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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Square Kilometre Array Science Data Challenge 1: analysis and results

ABSTRACT As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality data sets for testing and evaluating new techniques. In this paper, we present a description and results from the first such Science Data Challenge 1 (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560, 1400, and 9200 MHz) at three depths (8, 100, and 1000 h), SDC1 asked participants to apply source detection, characterization, and classification methods to simulated data. The challenge opened in 2018 November, with nine teams submitting results by the deadline of 2019 April. In this work, we analyse the results for eight of those teams, showcasing the variety of approaches that can be successfully used to find, characterize, and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.

Bonaldi, A.↗
DOE OSTI2015

A physical approach to the identification of high-Z mergers: Morphological classification in the stellar mass domain

At z ≳ 1, the distinction between merging and “normal” star-forming galaxies based on single band morphology is often hampered by the presence of large clumps which result in a disturbed, merger-like appearance even in rotationally supported disks. In this paper we discuss how a classification based on canonical, non-parametric structural indices measured on resolved stellar mass maps, rather than on single-band images, reduces the misclassification of clumpy but not merging galaxies. We calibrate the mass-based selection of mergers using the MIRAGE hydrodynamical numerical simulations of isolated and merging galaxies which span a stellar mass range of 10{sup 9.8}–10{sup 10.6} M{sub ⊙} and merger ratios between 1:1–1:6.3. These simulations are processed to reproduce the typical depth and spatial resolution of observed Hubble Ultra Deep Field (HUDF) data. We test our approach on a sample of real z≃2 galaxies with kinematic classification into disks or mergers and on ∼100 galaxies in the HUDF field with photometric/spectroscopic redshift between 1.5 ≤ z ≤ 3 and M > 10{sup 9.4} M{sub ⊙}. We find that a combination of the asymmetry A{sub MASS} and M{sub 20, MASS} indices measured on the stellar mass maps can efficiently identify real (major) mergers with ≲20% contamination from clumpy disks in the merger sample. This mass-based classification cannot be reproduced in star-forming galaxies by H-band measurements alone, which instead result in a contamination from clumpy galaxies which can be as high as 50%. Moreover, we find that the mass-based classification always results in a lower contamination from clumpy galaxies than an H-band classification, regardless of the depth of the imaging used (e.g., CANDELS versus HUDF).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Superconductivity and phase diagrams of CaK(Fe 1- x Mn x ) 4 As 4 single crystals

In order to study the effects of Mn substitution on the superconducting and magnetic ground state of CaKFe 4 As 4 (T c = 35 K), members of the CaK (Fe 1–x Mn x ) 4 As 4 series have been synthesized by high-temperature solution growth in single-crystalline form and characterized by elemental analysis, thermodynamic, and transport measurements. These measurements show that the superconducting transition temperature decreases monotonically and is finally suppressed below 1.8 K as x is increased from 0 to 0.036. For x values greater than 0.016, signatures of a magnetic transition can be detected in both thermodynamic and transport measurements in which kinklike features allow for the determination of the transition temperature T* that increases as Mn substitution increases. Here, a temperature-composition (T–x) phase diagram is constructed, revealing a half-dome of superconductivity with the magnetic transition temperature T* appearing near 26 K for x ~ 0.017 and rising slowly up to 33 K for x ~ 0.036. In addition to the creation of the T–x phase diagram for CaK(Fe 1–x Mn x ) 4 As 4 , specific-heat data are used to track the jump in specific heat at T c ; the CaK(Fe 1–x Mn x ) 4 As 4 data do not follow the scaling of ΔC p with $T$$^{3}_{c}$ as many of the other Fe-based superconducting systems do. These data suggest that, as magnetic pair breaking is present, the jump in C p for a given T c is reduced. Elastoresistivity coefficients 2m 66 and m 11 – m 12 as a function of temperature are also measured. 2m 66 and m 11 – m 12 are qualitatively similar to CaK(Fe 1–x Ni x ) 4 As 4 . This may indicate that the magnetic order in Mn-substituted system may be still the same as CaK(Fe 1–x Mn x ) 4 As 4 . Superconductivity of CaK(Fe 1–x Mn x ) 4 As 4 is also studied as a function of magnetic field. A clear change in H' c2 (T)/T c , where H' c2 (T) is dH' c2 (T)/dT, at x ~ 0.015 is observed and probably is related to change of the Fermi surface due to magnetic order. Coherence lengths and the London penetration depths are also calculated based on H c1 and H c2 data. Coherence lengths as the function of x also show the changes near x = 0.015, again consistent with Fermi-surface changes associated with the magnetic ordering seen for higher-x values.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2000

