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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Dynamics of water in prussian blue analogues: Neutron scattering study

Dynamics of crystal water in Prussian blue (PB), Fe(III){sub 4}[Fe(II)(CN){sub 6}]{sub 3}.14H{sub 2}O and its analogue Prussian green (PG), ferriferricynaide, Fe(III){sub 4}[Fe(III)(CN){sub 6}]{sub 4}.16H{sub 2}O have been investigated using Quasielastic Neutron Scattering (QENS) technique. PB and its analogue compounds are important materials for their various interesting multifunctional properties. It is known that crystal water plays a crucial role towards the multifunctional properties of Prussian blue analogue compounds. Three structurally distinguishable water molecules: (i) coordinated water molecules at empty nitrogen sites, (ii) non-coordinated water molecules in the spherical cavities, and (iii) at interstitial sites exist in PB. Here spherical cavities are created due to the vacant sites of Fe(CN){sub 6} units. However, PG does not have any such vacant N or Fe(CN){sub 6} units, and only one kind of water molecules, exists only at interstitial sites. QENS experiments have been carried out on both the compounds in the temperature range of 260–360 K to elucidate the dynamical behavior of different kinds of water molecules. Dynamics is found to be much more pronounced in case of PB, compared to PG. A detailed data analysis showed that localized translational diffusion model could describe the observed data for both PB and PG systems. The average diffusion coefficient is found to be much larger in the PB than PG. The obtained domain of dynamics is found to be consistent with the geometry of the structure of the two systems. Combining the data of the two systems, a quantitative estimate of the dynamics, corresponding to the water molecules at different locations is made.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

An MHD model for magnetar giant flares

Giant flares on soft gamma-ray repeaters that are thought to take place on magnetars release enormous energy in a short time interval. Their power can be explained by catastrophic instabilities occurring in the magnetic field configuration and the subsequent magnetic reconnection. By analogy with the coronal mass ejection events on the Sun, we develop a theoretical model via an analytic approach for magnetar giant flares. In this model, the rotation and/or displacement of the crust causes the field to twist and deform, leading to flux rope formation in the magnetosphere and energy accumulation in the related configuration. When the energy and helicity stored in the configuration reach a threshold, the system loses its equilibrium, the flux rope is ejected outward in a catastrophic way, and magnetic reconnection helps the catastrophe develop to a plausible eruption. By taking SGR 1806–20 as an example, we calculate the free magnetic energy released in such an eruptive process and find that it is more than 10{sup 47} erg, which is enough to power a giant flare. The released free magnetic energy is converted into radiative energy, kinetic energy, and gravitational energy of the flux rope. We calculated the light curves of the eruptive processes for the giant flares of SGR 1806–20, SGR 0526–66, and SGR 1900+14, and compared them with the observational data. The calculated light curves are in good agreement with the observed light curves of giant flares.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Tensor Minkowski Functionals: first application to the CMB

Tensor Minkowski Functionals (TMFs) are tensor generalizations of the usual Minkowski Functionals which are scalar quantities. We introduce them here for use in cosmological analysis, in particular to analyze the Cosmic Microwave Background (CMB) radiation. They encapsulate information about the shapes of structures and the orientation of distributions of structures. We focus on one of the TMFs, namely W {sub 2}{sup 1,1}, which is the (1,1) rank tensor generalization of the genus. The ratio of the eigenvalues of the average of W {sub 2}{sup 1,1} over all structures, α, encodes the net orientation of the structures; and the average of the ratios of the eigenvalues of W {sub 2}{sup 1,1} for each structure, β, encodes the net intrinsic anisotropy of the structures. We have developed a code that computes W {sub 2}{sup 1,1}, and from it α and β, for a set of structures on the 2-dimensional Euclidean plane. We use it to compute α and β as functions of chosen threshold levels for simulated Gaussian and isotropic CMB temperature and E mode fields. We obtain the value of α to be one for both temperature and E mode, which means that we recover the statistical isotropy of density fluctuations that we input in the simulations. We find that the standard ΛCDM model predicts a charateristic shape of β for temperature and E mode as a function of the threshold, and the average over thresholds is β∼ 0.62 for temperature and β∼ 0.63 for E mode. Accurate measurements of α and β can be used to test the standard model of cosmology and to search for deviations from it. For this purpose we compute α and β for temperature and E mode data of various data sets from PLANCK mission. We compare the values measured from observed data with those obtained from simulations to which instrument beam and noise characteristics of the 44GHz frequency channel have been added (which are provided as part of the PLANCK data release). We find very good agreement of β and α between all PLANCK temperature data sets with ΛCDM expectations. E mode data show good agreement for β but α for all data sets deviate from ΛCDM predictions higher than 3−σ. It is most likely that the deviations are probing the anisotropy of the noise field and beam characteristics of the detector rather than the true E mode signal since for 44GHz the signal-to-noise ratio is well below one. This will be further investigated after the full PLANCK data becomes publicly available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

