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A review of remote sensing technology for lower tropospheric thermodynamic (TD) profiling is presented with focus on high accuracy and high temporal-vertical resolution. The contributions of these instruments to the understanding of the Earth system are assessed with respect to radiative transfer, land surface-atmosphere feedback, convection initiation, and data assimilation. We demonstrate that for progress in weather and climate research, TD profilers are essential. These observational systems must resolve gradients of humidity and temperature in the stable or unstable atmospheric surface layer close to the ground, in the mixed layer, in the interfacial layer—usually characterized by an inversion—and the lower troposphere. A thorough analysis of the current observing systems is performed revealing significant gaps that must be addressed to fulfill existing needs. We analyze whether current and future passive and active remote sensing systems can close these gaps. A methodological analysis and demonstration of measurement capabilities with respect to bias and precision is executed both for passive and active remote sensing including passive infrared and microwave spectroscopy, the global navigation satellite system, as well as water vapor and temperature Raman lidar and water vapor differential absorption lidar. Whereas passive remote sensing systems are already mature with respect to operational applications, active remote sensing systems require further engineering to become operational in networks. However, active remote sensing systems provide a smaller bias as well as higher temporal and vertical resolutions. For a suitable mesoscale network design, TD profiler system developments should be intensified and dedicated observing system simulation experiments should be performed.
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Radiation response of nanocrystalline ceria films deposited on a silicon substrate was investigated under a 3-MeV Au-ion irradiation at 300 K. A uniform grain growth cross the ceria films is observed and effective densification of the ceria thin films occurs during irradiation. The Au ion profiling was measured by secondary ion mass spectrometry (SIMS) and compared to the Au ion distribution predicted by the Stopping and Range of Ions in Solids (SRIM) code. It is observed that the Au-ion penetration depth is underestimated in comparison with the SIMS measurements. An overestimation of the electronic stopping power for heavy incident ions in the SRIM program may account for the discrepancies between the calculations and the SIMS experimental results. This work presents an approach to compensate the overestimation of the electronic stopping powers in the SRIM program by adjusting the nanocrystalline ceria target density to better predict the ion implantation profile.
Globus Nexus is a professionally hosted Platform-as-a-Service that provides identity, profile and group management functionality for the research community. Many collaborative e-Science applications need to manage large numbers of user identities, profiles, and groups. However, developing and maintaining such capabilities is often challenging given the complexity of modern security protocols and requirements for scalable, robust, and highly available implementations. By outsourcing this functionality to Globus Nexus, developers can leverage best-practice implementations without incurring development and operations overhead. Users benefit from enhanced capabilities such as identity federation, flexible profile management, and user-oriented group management. In this paper we present Globus Nexus, describe its capabilities and architecture, summarize how several e-Science applications leverage these capabilities, and present results that characterize its scalability, reliability, and availability.
The Cryogenic Dark Matter Search low ionization threshold experiment (CDMSlite) searches for interactions between dark matter particles and germanium nuclei in cryogenic detectors. The experiment has achieved a low energy threshold with improved sensitivity to low-mass (<10 GeV/c2) dark matter particles. We present an analysis of the final CDMSlite data set, taken with a different detector than was used for the two previous CDMSlite data sets. This analysis includes a data "salting" method to protect against bias, improved noise discrimination, background modeling, and the use of profile likelihood methods to search for a dark matter signal in the presence of backgrounds. We achieve an energy threshold of 70 eV and significantly improve the sensitivity for dark matter particles with masses between 2.5 and 10 GeV/c2 compared to previous analyses. We set an upper limit on the dark matter-nucleon scattering cross section in germanium of 5.4×10-42 cm2 at 5 GeV/c2, a factor of ~2.5 improvement over the previous CDMSlite result.
