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NASA NTRS2018

Reconstruction of Snow on Arctic Sea Ice

Snow on Arctic sea ice is a poorly observed variable that plays an important role in the Arctic climate system and impacts the remote sensing systems that monitor Arctic sea ice. We present and validate a reconstruction of Arctic snow depth based on observed sea ice motion and snowfall derived from reanalysis data. Overall, the reconstruction is in good agreement with direct measurements of snow depth from Operation IceBridge, slightly underestimating mean IceBridge snow depth. At the local scale (10 km), the reconstruction is more skilled than a weighted climatology over first year ice, but underestimates deeper snow over multiyear ice. Reconstructions of single buoy snow depths are unskilled, but the reconstruction shows skill in simulating the mean snow depth across all buoys. Spring snow depths show a lowtohigh crossArctic gradient and tend to be greatest in the Atlantic sector of the eastern Arctic. The relationship between ice type (multiyear or firstyear ice) and snow depth previously documented in the western Arctic is not evident in the eastern Arctic. Using ice type to weight snow depths for satellite ice thickness retrievals may not be justifiable in the eastern Arctic. Reconstructed snow depth across the Arctic shows significant interannual variability, suggesting that use of a fixed snow depth climatology may lead to biases in retrieved ice thickness and its variability. However, interannual variability in panArctic mean snow depth is comparable or smaller than the uncertainty in both the reconstruction and IceBridge, highlighting the need for high accuracy snow depth products and reconstructions.

sea ice↗

DOE OSTI2017

Completion Report for Well ER-2-2 Corrective Action Unit 97: Yucca Flat/Climax Mine

Well ER-2-2 was drilled for the U.S. Department of Energy, Nevada National Security Administration Nevada Field Office in support of the Underground Test Area (UGTA) Activity. The well was drilled from January 17 to February 8, 2016, as part of the Corrective Action Investigation Plan (CAIP) for Corrective Action Unit 97: Yucca Flat/Climax Mine, Nevada Test Site, Nevada. The primary purpose of the well was to collect hydrogeologic data to evaluate uncertainty in the flow and transport conceptual model and its contamination boundary forecasts, and to detect radionuclides in groundwater from the CALABASH (U2av) underground test. Well ER-2-2 was not completed as planned due to borehole stability problems. As completed, the well includes a piezometer (p1) to 582 meters (m) (1,909 feet [ft]) below ground surface (bgs) installed in the Timber Mountain lower vitric-tuff aquifer (TMLVTA) and a 12.25-inch (in.) diameter open borehole to 836 m (2,743 ft) bgs in the Lower tuff confining unit (LTCU). A 13.375-in. diameter carbon-steel casing is installed from the surface to a depth of 607 m (1,990 ft) bgs. Data collected during borehole construction include composite drill cutting samples collected every 3.0 m (10 ft), geophysical logs to a depth of 672.4 m (2,206 ft) bgs, water-quality measurements (including tritium), water-level measurements, and slug test data. The well penetrated 384.05 m (1,260 ft) of Quaternary alluvium, 541.93 m (1,778 ft) of Tertiary Volcanics (Tv) rocks, and 127.71 m (419 ft) of Paleozoic carbonates. The stratigraphy and lithology were generally as expected. However, several of the stratigraphic units were significantly thicker then predicted—principally, the Tunnel formation (Tn), which had been predicted to be 30 m (100 ft) thick; the actual thickness of this unit was 268.22 m (880 ft). Fluid depths were measured in the borehole during drilling as follows: (1) in the piezometer (p1) at 552.15 m (1,811.53 ft) bgs and (2) in the main casing (m1) at 551.69 m (1,810.01 ft) bgs. As expected, field measurements for tritium were above the Safe Drinking Water Act limit (20,000 picocuries per liter). All Fluid Management Plan requirements were met.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Completion Report for Well ER-2-2 Corrective Action Unit 97: Yucca Flat/Climax Mine, Revision 1

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

The effect of voxel size on dose distribution in Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