Data-model integration plays a critical role in assessing and improving our capacity to predict ecosystem dynamics. Similarly, the ability to attach quantitative statements of uncertainty around model forecasts is crucial for model assessment and interpretation and for setting field research priorities. Bayesian methods provide a rigorous data assimilation framework for these applications, especially for problems with multiple data constraints. However, the Markov chain Monte Carlo (MCMC) techniques underlying most Bayesian calibration can be prohibitive for computationally demanding models and large datasets. We employ an alternative method, Bayesian model emulation of sufficient statistics, that can approximate the full joint posterior density, is more amenable to parallelization, and provides an estimate of parameter sensitivity. Analysis involved informative priors constructed from a meta-analysis of the primary literature and specification of both model and data uncertainties, and it introduced novel approaches to autocorrelation corrections on multiple data streams and emulating the sufficient statistics surface. We report the integration of this method within an ecological workflow management software, Predictive Ecosystem Analyzer (PEcAn), and its application and validation with two process-based terrestrial ecosystem models: SIPNET and ED2. In a test against a synthetic dataset, the emulator was able to retrieve the true parameter values. A comparison of the emulator approach to standard brute-force MCMC involving multiple data constraints showed that the emulator method was able to constrain the faster and simpler SIPNET model's parameters with comparable performance to the brute-force approach but reduced computation time by more than 2 orders of magnitude. The emulator was then applied to calibration of the ED2 model, whose complexity precludes standard (brute-force) Bayesian data assimilation techniques. Both models are constrained after assimilation of the observational data with the emulator method, reducing the uncertainty around their predictions. Performance metrics showed increased agreement between model predictions and data. Our study furthers efforts toward reducing model uncertainties, showing that the emulator method makes it possible to efficiently calibrate complex models.

58 GEOSCIENCES↗
NASA NTRS1976

Earth-based radio observations of Jupiter - Millimeter to meter wavelengths

The historical development of the study of Jupiter radio emission is considered and a description of the observational data is presented, taking into account the spectrum of the continuous microwave radiation, the polarization of the microwave radiation, the brightness distribution, the rotation-related variability, variations related to the zenocentric declination of the earth, and other time variations. The separation of radio emission into thermal and nonthermal components is discussed and interpretations of the two components are provided. A comparison of earth-based radio measurements with Pioneer 10 and 11 data is conducted and the future of earth-based radio observations is evaluated.

Berge, G. L.↗
NASA NTRS1979

Data System Implications Derived from User Application Requirements for Satellite Data

An investigation of the data system needs as driven by users of space acquired Earth observation data is documented. Two major categories of users, operational and research, are identified. Limiting data acquisition alleviates some of the delays in processing thus improving timeliness of the delivered product. Trade offs occur between timeliness and data distribution costs, and between data storage and reprocessing. The complexity of the data system requirements to apply space data to users' needs is such that no single analysis suffices to design and implement the optimum system. A series of iterations is required with analyses of the salient problems in a general way, followed by a limited implementation of benefit to some users with a continual upgrade in system capacity, functions, and applications served. The resulting most important requirement for the data system is flexibility to accommodate changing requirements as the system is implemented.

Neiers, J.↗
NASA NTRS1985

Photodissociation regions. I - Basic model. II - A model for the Orion photodissociation region

A theoretical parameter study of the temperature and chemical structure of dense photodissociation regions and their resultant spectrum is presented. Models are discussed which are relevant not only to the dust and gas between molecular clouds and H II regions, but also apply to any neutral cloud illuminated by intense FUV fluxes. The models relate observed line and continuum emission from these regions to physical parameters such as the gas density and temperature, the elemental and chemical abundances, the local radiation field, and the grain properties. The results are applied to observational data from the OMC-1 region. The model shows that the observed high brightness temperature of the C I 609 microns line can be explained by emission from the C(+)/C/CO transition region. This difference with previous chemical models is due to a higher gas phase elemental abundance of carbon, to the charge exchange reactions of C(+) with S and SiO, and to carbon self-shielding.