BOREAS RSS-12 Airborne Tracking Sunphotometer Measurements

The BOREAS RSS-12 team collected both ground and airborne sunphotometer measurements for use in characterizing the aerosol optical properties of the atmosphere during the BOREAS data collection activities. These measurements are to be used to: 1) measure the magnitude and variability of the aerosol optical depth in both time and space; 2) determine the optical properties of the boreal aerosols; and 3) atmospherically correct remotely sensed data acquired during BOREAS. This data set contains airborne tracking sunphotometer data that were acquired from the C-130 aircraft during its flights over the BOREAS study areas. The data cover selected days and times from May to September 1994. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS1992

Method for determining transport critical current densities and flux penetration depth in bulk superconductors

A contact-less method for determining transport critical current density and flux penetration depth in bulk superconductor material. A compressor having a hollow interior and a plunger for selectively reducing the free space area for distribution of the magnetic flux therein are formed of superconductor material. Analytical relationships, based upon the critical state model, Maxwell's equations and geometrical relationships define transport critical current density and flux penetration depth in terms of the initial trapped magnetic flux density and the ratio between initial and final magnetic flux densities whereby data may be reliably determined by means of the simple test apparatus for evaluating the current density and flux penetration depth.

Israelsson, Ulf E.↗
NASA NTRS2015

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

Evaluation↗
NASA NTRS2014

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

hydrology↗
NASA NTRS2018

HZETRN Radiation Transport Validation Using Balloon-Based Experimental Data

The deterministic radiation transport code HZETRN (High charge (Z) and Energy TRaNsport) was developed by NASA to study the effects of cosmic radiation on astronauts and instrumentation shielded by various materials. This work presents an analysis of computed differential flux from HZETRN compared with measurement data from three balloon-based experiments over a range of atmospheric depths, particle types, and energies. Model uncertainties were quantified using an interval-based validation metric that takes into account measurement uncertainty both in the flux and the energy at which it was measured. Average uncertainty metrics were computed for the entire dataset as well as subsets of the measurements (by experiment, particle type, energy, etc.) to reveal any specific trends of systematic over- or under-prediction by HZETRN. The distribution of individual model uncertainties was also investigated to study the range and dispersion of errors beyond just single scalar and interval metrics. The differential fluxes from HZETRN were generally well-correlated with balloon-based measurements; the median relative model difference across the entire dataset was determined to be 30%. The distribution of model uncertainties, however, revealed that the range of errors was relatively broad, with approximately 30% of the uncertainties exceeding ± 40%. The distribution also indicated that HZETRN systematically under-predicts the measurement dataset as a whole, with approximately 80% of the relative uncertainties having negative values. Instances of systematic bias for subsets of the data were also observed, including a significant underestimation of alpha particles and protons for energies below 2.5 GeV/u. Muons were found to be systematically over-predicted at atmospheric depths deeper than 50 g/cm(sup 2) but under-predicted for shallower depths. Furthermore, a systematic under-prediction of alpha particles and protons was observed below the geomagnetic cutoff, suggesting that improvements to the light ion production cross sections in HZETRN should be investigated.

James E Warner↗
NASA NTRS1988

Calibration and evaluation of AVIRIS data: Cripple Creek in October 1987

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were obtained over Cripple Creek and Canon City Colorado on October 19, 1987 at local noon. Multiple ground calibration sites were measured within both areas with a field spectrometer and samples were returned to the laboratory for more detailed spectral characterization. The data were used to calibrate the AVIRIS data to ground reflectance. Once calibrated, selected spectra in the image were extracted and examined, and the signal to noise performance was computed. Images of band depth selected to be diagnostic of the presence of certain minerals and vegetation were computed. The AVIRIS data were extremely noisy, but images showing the presence of goethite, kaolinite and lodgepole pine trees agree with ground checks of the area.