We present the results of an X-ray analysis of 80 galaxy clusters selected in the 2500 deg{sup 2} South Pole Telescope survey and observed with the Chandra X-ray Observatory. We divide the full sample into subsamples of ∼20 clusters based on redshift and central density, performing a joint X-ray spectral fit to all clusters in a subsample simultaneously, assuming self-similarity of the temperature profile. This approach allows us to constrain the shape of the temperature profile over 0 < r < 1.5R {sub 500}, which would be impossible on a per-cluster basis, since the observations of individual clusters have, on average, 2000 X-ray counts. The results presented here represent the first constraints on the evolution of the average temperature profile from z = 0 to z = 1.2. We find that high-z (0.6 < z < 1.2) clusters are slightly (∼30%) cooler both in the inner (r < 0.1R {sub 500}) and outer (r > R {sub 500}) regions than their low-z (0.3 < z < 0.6) counterparts. Combining the average temperature profile with measured gas density profiles from our earlier work, we infer the average pressure and entropy profiles for each subsample. Confirming earlier results from this data set, we find an absence of strong cool cores at high z, manifested in this analysis as a significantly lower observed pressure in the central 0.1R {sub 500} of the high-z cool-core subset of clusters compared to the low-z cool-core subset. Overall, our observed pressure profiles agree well with earlier lower-redshift measurements, suggesting minimal redshift evolution in the pressure profile outside of the core. We find no measurable redshift evolution in the entropy profile at r ≲ 0.7R {sub 500}—this may reflect a long-standing balance between cooling and feedback over long timescales and large physical scales. We observe a slight flattening of the entropy profile at r ≳ R {sub 500} in our high-z subsample. This flattening is consistent with a temperature bias due to the enhanced (∼3×) rate at which group-mass (∼2 keV) halos, which would go undetected at our survey depth, are accreting onto the cluster at z ∼ 1. This work demonstrates a powerful method for inferring spatially resolved cluster properties in the case where individual cluster signal-to-noise is low, but the number of observed clusters is high.
With Sloan Digital Sky Survey galaxy data and halo data from up-to-date N-body simulations within the ΛCDM framework we construct a semi-empirical catalog (SEC) of early-type galaxy-halo systems by making a self-consistent bivariate statistical match of stellar mass (M{sub *}) and velocity dispersion (σ) with halo virial mass (M{sub vir}) as demonstrated here for the first time. We then assign stellar mass profile and velocity dispersion profile parameters to each system in the SEC using their observed correlations with M{sub *} and σ. Simultaneously, we solve for dark matter density profile of each halo using the spherical Jeans equation. The resulting dark matter density profiles deviate in general from the dissipationless profile of Navarro-Frenk-White or Einasto and their mean inner density slope and concentration vary systematically with M{sub vir}. Statistical tests of the distribution of profiles at fixed M{sub vir} rule out the null hypothesis that it follows the distribution predicted by dissipationless N-body simulations for M{sub vir}∼<10{sup 13.5} {sup –} {sup 14.5} M{sub s}un. These dark matter profiles imply that dark matter density is, on average, enhanced significantly in the inner region of halos with M{sub vir}∼<10{sup 13.5} {sup –} {sup 14.5} M{sub s}un supporting halo contraction. The main characteristics of halo contraction are: (1) the mean dark matter density within the effective radius has increased by a factor varying systematically up to ≈ 3–4 at M{sub vir} = 10{sup 12} M{sub s}un, and (2) the inner density slope has a mean of (α) ≈ 1.3 with ρ{sub dm}(r)∝r{sup −α} and a halo-to-halo rms scatter of rms(α) ∼ 0.4–0.5 for 10{sup 12} M{sub s}un∼<M{sub vir}∼<10{sup 13} {sup –} {sup 14} M{sub s}un steeper than the NFW profile (α = 1). Based on our results we predict that halos of nearby elliptical and lenticular galaxies can, in principle, be promising targets for γ-ray emission from dark matter annihilation.
The fatty acid profile of plant oils determines their quality and uses. Saturated fatty acids are often not desirable from the standpoints of nutrition and some industrial applications. Camelina sativa is a re-emerged oilseed crop, however its oil needs to be improved to meet different application requirements. In this study, saturated fatty acids were greatly reduced by down-regulating genes encoding the fatty acyl-ACP thioesterases (FATB). An artificial microRNA (amiFATB) was created by replacing a microRNA sequence in the camelina Csa-miR159a gene with a FATB gene specific sequence. Seed-specific expression of amiFATB caused a 45% reduction of palmitic acid (16:0) and a 38% reduction of stearic acid (18:0) compared to wildtype seeds. The total saturated fatty acid content was decreased by 35% from 14.6% to 9.4% of total fatty acids. When amiFATB was expressed in a high-oleic acid transgenic line, it caused further increased oleic acid content. This work demonstrates that the FATB genes in camelina can be effectively knocked down by an artificial microRNA targeting gene-specific sequences, thus provides an additional tool to improve seed oils for desired properties.
This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.