Recently, Monte Carlo (MC) calculation method has reported as the most accurate method of predicting dose distributions in radiotherapy. The MC code system (especially DOSXYZnrc) has been used to investigate the different voxel (volume elements) sizes effect on the accuracy of dose distributions. To investigate this effect on dosimetry parameters, calculations were made with three different voxel sizes. The effects were investigated with dose distribution calculations for seven voxel sizes: 1 × 1 × 0.1 cm{sup 3}, 1 × 1 × 0.5 cm{sup 3}, and 1 × 1 × 0.8 cm{sup 3}. The 1 × 10{sup 9} histories were simulated in order to get statistical uncertainties of 2%. This simulation takes about 9-10 hours to complete. Measurements are made with field sizes 10 × 10 cm2 for the 6 MV photon beams with Gaussian intensity distribution FWHM 0.1 cm and SSD 100.1 cm. MC simulated and measured dose distributions in a water phantom. The output of this simulation i.e. the percent depth dose and dose profile in d{sub max} from the three sets of calculations are presented and comparisons are made with the experiment data from TTSH (Tan Tock Seng Hospital, Singapore) in 0-5 cm depth. Dose that scored in voxels is a volume averaged estimate of the dose at the center of a voxel. The results in this study show that the difference between Monte Carlo simulation and experiment data depend on the voxel size both for percent depth dose (PDD) and profile dose. PDD scan on Z axis (depth) of water phantom, the big difference obtain in the voxel size 1 × 1 × 0.8 cm{sup 3} about 17%. In this study, the profile dose focused on high gradient dose area. Profile dose scan on Y axis and the big difference get in the voxel size 1 × 1 × 0.1 cm{sup 3} about 12%. This study demonstrated that the arrange voxel in Monte Carlo simulation becomes important.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2017

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Measuring surface fluxes in CAPE

Two stations (site 1612 and site 2008) were operated by the University of Georgia group from 6 July 1991 to 18 August 1991. The following data were collected continuously: surface energy fluxes (i.e., net radiation, soil heat fluxes, sensible heat flux and latent heat flux), air temperature, vapor pressure, soil temperature (at 1 cm depth), and precipitation. Canopy reflectance and light interception data were taken three times at each site between 6 July and 18 August. Soil moisture content was measured twice at each site.

Kanemasu, E. T.↗

DOE OSTI2019

3D Imaging of Geothermal Faults from a Vertical DAS Fiber at Brady Hot Spring, NV USA

In March 2016, arguably the most ambitious 4D (3D space + over time) active-source seismic survey for geothermal exploration in the U.S. was acquired at Brady Natural Laboratory, outside Fernley, Nevada. The four-week experiment included 191 vibroseis source locations, and approximately 130 m of distributed acoustic sensing (DAS) in a vertical well, located at the southern end of the survey area. The imaging of the geothermal faults is done with reverse time migration of the DAS data for both P-P and P-S events in order to generate 3D models of reflectivity, which can identify subsurface fault locations. Three scenarios of receiver data are explored to investigate the reliability of the reflectivity models obtained: (1) Migration of synthetic P-P and P-S DAS data, (2) migration of the observed field DAS data and (3) migration of pure random noise to better assess the validity of our results. The comparisons of the 3D reflectivity models from these three scenarios confirm that sections of three known faults at Brady produce reflected energy observed by the DAS. Two faults that are imaged are ~1 km away from the DAS well; one of these faults (middle west-dipping) is well-constructed for over 400 m along the fault’s strike, and 300 m in depth. These results confirm that the DAS data, together with an imaging engine such as reverse time migration, can be used to position important geothermal features such as faults.

10 SYNTHETIC FUELS↗

DOE OSTI2017

Surface Meteorology at Teller Site Stations, Seward Peninsula, Alaska, Ongoing from 2016

Meteorological data are currently being collected at two locations at the Teller Site, Seward Peninsula. This December 6, 2017 release includes data for: Teller Creek Station near TL_BSV (TELLER BOTTOM METEOROLOGICAL STATION) Station is located in the lower watershed in a tussock / willow transition zone and co-located with continuous snow depth measurements and subsurface measurements. Teller Creek Station near TL_IS_5 (TELLER TOP METEOROLOGICAL STATION) Station is located in the upper watershed and co-located with continuous snow depth measurements and subsurface measurements. Two types of data products are provided for these stations: First, meteorological and site characterization data grouped by sensor/measurement type (e.g., radiation or soil pit temperature and moisture). These are *.csv files. Second, a Data Visualization tool is provided for quick visualization of measurements over time at a station. Download the *_Visualizer.zip file, extract, and click on the 'index.html' file. Data values are the same in both products. Dataset DOI: 10.5440/1437633; https://doi.org/10.5440/1437633

