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NASA NTRS1990

Tropical Pacific moisture variability

The objectives are to describe synoptic scale variability of moisture over the tropical Pacific Ocean and the systems leading to this variability; implement satellite analysis procedures in support of this effort, and to incorporate additional satellite information into operational analysis forecast systems at the National Meteorological Center (NMC). Composite satellite radiance patterns describe features detectable well before the development of synoptic scale tropical plumes. These typical features were extracted from historical files of Tiros Operational Vertical Sounder (TOVS) radiance observations for a pair of tropical plumes which developed during January 1989. Signals were inserted into the NMC operational medium range forecast model and a suite of model integrations were conducted. Many of the 48 h model errors of the historical forecasts were eliminated by the inclusion of more complete satellite observations. Three studies in satellite radiance analysis progressed. An analysis which blended TOVS moisture channels, OLR observations and European Center for Medium Weather Forecasts (ECMWF) model analysis to generate fields of total precipitable water comparable to those estimated from Scanning Multichannel Microwave Radiometer (SMMR) mu-wave observations. This study demonstrated that a 10 y climatology of precipitable water over the oceans is feasible, using available infrared observations (OLR and TOVS) and model analysis (ECMWF, NMC or similar quality). The estimates are sensitive to model quality and the estimating model must be updated with operational model changes. Coe developed a set of tropical plume and ITCZ composites from TOVS observations, and from NMC and ECMWF analyses which had been passed through a radiative transfer model to simulate TOVS radiances. The composites have been completed as well as many statistical diagnostics of individual TOVS channels. Analysis of the computations is commencing. Chung has initiated a study of the differences between TOVS observed vapor structure during El Nino Southern Oscillation (ENSO) (1983) and non-ENSO (1984) years. Preliminary diagnosis demonstrates gross moisture changes between warm and cold sea surface temperature episodes.

Mcguirk, James P.↗

NASA NTRS2011

TRMM-Based Lightning Climatology

Gridded climatologies of total lightning flash rates seen by the spaceborne Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) have been updated. OTD collected data from May 1995 to March 2000. LIS data (equatorward of about 38 deg) has been added for 1998-2010. Flash counts from each instrument are scaled by the best available estimates of detection efficiency. The long LIS record makes the merged climatology most robust in the tropics and subtropics, while the high latitude data is entirely from OTD. The mean global flash rate from the merged climatology is 46 flashes per second. The peak annual flash rate at 0.5 deg scale is 160 fl/square km/yr in eastern Congo. The peak monthly average flash rate at 2.5 scale is 18 fl/square km/mo, from early April to early May in the Brahmaputra Valley of far eastern India. Lightning decreases in this region during the monsoon season, but increases further north and west. A monthly average peak from early August to early September in northern Pakistan also exceeds any monthly averages from Africa, despite central Africa having the greatest yearly average. Most continental regions away from the equator have an annual cycle with lightning flash rates peaking in late spring or summer. The main exceptions are India and southeast Asia, with springtime peaks in April and May. For landmasses near the equator, flash rates peak near the equinoxes. For many oceanic regions, the peak flash rates occur in autumn. This is particularly noticeable for the Mediterranean and North Atlantic. Landmasses have a strong diurnal cycle of lightning, with flash rates generally peaking between 3-5 pm local solar time. The central United States flash rates peak later, in late evening or early night. Flash rates peak after midnight in northern Argentina. These regions are known for large, intense, long-lived mesoscale convective systems.

Cecil, Daniel J.↗

NASA NTRSDate not supplied

Phenomena Portal: Large- Scale Visual Exploration of Atmospheric Phenomena

The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.