Single crystalline 6H-SiC samples were irradiated at 150 K with 2 MeV Pt ions. The local volume swelling was determined by electron energy loss spectroscopy (EELS), and a nearly sigmoidal dependence on irradiation dose is observed. The disorder profiles and ion distribution were determined by Rutherford backscattering spectrometry (RBS), transmission electron microscopy, and secondary ion mass spectrometry. Since the volume swelling reaches 12% over the damage region at high ion fluence, the effect of lattice expansion is considered and corrected for in the analysis of RBS spectra to obtain depth profiles. Projectile and damage profiles are estimated by SRIM (Stopping and Range of Ions in Matter).When compared with the measured profiles, the SRIM code predictions of ion distribution and the damage profiles are underestimated due to significant overestimation of the electronic stopping power for the slow heavy Pt ions. By utilizing the reciprocity method, which is based on the invariance of the inelastic energy loss in ion-solid collisions against interchange of projectile and target atom, a much lower electronic stopping power is deduced. A simple approach, based on reducing the density of SiC target in SRIM simulation, is proposed to compensate the overestimated SRIM electronic stopping power values, which results in improved agreement between predicted and measured damage profiles and ion ranges.
The space-borne active sounders have been contributing invaluable vertically resolved information of atmospheric optical properties since the launch of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in 2006. To build long-term records from space-borne lidars useful for climate studies, one has to understand the differences between successive space lidars operating at different wavelengths, flying on different orbits, and using different viewing geometries, receiving paths, and detectors. In this article, we compare the results of Atmospheric Laser Doppler INstrument (ALADIN) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidars for the period from 28 June to 31 December 2019. First, we build a dataset of ALADIN–CALIOP collocated profiles (Δdist<1°; Δtime<6 h). Then we convert ALADIN's 355 nm particulate backscatter and extinction profiles into the scattering ratio vertical profiles SR(z) at 532 nm using molecular density profiles from Goddard Earth Observing System Data Assimilation System, version 5 (GEOS-5 DAS). And finally, we build the CALIOP and ALADIN globally gridded cloud fraction profiles CF(z) by applying the same cloud detection threshold to the SR(z) profiles of both lidars at the same spatial resolution. Before comparing the SR(z) and CF(z) profiles retrieved from the two analyzed lidar missions, we performed a numerical experiment to estimate the best achievable cloud detection agreement CDA norm (z) considering the differences between the instruments. We define CDA norm (z) in each latitude–altitude bin as the occurrence frequency of cloud layers detected by both lidars, divided by a cloud fraction value for the same latitude–altitude bin. We simulated the SR(z) and CF(z) profiles that would be observed by these two lidars if they were flying over the same atmosphere predicted by a global model. By analyzing these simulations, we show that the theoretical limit for CDA$_{norm}^{theor}$(z) for a combination of ALADIN and CALIOP instruments is equal to 0.81±0.07 at all altitudes. In other words, 19 % of the clouds cannot be detected simultaneously by two instruments due to said differences. The analyses of the actual observed CALIOP–ALADIN collocated dataset containing ~78 000 pairs of nighttime SR(z) profiles revealed the following points: (a) the values of SR(z) agree well up to ~3 km height. (b) The CF(z) profiles show agreement below ~3 km, where ~80 % of the clouds detected by CALIOP are detected by ALADIN as expected from the numerical experiment. (c) Above this height, the CDA$_{norm}^{obs}$(z) reduces to ~50 %. (d) On average, better sensitivity to lower clouds skews ALADIN's cloud peak height in pairs of ALADIN–CALIOP profiles by ~0.5±0.6 km downwards, but this effect does not alter the heights of polar stratospheric clouds and high tropical clouds thanks to their strong backscatter signals. (e) The temporal evolution of the observed CDA$_{norm}^{obs}$(z) does not reveal any statistically significant change during the considered period. This indicates that the instrument-related issues in ALADIN L0/L1 have been mitigated, at least down to the uncertainties of the following CDA$_{norm}^{obs}$(z) values: 68±12 %, 55±14 %, 34±14 %, 39±13 %, and 42±14 % estimated at 0.75, 2.25, 6.75, 8.75, and 10.25 km, respectively.