Clark, Roger N.↗
NASA NTRS2013

Post-flight Analysis of Mars Science Laboratory Entry Aerothermal Environment and Thermal Protection System Response

The Mars Science Laboratory successfully landed on the Martian surface on August 5th, 2012. The rover was protected from the extreme heating environments of atmospheric entry by an ablative heatshield. This Phenolic Impregnated Carbon Ablator heatshield was instrumented with a suite of embedded thermocouples, isotherm sensors, and pressure transducers. The sensors monitored the in-depth ablator response, as well as the surface pressure at discrete locations throughout the hypersonic deceleration. This paper presents a comparison of the flight data with post-entry estimates. An assessment of the aerothermal environments, as well as the in-depth response of the heatshield material is made, and conclusions regarding the overall performance of the ablator at the suite locations are presented.

mars science laboratory↗
DOE OSTI2022

Improved limits on the tensor-to-scalar ratio using BICEP and P l a n c k data

In this study, we present constraints on the tensor-to-scalar ratio r using a combination of BICEP/Keck 2018 (BK18) and Planck PR4 data allowing us to fit for r consistently with the six parameters of the Λ CDM model. We discuss the sensitivity of constraints on r to uncertainties in the Λ CDM parameters as defined by the Planck data. In particular, we are able to derive a constraint on the reionization optical depth τ and thus propagate its uncertainty into the posterior distribution for r . While Planck sensitivity to r is slightly lower than the current ground-based measurements, the combination of Planck with BK18 and baryon-acoustic-oscillation data yields results consistent with r = 0 and tightens the constraint to r < 0.032 at 95% confidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Transport and Retention of Particulate Organic Matter in Sand: Lab Experiments and Modelling

Flow-through reactor (FTR) experiments were conducted at three different downward vertical flow rates to study the transport and retention of particulate organic matter (Chlorella powder) in riverbed sediments. This data package includes data files (.csv) regarding effluent collected from the FTRs during the experiments (time, duration, volume of each sample collection; concentration of nonreactive bromide tracer; concentration of suspended Chlorella determined by absorbance measurements) and sediment (sand) slices collected from the FTRs after the experiments (mass of Chlorella retained in 1 cm depth intervals determined by loss-on-ignition method). More detailed descriptions of data are provided in the data dictionary, and detailed methods are available in the associated MSc thesis listed in ‘Related References.’ The data dictionary and file level meta data (FLMD) are included in the data package as both .csv and .xlsx files. This data package also includes timelapse videos (.mp4) of the experiments, and modelling scripts associated with the experiments. The modelling scripts are included as MATLAB ‘live scripts’ (.mlx, which can be run using MATLAB), and are also included as .pdf and .html files with output plots included (which can be viewed without a MATLAB license and installation). The data files and modelling scripts are organized into a .zip folder for each of the three FTR experiments (three flow rates).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Microwave Signatures of Snow on Sea Ice: Modeling

Accurate knowledge of snow-depth distribution over sea ice is critical for polar climate studies. Current snow-depth-over-sea-ice retrieval algorithms do not sufficiently account for variations in snow and ice physical properties that can affect the accuracy of retrievals. For this reason, airborne microwave observations were coordinated with ground-based measurements of snow depth and snow properties in the vicinity of Barrow, AK, in March 2003. In this paper, the effects of snowpack properties and ice conditions on microwave signatures are examined using detailed surface-based measurements and airborne observations in conjunction with a thermal microwave-emission model. A comparison of the Microwave Emission Model of Layered Snowpacks (MEMLS) simulations with detailed snowpack and ice data from stakes along the Elson Lagoon and the Beaufort Sea and ra- 'diometer data taken from low-level flights using a Polarimetric Scanning Radiometer (PSR-A) shows that MEMLS can be used to simulate snow on sea ice and is a useful tool for understanding the limitations of the snow-depth algorithm. Analysis of radiance data taken over the Elson Lagoon and the Beaufort Sea using MEMLS suggests that the radiometric differences between the two locations are due to the differences in sea-ice emissivity. Furthermore, measured brightness temperatures suggest that the current snow-depth retrieval algorithm is sufficient for areas of smooth first-year sea ice, whereas new algorithm coefficients are needed for rough first-year sea ice. Snowpack grain size and density remain an unresolved issue for snow-depth retrievals using passive-microwave radiances.

Powell, D. C.↗
NASA NTRS1991

An ellipsoidal representation of human hand anthropometry

Anthropometric data concerning the heometry of the hand's surface are presently modeled as a function of gross external hand measurements; an effort is made to evaluate the accuracy with which ellipsoids describe the geometry of the hand segments. Graphical comparisons indicate that differences between the ellipsoidal approximations and the breadth and depth measurements were greatest near the joints. On the bases of the present data, a set of overlapping ellipsoids could furnish a more accurate representation of hand geometry for adaptation to ellipsoid segment-geometry employing biomechanical models.

