure gradient determined by cold pool intensity and buoyancy that is not necessarily well correlated to differences in latent heating among the simulations. Variability of updraft velocity between schemes is also related to differences in ice-related parameterizations, whereas precipitation variability increases in no-ice simulations because of scheme differences in collision-coalescence parameterizations.

Fan, Jiwen↗
DOE OSTI2021

Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling

Abstract This study integrates machine learning and particle‐resolved aerosol simulations to develop emulators that predict submicron aerosol mixing state indices from the Earth system model (ESM) simulations. The emulators predict aerosol mixing state using only quantities that are predicted by the ESM, including bulk aerosol species concentrations, which do not by themselves carry mixing state information. We used PartMC‐MOSAIC as the particle‐resolved model and NCAR's CESM as the ESM. We trained emulators for three different mixing state indices for submicron aerosol in terms of chemical species abundance ( χ a ), the mixing of optically absorbing and nonabsorbing species ( χ o ), and the mixing of hygroscopic and nonhygroscopic species ( χ h ). Our global mixing state maps show considerable spatial and seasonal variability unique to each mixing state index. Seasonal averages varied spatially between 13% and 94% for χ a , between 38% and 94% for χ o , and between 20% and 87% for χ h with global annual averages of 67%, 68%, and 56%, respectively. High values in one index can be consistent with low values in another index depending on the grouping of species and their relative abundance, meaning that each mixing state index captures different aspects of the population mixing state. Although a direct validation with observational data has not been possible yet, our results are consistent with mixing state index values derived from ambient observations. This work is a prototypical example of using machine learning emulators to add information to ESM simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Thresholded power law size distributions of instabilities in astrophysics

Power-law-like size distributions are ubiquitous in astrophysical instabilities. There are at least four natural effects that cause deviations from ideal power law size distributions, which we model here in a generalized way: (1) a physical threshold of an instability; (2) incomplete sampling of the smallest events below a threshold x{sub 0}; (3) contamination by an event-unrelated background x{sub b}; and (4) truncation effects at the largest events due to a finite system size. These effects can be modeled in the simplest terms with a “thresholded power law” distribution function (also called generalized Pareto [type II] or Lomax distribution), N(x)dx∝(x+x{sub 0}){sup −a}dx, where x{sub 0} > 0 is positive for a threshold effect, while x{sub 0} < 0 is negative for background contamination. We analytically derive the functional shape of this thresholded power law distribution function from an exponential growth evolution model, which produces avalanches only when a disturbance exceeds a critical threshold x{sub 0}. We apply the thresholded power law distribution function to terrestrial, solar (HXRBS, BATSE, RHESSI), and stellar flare (Kepler) data sets. We find that the thresholded power law model provides an adequate fit to most of the observed data. Major advantages of this model are the automated choice of the power law fitting range, diagnostics of background contamination, physical instability thresholds, instrumental detection thresholds, and finite system size limits. When testing self-organized criticality models that predict ideal power laws, we suggest including these natural truncation effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

The PALS Land Surface Model Benchmarking Evaluation Project (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave, surface air temperature and relative humidity. These results are explored here in greater detail and possible causes are investigated. We examine whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation and whether a lack of energy conservation in flux tower data gives the empirical models an unfair advantage in the intercomparison. We demonstrate that energy conservation in the observational data is not responsible for these results. We also show that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. In conclusion, we present evidence suggesting that the nature of this partitioning problem is likely shared among all contributing LSMs. While we do not find a single candidate explanation for why land surface models perform poorly relative to empirical benchmarks in PLUMBER, we do exclude multiple possible explanations and provide guidance on where future research should focus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Magnetohydrodynamic Simulations for Studying Solar Flare Trigger Mechanism

In order to understand the flare trigger mechanism, we conduct three-dimensional magnetohydrodynamic simulations using a coronal magnetic field model derived from data observed by the Hinode satellite. Several types of magnetic bipoles are imposed into the photospheric boundary of the Nonlinear Force-free Field model of Active Region (AR) NOAA 10930 on 2006 December 13, to investigate what kind of magnetic disturbance may trigger the flare. As a result, we confirm that certain small bipole fields, which emerge into the highly sheared global magnetic field of an AR, can effectively trigger a flare. These bipole fields can be classified into two groups based on their orientation relative to the polarity inversion line: the so-called opposite polarity, and reversed shear structures, as suggested by Kusano et al. We also investigate the structure of the footpoints of reconnected field lines. By comparing the distribution of reconstructed field lines and observed flare ribbons, the trigger structure of the flare can be inferred. Our simulation suggests that the data-constrained simulation, taking into account both the large-scale magnetic structure and small-scale magnetic disturbance (such as emerging fluxes), is a good way to discover a flare-producing AR, which can be applied to space weather prediction.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Uncertainties in derived temperature-height soundings A summary

It is shown that high-resolution low-uncertainty temperature-height profiles cannot be deduced from pressure-height data alone because the relative uncertainty in pressure data cannot be expected to be smaller than 1% or 2% in present-day practical instrumentation. The basic equations relating temperature to pressure-height or density-height data are subjected to error analysis to determine the uncertainty introduced into computed temperature-height values by observed data. The results show that the use of density data is much more preferable than the use of pressure data if atmospheric temperature is to be determined as a function of height with a fine height resolution and a small uncertainty from the height profiles of pressure or density and if pressures and densities can be measured with comparable accuracies.

Minzner, R. A.↗