Muthukumaran Ramasubramanian↗

DOE OSTI2014

Ultrafast reduction of the total magnetization in iron

Surprisingly, if a ferromagnet is exposed to an ultrafast laser pulse, its apparent magnetization is reduced within less than a picosecond. Up to now, the total magnetization, i.e., the average spin polarization of the whole valence band, was not detectable on a sub-picosecond time scale. Here, we present experimental data, confirming the ultrafast reduction of the total magnetization. Soft x-ray pulses from the free electron laser in Hamburg (FLASH) extract polarized cascade photoelectrons from an iron layer excited by a femtosecond laser pulse. The spin polarization of the emitted electrons is detected by a Mott spin polarimeter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1976

Jupiter at five microns

The paper summarizes the information obtained in recent maps of Jupiter at 5 microns, a frequency at which the gases in Jupiter have a relatively low opacity. It is highly possible that 5-micron hot spots are breaks in the cloud deck permitting observation of the hot lower layers of the atmosphere. Many 5-micron sources coincide with blue visual features, but the details of the correspondence need further investigation. Large-scale changes in the appearance of the planet occur at 5 microns on time scales of months; these changes are sufficiently dramatic to produce detectable variations in the whole-disk flux from the planet. Their correspondence to large-scale changes in visual features is not yet determined.

Armstrong, K. R.↗

DOE OSTI2015

The Atacama cosmology telescope: Lensing of CMB temperature and polarization derived from cosmic infrared background cross-correlation

We present a measurement of the gravitational lensing of the Cosmic Microwave Background (CMB) temperature and polarization fields obtained by cross-correlating the reconstructed convergence signal from the first season of Atacama Cosmology Telescope Polarimeter data at 146 GHz with Cosmic Infrared Background (CIB) fluctuations measured using the Planck satellite. Using an effective overlap area of 92.7 square degrees, we detect gravitational lensing of the CMB polarization by large-scale structure at a statistical significance of 4.5σ. Combining both CMB temperature and polarization data gives a lensing detection at 9.1σ significance. A B-mode polarization lensing signal is present with a significance of 3.2σ. We also present the first measurement of CMB lensing–CIB correlation at small scales corresponding to l>2000. Null tests and systematic checks show that our results are not significantly biased by astrophysical or instrumental systematic effects, including Galactic dust. Fitting our measurements to the best-fit lensing-CIB cross-power spectrum measured in Planck data, scaled by an amplitude A, gives A=1.02{sub −0.08}{sup +0.12}(stat.) ± 0.06(syst.), consistent with the Planck results.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1999

Characterizing the Small Scale Structure in Clusters of Galaxies

We have applied a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies to several clusters. Three of these clusters show interesting structure. In addition to the small scale structure in surface brightness, we have searched for temperature structure using Advanced Satellite for Cosmology and Astrophysics (ASCA) observations. For A754, we find a filamentary structure, similar to that previously detected in A85. For A119, we find small scale structure associated with both cool and hot regions with a hot filament extending to the northeast. For A1750, one of the first clusters to show substructure from Einstein, we have a rederived the substructure from the ROSAT observations. The ASCA observations show a hot region between the two small scale features - sub-clusters. The hot region shows that the two subclusters are merging and producing a shock wave at the leading edge of the interaction. This analysis had been applied to a sample of 17 clusters to determine the radial distribution of substructure in a sample. The number of detected substructures was rather small and it was decided to select a different cluster sample at larger redshift. This provided a larger radial range over which substructure could be detected. This new cluster sample also includes about 20 clusters and is being analyzed. Finally, we are considering how to compare the substructure parameters of nearby clusters with a more distant sample to see if one can extract cosmological information. Since substructure frequency should depend on the cosmological density parameter, it may be possible to derive new constraints by comparing nearby and distant clusters.

Forman, William R.↗

NASA NTRS1982

An analysis of Seasat SAR for detecting geologic linears

The value of Seasat synthetic aperture radar (SAR) imagery for detecting geologic linears was assessed in a study of an 89,000 sq km section of New York's Adirondack Mountains. A photographic print of optically processed, 1:500,000 scale SAR imagery (one look direction) was analyzed visually, and the detected linears were compared to those recorded on a 1:250,000 scale geologic map. Eighty percent of the 4,170 km of mapped, geologic linears were detected with the SAR imagery. Moreover, nearly 6,900 km of unmapped linears were also detected. Of these, an estimated 90 percent could be observed on high altitude aerial photographs. The relationship between SAR image detection of linears and the different types of indicators (e.g., straight valleys or shorelines) is reported.