Buchholz, Bryan↗
NASA NTRS2000

BOREAS HYD-5 Winter Surface Flux Data

The BOREAS HYD-5 team collected tower flux, surface meteorological, and surface temperature data on a frozen lake (Namekus Lake) and in a mature jack pine forest in the Beartrap Creek watershed. Both sites were located in the BOREAS SSA. The objective of this study was to characterize the winter energy and water vapor fluxes, as well as related properties (such as snow density, depth, temperature, and melt) for forested and nonforested areas of the boreal forest. Data were collected on Namekus Lake in the winters of 1994 and 1996, and at Beartrap Creek in the winter of 1994 only. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Harding, Richard↗
NASA NTRS2018

The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis

The NASA Eulerian Snow On Sea Ice Model (NESOSIM) is a new, open-source snow budget model that is currentlyconfigured to produce daily estimates of the depth and density of snow on sea ice across the Arctic Ocean throughthe accumulation season. NESOSIM has been developed in a three-dimensional Eulerian framework and includes two(vertical) snow layers and several simple parameterizations (accumulation, wind packing, advection_divergence, blowingsnow lost to leads) to represent key sources and sinks of snow on sea ice. The model is forced with daily inputs of snowfall and near-surface winds (from reanalyses), sea ice concentration (from satellite passive microwave data) and sea ice drift (from satellite feature tracking) during the accumulation season (August through April). In this study, we present the NESOSIM formulation, calibration efforts, sensitivity studies and validation efforts across an Arctic Ocean domain (100 km horizontal resolution). The simulated snow depth and density are calibrated with in situ data collected on drifting ice stations during the 1980s. NESOSIM shows strong agreement with the in situ seasonal cycles of snow depth and density, and shows good (moderate) agreement with the regional snow depth (density) distributions. NESOSIM is run for a contemporary period (2000 to 2015), with the results showing strong sensitivity to the reanalysis derived snowfall forcing data, with the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the Japanese Meteorological Agency 55-year reanalysis (JRA-55) forced snow depths generally higher than ERA-Interim,and the Arctic System Reanalysis (ASR) generally lower. We also generate and force NESOSIM with a consensus "median" daily snowfall dataset from these reanalyses.The results are compared against snow depth estimates derived from NASA's Operation IceBridge (OIB) snow radar data from 2009 to 2015, showing moderate_strong correlations and root mean squared errors of 10 cm depending on the OIB snow depth product analyzed, similar to the comparisons between OIB snow depths and the commonly used modified Warren snow depth climatology. Potential improvements to this initial NESOSIM formulation are discussed in the hopes of improving the accuracy and reliability of these simulated snow depths and densities.

Petty, Alek A.↗
DOE OSTI2019

Depth and elevation of floodplain fine sediment along the East River near Crested Butte, Colorado measured in 2016 and 2017

The depth of floodplain fine sediment was measured at 1,601 points along the East River near Crested Butte, Colorado spanning a study reach approximately 800 m in length in 2016 and 2017. These depths are being used to estimate the volume of floodplain sediment present along the study reach, converted into mass of sediment using bulk density measurements, and finally used to estimate the mass of organic carbon stored in the floodplain based on elemental analysis of percent organic carbon content. Recorded depths include a minimum of 1 cm, a median of 56 cm, a maximum of 175 cm, and a mean with standard deviation of 61 ± 34 cm. This data include a csv file of the coordinates for each point in NAD 83 UTM zone 13, measured sediment depths, distance from the river channel active during 2015 measured using geographic information systems, the elevation of the floodplain surface derived from 0.5-m resolution lidar, and the elevation of the underlying gravel/bedrock surface, and in some cases the distance from the active channel measured in the field along the sampling transect. Also included is an ESRI ArcMap shapefile of the measurement points complete with the data listed above.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Lightning and Radar Measures of Mixed Phase Updraft Variability in Tracked Storms During the TRACER Field Campaign in Houston, Texas

Properties of 7488 thunderstorms are summarized for June-September 2022 during the TRACER field campaign Houston, Texas using polarimetric weather radar and VHF 3D lightning mapping array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day, and cells with lightning had stronger polarimetric columns. Track-level correlation of lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region.

TRACER field campaign↗