This paper describes in detail the QC and splicing methodology for KSC's 50- and 915-MHz DRWP measurements that generates an extensive archive of vertically complete profiles from 0.20-18.45 km. The concurrent POR from each archive extends from April 2000 to December 2009. MSFC NE applies separate but similar QC processes to each of the 50- and 915-MHz DRWP archives. DRWP literature and data examination provide the basis for developing and applying the automated and manual QC processes on both archives. Depending on the month, the QC'ed 50- and 915-MHz DRWP archives retain 52-65% and 16-30% of the possible data, respectively. The 50- and 915-MHz DRWP QC archives retain 84-91% and 85-95%, respectively, of all the available data provided that data exist in the non- QC'ed archives. Next, MSFC NE applies an algorithm to splice concurrent measurements from both DRWP sources. Last, MSFC NE generates a composite profile from the (up to) five available spliced profiles to effectively characterize boundary layer winds and to utilize all possible 915-MHz DRWP measurements at each timestamp. During a given month, roughly 23,000-32,000 complete profiles exist from 0.25-18.45 km from the composite profiles' archive, and approximately 5,000- 27,000 complete profiles exist from an archive utilizing an individual 915-MHz DRWP. One can extract a variety of profile combinations (pairs, triplets, etc.) from this sample for a given application. The sample of vertically complete DRWP wind measurements not only gives launch vehicle customers greater confidence in loads and trajectory assessments versus using balloon output, but also provides flexibility to simulate different DOL situations across applicable altitudes. In addition to increasing sample size and providing more flexibility for DOL simulations in the vehicle design phase, the spliced DRWP database provides any upcoming launch vehicle program with the capability to utilize DRWP profiles on DOL to compute vehicle steering commands, provided the program applies the procedures that this report describes to new DRWP data on DOL. Decker et al. (2015) details how SLS is proposing to use DRWP data and splicing techniques on DOL. Although automation could enhance the current DOL 50-MHz DRWP QC process and could streamline any future DOL 915-MHz DRWP QC and splicing process, the DOL community would still require manual intervention to ensure that the vehicle only uses valid profiles. If a program desires to use high spatial resolution profiles, then the algorithm could randomly add high-frequency components to the DRWP profiles. The spliced DRWP database provides lots of flexibility in how one performs DOL simulations, and the algorithms that this report provides will assist the aerospace and atmospheric communities that are interested in utilizing the DRWP.
We profile the local carrier concentration, n, across epitaxial InAs/GaAs quantum dots (QDs) consisting of 3D islands on top of a 2D alloy layer. We use scanning thermoelectric microscopy to measure a profile of the temperature gradient-induced voltage, which is converted to a profile of the local Seebeck coefficient, S. The S profile is then converted to a conduction band-edge profile and compared with Poisson-Schrodinger band-edge simulations. Our combined computational-experimental approach suggests a reduced carrier concentration in the QD center in comparison to that of the 2D alloy layer. The relative roles of free carrier trapping and/or dopant expulsion are discussed.
The effect of lithium (Li) wall coatings on scrape-off-layer (SOL) turbulence in the National Spherical Torus Experiment (NSTX) is modeled with the Lodestar SOLT (SOL Turbulence) code. Specifically, the implications for the SOL heat flux width of experimentally observed, Li-induced changes in the pedestal profiles are considered. The SOLT code used in the modeling has been expanded recently to include ion temperature evolution and ion diamagnetic drift effects. This work focuses on two NSTX discharges occurring pre- and with-Li deposition. The simulation density and temperature profiles are constrained, inside the last closed flux surface only, to match those measured in the two experiments, and the resulting drift-interchange-driven turbulence is explored. The effect of Li enters the simulation only through the pedestal profile constraint: Li modifies the experimental density and temperature profiles in the pedestal, and these profiles affect the simulated SOL turbulence. The power entering the SOL measured in the experiments is matched in the simulations by adjusting “free” dissipation parameters (e.g., diffusion coefficients) that are not measured directly in the experiments. With power-matching, (a) the heat flux SOL width is smaller, as observed experimentally by infrared thermography and (b) the simulated density fluctuation amplitudes are reduced with Li, as inferred for the experiments as well from reflectometry analysis. The instabilities and saturation mechanisms that underlie the SOLT model equilibria are also discussed.
As leadership computing facilities grow their storage capacity into the multi- petabyte range, the number of files and directories leap into the scale of billions. A complete profiling of such a parallel file system in a production environment presents a unique challenge. On one hand, the time, resources, and negative performance impact on production users can make regular profiling difficult. On the other hand, the result of such profiling can yield much needed understanding of the file system's general characteristics, as well as provide insight to how users write and access their data on a grand scale. This paper presents a lightweight and scalable profiling solution that can efficiently walk, analyze, and profile multi-petabyte parallel file systems. This tool has been deployed and is in regular use on very large-scale production parallel file systems at both Oak Ridge National Lab's Oak Ridge Leadership Facility (OLCF) and Lawrence Livermore National Lab's Livermore Computing (LC) facilities. We present the results of our initial analysis on the data collected from these two large-scale production systems, organized into three use cases: (1) file system snapshot and composition, (2) striping pattern analysis for Lustre, and (3) simulated storage capacity utilization in preparation for future file systems. Our analysis shows that on the OLCF file system, over 96% of user files exhibit the default stripe width, potentially limiting performance on large files by underutilizing storage servers and disks. Our simulated block analysis quantitatively shows the space overhead when doing a forklift system migration. It also reveals that due to the difference in system compositions (OLCF vs. LC), we can achieve better performance and space trade-offs by employing different native file system block sizes.