Yan, S.-Y.↗

DOE OSTI2026

The SPT-3G+ Experiment on the South Pole Telescope

Observations of the cosmic microwave background (CMB) offer an unparalleled opportunity to advance our understanding of fundamental physics. SPT-3G+ is an upgraded receiver for the arcminute-resolution South Pole Telescope (SPT) that plans to deploy in late 2028. SPT-3G+ will increase the CMB mapping speed of SPT by nearly an order of magnitude over the currently installed SPT-3G receiver. SPT-3G+ will have ~24,000 transition-edge sensor (TES) bolometers in two frequency bands with center frequencies at 95 GHz and 150 GHz that will be read out with microwave multiplexing. SPT-3G+ will measure the CMB lensing spectrum and galaxy clusters to constrain the growth of structure, dark matter, and dark energy. SPT-3G+ will also reach critical thresholds on inflationary constraints by combining data with BICEP/Keck, forming the South Pole Observatory (SPO). BICEP/Keck has deep degree-angular scale measurements but is currently delensing-limited, while SPT-3G+ will provide deep lensing measurements. Forecasts show that SPO will reach an uncertainty on the tensor-to-scalar ratio $r$ of $\sigma(r) \sim 1.2\times 10^{-3}$ by 2034. A detection at these levels would provide evidence of inflation and probe new physics at grand unified theory energy scales, while no detection would exclude large classes of models and shift the scientific paradigm describing the early universe. I will give an overview of SPT-3G+ including its design and current status.

Simon, Sara M. [Fermilab] (ORCID:0009000006683584)↗

DOE OSTI2018

Characterization of an Ionization Readout Tile for nEXO

Anewdesign for the anode of a time projection chamber, consisting of a charge-detecting "tile", is investigated for use in large scale liquid xenon detectors. The tile is produced by depositing 60 orthogonal metal charge-collecting strips, 3 mm wide, on a 10 cm 10 cm fused-silica wafer. These charge tiles may be employed by large detectors, such as the proposed tonne-scale nEXO experiment to search for neutrinoless double-beta decay. Modular by design, an array of tiles can cover a sizable area. The width of each strip is small compared to the size of the tile, so a Frisch grid is not required. A grid-less, tiled anode design is beneficial for an experiment such as nEXO, where a wire tensioning support structure and Frisch grid might contribute radioactive backgrounds and would have to be designed to accommodate cycling to cryogenic temperatures. The segmented anode also reduces some degeneracies in signal reconstruction that arise in large-area crossed-wire time projection chambers. A prototype tile was tested in a cell containing liquid xenon. Very good agreement is achieved between the measured ionization spectrum of a 207Bi source and simulations that include the microphysics of recombination in xenon and a detailed modeling of the electrostatic field of the detector. An energy resolution E=5.5% is observed at 570 keV, comparable to the best intrinsic ionization-only resolution reported in literature for liquid xenon at 936 V/cm.

Jewell, M J.↗

DOE OSTI2021

Multiresolution classification of turbulence features in image data through machine learning

During large-scale simulations, intermediate data products such as image databases have become popular due to their low relative storage cost and fast in-situ analysis. Serving as a form of data reduction, these image databases have become more acceptable to perform data analysis on. In this work, we present an image-space detection and classification system for extracting vortices at multiple scales through wavelet-based filtering. A custom image-space descriptor is used to encode a large variety of vortex-types and a machine learning system is trained for fast classification of vortex regions. By combining a radial-based histogram descriptor, a bag of visual words feature descriptor, and a support vector machine, our results show that we are able to detect and classify vortex features at various sizes at multiple scales. Once trained, our framework enables the fast extraction of vortices on new, unknown image datasets for flow analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Photovoltaic inverter-based quantification of snow conditions and power loss