Tielens, A. G. G. M.↗
NASA NTRS1990

Planetary waves in Jupiter's equatorial atmosphere

Planetary-scale waves which have been latitudinally trapped within the equatorial jet of Jupiter are attested to by Voyager IR, radio occultation, and imaging data. An effort is presently made to identify a distinguishing class of planetary wave modes in the course of interpreting these data, with special attention being given to the equatorial plume features observed. A comparative evaluation of horizontal dispersion properties for linear wave modes on an equatorial beta plane suggests that the Rossby modes with a meridional structure index of 1 and an equivalent depth of 2-4 km are the interpretation most nearly consistent with all of the observational data for an equatorially trapped, wavenumber 12 pattern.

Allison, Michael↗
NASA NTRS1993

The quasar proximity effect in an equivalent-width-limited sample of the Lyman-alpha forest

We have obtained a simple analytical approximation to the relationship between a rest-frame equivalent-width distribution for Ly-alpha forest absorption lines, N(W), and an H I column density distribution of the observed cloud number, N(N). Assuming a simple power-law form for N(N) proportional to N exp (1-beta), it is shown that beta = 1.4 turns out to agree fairly well with the observed form of N(W) in a broad range of column densities. We present a theoretical analysis of how the 'proximity effect' influences a W-limited sample of Ly-alpha forest lines. It is shown that this influence is considerably smaller than has been found before for a N-limited sample, for which an approximate value of beta was assumed rather than derived as has been done, for a W-limited sample, in the present paper. As a result, available observational data appear to be still consistent with the conjecture that the observed population of QSOs is the major source of the UV background at redshifts z about 2-4.

Chernomordik, Viktor V.↗
NASA NTRS2010

The First Experiment with VLBI-GPS Hybrid System

In this paper, we introduce our GPS-VLBI hybrid system and show the results of the first experiment which is now under way. In this hybrid system, GPS signals are captured by a normal GPS antenna, down-converted to IF signals, and then sampled by the VLBI sampler VSSP32 developed by NICT. The sampled GPS data are recorded and correlated in the same way as VLBI observation data. The correlator outputs are the group delay and the delay rate. Since the whole system uses the same frequency standard, many sources of systematic errors are common between the VLBI system and the GPS system. In this hybrid system, the GPS antenna can be regarded as an additional VLBI antenna having multiple beams towards GPS satellites. Therefore, we expect that this approach will provide enough data to improve zenith delay estimates and geodetic results.

Kwak, Younghee↗
NASA NTRS2018

Lessons Learned and Cost Analysis of Hosting a Full Stack Open Data Cube (ODC) Application on the Amazon Web Services (AWS)

The Open Data Cube (ODC) initiative, with support from the Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has developed a state-of-the-art suite of software tools and products to facilitate the analysis of Earth Observation data. This paper presents a short summary and cost analysis of our experience using Amazon Web Services (AWS) to host one such software product, the CEOS Data Cube (CDC) web-based User Interface (UI). In order to provide adaptability, flexibility, scalability, and robustness, we leverage widely-adopted and well-supported technologies such as the Django web framework and the AWS Cloud platform. The UI has empowered users by providing features that assist with streamlining data preparation, data processing, data visualization, and the sub-setting of Analysis Ready Data (ARD) products in order to achieve a wide variety of Earth imaging objectives.

Rizvi, Syed R.↗
DOE OSTI2019

Strong SUSY at ATLAS and CMS

Supersymmetry (SUSY) remains one of the most elegant theories of new physics. The experiments at the LHC are able to put stringent constraints on strongly produced SUSY particles. Several of the most recent results by the CMS and ATLAS Collaborations in searches for gluinos and squarks are presented. The results use between 36 and 139 fb$^{-1}$ of proton-proton collision data at 13 TeV, and the background predictions agree with the observed data. For a variety of SUSY models, new limits on sparticle masses are set that surpass previous results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP5 ensemble

Abstract Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

Lee, Youngsaeng↗
NASA NTRS2022

Unique NISTAR-Based Climate GCM Diagnostics of the Earth’s Planetary Albedo and Spectral Absorption Through Longitudinal Data Slicing