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1998

Inversion of Crater Morphometric Data to Gain Insight on the Cratering Process

In recent years, morphometric data for Venus and several outer planet satellites have been collected, so we now have observational data of complex Craters formed in a large range of target properties. We present general inversion techniques that can utilize the morphometric data to quantitatively test various models of complex crater formation. The morphometric data we use in this paper are depth of a complex crater, the diameter at which the depth-diameter ratio changes, and onset diameters for central peaks, terraces, and peak rings. We tested the roles of impactor velocities and hydrostatic pressure vs. crustal strength, and we tested the specific models of acoustic fluidization (Melosh, 1982) and nonproportional growth (Schultz, 1988). Neither the acoustic fluidization model nor the nonproportional growth in their published formulations are able to successfully reproduce the data. No dependence on impactor velocity is evident from our inversions. Most of the morphometric data is consistent with a linear dependence on the ratio of crustal strength to hydrostatic pressure on a planet, or the factor c/pg.

Herrick, Robert R.↗

NASA NTRS1973

Identification of Geostructures of continental crust, particularly as they relate to mineral-resource evaluation

The author has identified the following significant results. Analysis of lineated lakes in the Umiat, Alaska area and comparison with known geology, gravity, and magnetic data in the the area suggest concealed structures exist at depth, possibly at or near basement, which may represent targets for petroleum exploration. Compilation of reconnaissance geologic data on 1:250,000 scale enlargements of ERTS-1 images near Corwin reveal structural and stratigraphic anomalies that suggest the Cretaceous sequence is less thick than supposed and is repeated in a series of plates superimposed by flat thrust faults. The structural style differs from that in coeval strata to the northeast, across the northwest-trending linear zone separating differing tectonic styles in older strata noted earlier. The regional extension of a fault known locally in the McCarthy area has been recognized; this fault appears to form the boundary of a significant terrane of mid-Paleozoic metamorphic rocks. ERTS-1 images are being used operationally, at 1:1,000,000 scale in the compilation of regional geologic maps, and at 1:250,000 scale in field mapping in the Brooks Range, in the study of faults in seismically active southern Alaska, in field-checking interpretations previously made from ERTS-1 imagery, and orthophoto base maps for geologic maps.

Gryc, G.↗

NASA NTRS2007

Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data

Researchers at JPL and Arizona State University conducted a comparative study of three candidate algorithms for estimating components of the Martian atmosphere, using raw (uncalibrated) data collected by the Thermal Emission Imaging System (THEMIS). THEMIS is an instrument onboard the Mars Odyssey spacecraft that acquires image data in five visible and nine infrared (IR) wavelength bands. The algorithms under study used data collected from eight of the nine IR bands to estimate the dust and water ice content of the atmosphere. Such an algorithm could be used in onboard data processing to trigger other algorithms that search for features of scientific interest and to reduce the volume of data transmitted to Earth. The algorithms studied were based on regression models. In the study, the optical depths estimated by these algorithms were compared with optical depths estimated in ground-based processing using fully calibrated data from both THEMIS and the Thermal Emission Spectrometer (TES). TES is an instrument onboard the Mars Global Surveyor spacecraft that also observes the planet at infrared wavelengths, but at a lower spatial resolution than THEMIS does. Of the algorithms studied, the one that performed best was based on a Gaussian Support Vector Machine regression model. The test results indicated that this algorithm, operating on the raw data, had error rates that were within the uncertainty associated with the estimates obtained by the groundbased analysis of the fully calibrated data. This level of fidelity demonstrates that these algorithms are sufficiently accurate for use in an onboard setting.