Snow is a significant challenge for photovoltaic (PV) systems at northern latitudes, where the pace of deployment is rapid but snow-related power losses can exceed 30% of annual production. Accurate snow-related power loss estimation methods for utility-scale sites can support snow mitigation strategies, inform resource planning and validate predictive snow-loss models. This study builds on our previous work on inverter-based detection of snow, and its implications for utility-scale power production, by validating the accuracy of our snow-loss method across different PV sites and system designs and highlighting its value in bringing greater visibility to PV plant operations in winter. Our estimation method is both novel and scalable, requiring only standard monitoring data to correlate snow-related losses with meteorological data. As demonstrated here, our validation method involved three main steps: 1) estimation of performance losses for multiple systems by comparing measured inverter data to modeled data; 2) application of a detection framework to identify which performance losses are snow-related; and 3) comparison of snow-related losses among three utility-scale sites differing in tilt angle. Results show that utility-scale systems at higher tilt angles consistently shed snow more quickly/completely than their lower-tilt counterparts. Further, monthly and seasonal snow losses are inversely and non-linearly correlated with tilt angle when normalized for cumulative snowfall. These results are consistent with the findings of previous studies and support the broad applicability of this method to fixed-tilt utility-scale PV systems around the world that routinely experience snow-related performance losses.

Cooper, Emma C. (ORCID:0000000190554098)↗

NASA NTRS1976

The application of an optical Fourier spectrum analyzer on detecting defects in mass-produced satellite photographs

Various defects in mass-produced pictures transmitted to earth from a satellite are investigated. It is found that the following defects are readily detectable via Fourier spectrum analysis: (1) bit slip, (2) breakup causing loss of image, and (3) disabled track at the top of the imagery. The scratches made on the film during mass production, which are difficult to detect by visual observation, also show themselves readily in Fourier spectrum analysis. A relation is established between the number of scratches, their width and depth and the intensity of their Fourier spectra. Other defects that are found to be equally suitable for Fourier spectrum analysis or visual (image analysis) detection are synchronous loss without blurring of image, and density variation in gray scale. However, the Fourier spectrum analysis is found to be unsuitable for detection of such defects as pin holes, annotation error, synchronous loss with blurring of images, and missing image in the beginning of the work order. The design of an automated, real time system, which will reject defective films, is treated.

Athale, R.↗

DOE OSTI2021

Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates

Abstract. We consider the problem of estimating the ensemble sizes required to characterize the forced component and the internal variability of a number of extreme metrics. While we exploit existing large ensembles, our perspective is that of a modeling center wanting to estimate a priori such sizes on the basis of an existing small ensemble (we assume the availability of only five members here). We therefore ask if such a small-size ensemble is sufficient to estimate accurately the population variance (i.e., the ensemble internal variability) and then apply a well-established formula that quantifies the expected error in the estimation of the population mean (i.e., the forced component) as a function of the sample size n, here taken to mean the ensemble size. We find that indeed we can anticipate errors in the estimation of the forced component for temperature and precipitation extremes as a function of n by plugging into the formula an estimate of the population variance derived on the basis of five members. For a range of spatial and temporal scales, forcing levels (we use simulations under Representative Concentration Pathway 8.5) and two models considered here as our proof of concept, it appears that an ensemble size of 20 or 25 members can provide estimates of the forced component for the extreme metrics considered that remain within small absolute and percentage errors. Additional members beyond 20 or 25 add only marginal precision to the estimate, and this remains true when statistical inference through extreme value analysis is used. We then ask about the ensemble size required to estimate the ensemble variance (a measure of internal variability) along the length of the simulation and – importantly – about the ensemble size required to detect significant changes in such variance along the simulation with increased external forcings. Using the F test, we find that estimates on the basis of only 5 or 10 ensemble members accurately represent the full ensemble variance even when the analysis is conducted at the grid-point scale. The detection of changes in the variance when comparing different times along the simulation, especially for the precipitation-based metrics, requires larger sizes but not larger than 15 or 20 members. While we recognize that there will always exist applications and metric definitions requiring larger statistical power and therefore ensemble sizes, our results suggest that for a wide range of analysis targets and scales an effective estimate of both forced component and internal variability can be achieved with sizes below 30 members. This invites consideration of the possibility of exploring additional sources of uncertainty, such as physics parameter settings, when designing ensemble simulations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