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation permit a unique model/data comparison perspective that is not readily available from other satellite data. The key factor is the unique Lissajous orbital viewing geometry from the Lagrangian L1 point, which enables a continuous view of Earth’s sunlit hemisphere. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) is the DSCOVR Mission energy budget instrument, which views the reflected and emitted radiation of the Earth’s sunlit hemisphere by means of single pixel active cavity full-spectrum (Band-A, 0.2–100 μm) and filtered solar wavelength (Band-B, 0.2–4.0 μm; and Band-C, 0.7–4.0 μm) radiometer measurements. An additional solar wavelength photodiode channel (0.3–1.1 μm) provides a calibration reference. The objective of this study is the assessment of climate GCM performance via direct model/data comparisons. Such comparisons are difficult due to quasi-chaotic natural variability present in real-world observational data and in climate GCM simulations. This is where the unique DSCOVR viewing geometry makes possible the longitudinal data slicing methodology for more direct model/data comparison. The key point of the longitudinal slicing approach is that data integration over the entire sunlit hemisphere eliminates the quasi-chaotic meteorological weather-scale noise, while preserving intra-seasonal and planetary-scale variability. The rotation of the Earth that retrieves this climate-style, large-scale longitudinal and seasonal variability. The hemispheric averaging is accomplished automatically in NISTAR measurements with its single-pixel view of the Earth. For climate GCMs, this requires implementing the Sunlit Hemisphere Sampling (SHS) scheme to operate on the GCM run-time output data, utilizing the DSCOVR Satellite Ephemeris data to assure precise viewing geometry between NISTAR measurements and GCM output data, while averaging out the meteorological weather noise. However, GCM generated data are radiative fluxes, while NISTAR (and EPIC) measurements are near-backscattered radiances. Conversing NISTSR measurements into radiative fluxes cannot be accomplished using NISTAR data alone, even with detailed support from conventional satellite data. But the identical viewing geometry of Earth’s sunlit hemisphere, and synergistic analyses of EPIC data make it feasible for this conversion of NISTAR near-backscatter radiances into radiative fluxes.

deep space climate observatory↗
NASA NTRS1992

Development of a four-dimensional variational analysis system using the adjoint method at GLA. I - Dynamics

Recent developments in the field of data assimilation have pointed to variational analysis (essentially least-squares fitting of a model solution to observed data) using the adjoint method as a new direction that holds the potential of major improvements over the current optimal interpolation method. This paper describes the initial effort in the development of a 4D variational analysis system. Although the development is based on the Goddard Laboratory for Atmospheres General Circulation Model (GCM), the methods and procedures described in this paper can be applied to any model. The adjoint code that computes the gradients needed in the analysis can be written directly from the GCM code. An easy error-detection technique was devised in the construction of the adjoint model. Also, a method of determining the weights and the preconditioning scales for the cases where model-generated data, which are error free, are used as observation is proposed. Two test experiments show that the dynamics part of the system has been successfully completed.

Chao, Winston C.↗
DOE OSTI2023

Predicting climate change impacts on poikilotherms using physiologically guided species abundance models

Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in laboratory-derived thermal response curves and provides estimates of thermal habitat suitability and extinction probability based on site-specific conditions. We show that temperature-driven changes in distributions, local extinction, and abundance of cold, cool, and warm-adapted species vary substantially when physiological information is incorporated. Notably, cold-adapted species were predicted by the PGA model to be extirpated in 61% of locations that they currently inhabit, while extirpation was never predicted by a correlative niche model. Failure to account for species-specific physiological constraints could lead to unrealistic predictions under a warming climate, including underestimates of local extirpation for cold-adapted species near the edges of their climate niche space and overoptimistic predictions of warm-adapted species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Convergence Analysis for an Online Data-Driven Feedback Control Algorithm

This paper presents convergence analysis of a novel data-driven feedback control algorithm designed for generating online controls based on partial noisy observational data. The algorithm comprises a particle filter-enabled state estimation component, estimating the controlled system’s state via indirect observations, alongside an efficient stochastic maximum principle-type optimal control solver. By integrating weak convergence techniques for the particle filter with convergence analysis for the stochastic maximum principle control solver, we derive a weak convergence result for the optimization procedure in search of optimal data-driven feedback control. Numerical experiments are performed to validate the theoretical findings.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Data Visualization and Analysis for Climate Studies using NASA Giovanni Online System

With many global earth observation systems and missions focused on climate systems and the associated large volumes of observational data available for exploring and explaining how climate is changing and why, there is an urgent need for climate services. Giovanni, the NASA GES DISC Interactive Online Visualization ANd ANalysis Infrastructure, is a simple to use yet powerful tool for analysing these data for research on global warming and climate change, as well as for applications to weather. air quality, agriculture, and water resources,

Rui, Hualan↗