Bandfield, Joshua↗

DOE OSTI2019

Exploratory analysis of high-resolution power interruption data reveals spatial and temporal heterogeneity in electric grid reliability

Modern grid monitoring equipment enables utilities to collect detailed records of power interruptions. Here, these data are aggregated to compute publicly reported metrics describing high-level characteristics of grid performance. The current work explores the depth of insights that can be gained from public data, and the implications of losing visibility into heterogeneity in grid performance through aggregation. We present an exploratory analysis examining three years of high-resolution power interruption data collected by archiving information posted in real-time on the public-facing website of a utility in the Western United States. We report on the size, frequency and duration of individual power interruptions, and on spatio-temporal variability in aggregate reliability metrics. Our results show that metrics of grid performance can vary spatially and temporally by orders of magnitude, revealing heterogeneity that is not evidenced in publicly reported metrics. We show that limited access to granular information presents a substantive barrier to conducting detailed policy analysis, and discuss how more widespread data access could help to answer questions that remain unanswered in the literature to date. Lastly, given open questions about whether grid performance is adequate to support societal needs, we recommend establishing pathways to make high-resolution power interruption data available to support policy research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗

DOE OSTI2017

Energy dependence of nonlocal optical potentials

Recently, a variety of studies have shown the importance of including nonlocality in the description of reactions. The goal of this work is to revisit the phenomenological approach to determining nonlocal optical potentials from elastic scattering. We perform a χ 2 analysis of neutron elastic scattering data off 40 Ca, 90 Zr, and 208 Pb at energies E ≈ 5–40 MeV, assuming a Perey and Buck [Nucl. Phys. 32, 353 (1962)] or Tian et al. [Int. J. Mod. Phys. E 24, 1550006 (2015)] nonlocal form for the optical potential. We introduce energy and asymmetry dependencies in the imaginary part of the potential and refit the data to obtain a global parametrization. Independently of the starting point in the minimization procedure, an energy dependence in the imaginary depth is required for a good description of the data across the included energy range. We then present two parametrizations, both of which represent an improvement over the original potentials for the fitted nuclei as well as for other nuclei not included in our fit. Our results show that, even when including the standard Gaussian nonlocality in optical potential, a significant energy dependence is required to describe elastic-scattering data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary

Cloud droplet size and optical depth are the most fundamental properties for understanding cloud formation, dissipation and interactions with aerosol and drizzle. They are also a crucial determinant of Earth’s radiative and water-energy balances. However, these properties are poorly predicted in climate models. As a result, the response of clouds to climate change is one of the major sources of uncertainty in climate prediction.

47 OTHER INSTRUMENTATION↗

NASA NTRS1991

Recovery of reflectance from imaging spectrometer measured radiance using a radiative transfer code

Radiance data were acquired over part of the Clark Mountain Range, California in 1990 by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS). From these calibrated radiance data, the lateral distribution of water vapor in precipitable mm was recovered through analysis of the 940 nm water absorption. Surface pressure height was calculated from the 760 nm oxygen absorption band in the AVIRIS data. Surface slopes are estimated from relative elevations derived from the equivalent water vapor elevation for a standard atmosphere. Atmospheric optical depths measured at the Mountain Pass site in these data are extended to the entire region and varied based on the calculated surface pressure elevation. These parameters, derived from every AVIRIS spatial element, are used to constrain the LOWTRAN 7 radiative transfer code for the recovery of surface reflectance. Once transformed to reflectance, the imaging spectrometer data may be analyzed quantitatively for determination of surface composition, and compared with reflectance measurements acquired from different locations, times, and instruments.

Green, Robert O.↗

NASA NTRS2021

Evaluation of Clouds, Radiation, and Precipitation in CMIP6 Models Using Global Weather States Derived from ISCCP-H Cloud Property Data

A clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

Clouds↗

DOE OSTI2016

A new data processing technique for Rayleigh-Taylor instability growth experiments

Typical face-on experiments for Rayleigh-Taylor instability study involve the time-resolved radiography of an accelerated foil with line-of-sight of the radiography along the direction of motion. The usual method which derives perturbation amplitudes from the face-on images reverses the actual image transmission procedure, so the obtained results will have a large error in the case of large optical depth. In order to improve the accuracy of data processing, a new data processing technique has been developed to process the face-on images. This technique based on convolution theorem, refined solutions of optical depth can be achieved by solving equations. Furthermore, we discuss both techniques for image processing, including the influence of modulation transfer function of imaging system and the backlighter spatial profile. Besides, we use the two methods to the process the experimental results in Shenguang-II laser facility and the comparison shows that the new method effectively improve the accuracy of data processing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