As part of the U.S. DOE EVs@Scale consortium Next-Gen Profiles (NGP) project, the profile capture of production electric vehicles undergoing high power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), and EVSE limitations. Nominal conditions are defined to be ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against its nominal condition profile counterpart to highlight the variance across less desirable starting conditions within a single EV. Under nominal conditions, most EVs can achieve the original equipment manufacturer (OEM) rated peak-power and charge times. Peak power across EVs has variance due to the vehicle design, battery topology, charging strategy, etc. These 10-100% nominal preconditioned charge profiles across 13 EVs (11 light-duty (LD), 2 heavy-duty (HD)) were used for analysis in power curve analysis, power distribution, SOC and range comparison, thermal impacts of current draw, battery pack size and energy charged, and ramp rates. Power curve analysis show the uniqueness in power vs time curves across all EVs, breaking down the features of a typical profile and where variation is typically seen. Power distribution results showed that over 50% of charge time is spent below 50kW and only 12.1% is spent above 200kW. SOC and range performance yielded different top performing EVs when exploring goals of performance from SOC and range gained after 10-min (EV2) and 20-min (EV8), and time-to-achieve 80% SOC (EV8) and 200 miles of range (EV1). Current draw from 400-volt EVs had a higher thermal impact to cable/connector temperatures when compared to 800-volt EVs, due to a higher current requirement to achieve similar power levels. There was high variance in C rating, a useful metric when comparing the relationship between peak/average charge session power and relative battery pack size, across EVs under test. Ramp rates during initial power transfer were examined, fastest and slowest speeds ranging from 192.5kW/second to 2.6kW/second respectively. A similar analysis of ramp rates was also conducted for OCPP curtailment testing, where EVs underwent a 2-minute 65A curtailment request before returning to full-power charge. Under off-nominal conditions, most EVs experienced variation from the nominal condition profiles. EVs that underwent the full set of NGP defined testing conditions were compared, analysis of which was categorized by 800-volt and 400-volt EVs. It should be noted that the 800-volt EVs had significantly higher peak power ratings than the 400-volt EVs, and thus were more prone to variance. Initial state of charge, battery temperature, and vehicle condition had a considerable impact on peak power levels and charge time for the 800-volt vehicles under test. EVSE limited tests lowered achievable power down to 200kW, greatly impacted 800-volt charging power, and had little to no effect on 400-volt charging power. Adapter testing was performed on a single 400-volt EV, where power and current limitations were found but overall charge time was not significantly impacted. Adapter and boost converter testing was performed on a single 800-volt EV, where both charge power and charge time were greatly impacted. Charge profiles are unique, and comparing such requires analysis that examines starting conditions, vehicle and battery topologies,
Assessment of space vehicle loads and trajectories during design requires a large sample of wind profiles at the altitudes where winds affect the vehicle. Traditionally, this altitude region extends from near 8-14 km to address maximum dynamic pressure upon ascent into space, but some applications require knowledge of measured wind profiles at lower altitudes. Such applications include crew capsule pad abort and plume damage analyses. Two Doppler Radar Wind Profiler (DRWP) systems exist at the United States Air Force (USAF) Eastern Range and at the National Aeronautics and Space Administration's Kennedy Space Center. The 50-MHz DRWP provides wind profiles every 3-5 minutes from roughly 2.5-18.5 km, and five 915-MHz DRWPs provide wind profiles every 15 minutes from approximately 0.2-3.0 km. Archived wind profiles from all systems underwent rigorous quality control (QC) processes, and concurrent measurements from the QC'ed 50- and 915-MHz DRWP archives were spliced into individual profiles that extend from about 0.2-18.5 km. The archive contains combined profiles from April 2000 to December 2009, and thousands of profiles during each month are available for use by the launch vehicle community. This paper presents the details of the QC and splice methodology, as well as some attributes of the archive.