A Structured Grid Based Solution-Adaptive Technique for Complex Separated Flows

The objective of this work was to enhance the predictive capability of widely used computational fluid dynamic (CFD) codes through the use of solution adaptive gridding. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. In order to study the accuracy and efficiency improvements due to the grid adaptation, it is necessary to quantify grid size and distribution requirements as well as computational times of non-adapted solutions. Flow fields about launch vehicles of practical interest often involve supersonic freestream conditions at angle of attack exhibiting large scale separate vortical flow, vortex-vortex and vortex-surface interactions, separated shear layers and multiple shocks of different intensity. In this work, a weight function and an associated mesh redistribution procedure is presented which detects and resolves these features without user intervention. Particular emphasis has been placed upon accurate resolution of expansion regions and boundary layers. Flow past a wedge at Mach=2.0 is used to illustrate the enhanced detection capabilities of this newly developed weight function.

Thornburg, Hugh↗

DOE OSTI2022

Light-Duty Vehicle Trip Classification Using One-Class Novelty Detection and Exhaustive Feature Extraction

Travel mode classification within travel survey data sets, especially light-duty vehicle (LDV) trips, is foundational, though nontrivial, to emerging mobility systems, travel behavior analysis, and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. The detection approaches are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the dataset requirements. This work proposes an LDV trip detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique - one-class support vector machines (OCSVMs) - and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size and feature selection, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multi-modal trip prediction.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Compiler-Assisted Detection of Transient Memory Errors

The probability of bit flips in hardware memory systems is projected to increase significantly as memory systems continue to scale in size and complexity. Effective hardware-based error detection and correction requires that the complete data path, involving all parts of the memory system, be protected with sufficient redundancy. First, this may be costly to employ on commodity computing platforms and second, even on high-end systems, protection against multi-bit errors may be lacking. Therefore, augmenting hardware error detection schemes with software techniques is of consider- able interest. In this paper, we consider software-level mechanisms to comprehensively detect transient memory faults. We develop novel compile-time algorithms to instrument application programs with checksum computation codes so as to detect memory errors. Unlike prior approaches that employ checksums on computational and architectural state, our scheme verifies every data access and works by tracking variables as they are produced and consumed. Experimental evaluation demonstrates that the proposed comprehensive error detection solution is viable as a completely software-only scheme. We also demonstrate that with limited hardware support, overheads of error detection can be further reduced.

def-use analysis↗

DOE OSTI2014

High-Q CMOS-integrated photonic crystal microcavity devices

Integrated optical resonators are necessary or beneficial in realizations of various functions in scaled photonic platforms, including filtering, modulation, and detection in classical communication systems, optical sensing, as well as addressing and control of solid state emitters for quantum technologies. Although photonic crystal (PhC) microresonators can be advantageous to the more commonly used microring devices due to the former’s low mode volumes, fabrication of PhC cavities has typically relied on electron-beam lithography, which precludes integration with large-scale and reproducible CMOS fabrication. Here, we demonstrate wavelength-scale polycrystalline silicon (pSi) PhC microresonators with Qs up to 60,000 fabricated within a bulk CMOS process. Quasi-1D resonators in lateral p-i-n structures allow for resonant defect-state photodetection in all-silicon devices, exhibiting voltage-dependent quantum efficiencies in the range of a few 10 s of %, few-GHz bandwidths, and low dark currents, in devices with loaded Qs in the range of 4,300–9,300; one device, for example, exhibited a loaded Q of 4,300, 25% quantum efficiency (corresponding to a responsivity of 0.31 A/W), 3 GHz bandwidth, and 30 nA dark current at a reverse bias of 30 V. This work demonstrates the possibility for practical integration of PhC microresonators with active electro-optic capability into large-scale silicon photonic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