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NASA NTRS2002

Optimal Extraction with Sub-sampled Line-Spread Functions

STIS long-slit medium resolution spectra reduced in CALSTIS extended-source mode with narrow extraction heights (GWIDTH=3 pixels) show photometric uncertainties of +/- 3% relative to point-source extractions. These uncertainties are introduced through interpolation in the spectral image rectification processing stage, and are correlated with the number of pixel crossings the spectral profile core encounters in the spatial direction. The line-spread-function may be determined as a function of pixel crossing- position from calibration data sub-sampled in the spatial direction. This line spread function will be applied to science data to perform optimal extractions and point- source de-blending. Wavelength and breathing effects will be studied. Viability of the method to de-convolve extended source 'blobs' will be investigated.

Collins, Nicholas R.↗

DOE OSTI2023

Spatially quasi-periodic bifurcations from periodic traveling water waves and a method for detecting bifurcations using signed singular values

We present a method of detecting bifurcations by locating zeros of a signed version of the smallest singular value of the Jacobian. This enables the use of quadratically convergent root-bracketing techniques or Chebyshev interpolation to locate bifurcation points. Only positive singular values have to be computed, though the method relies on the existence of an analytic or smooth singular value decomposition (SVD). The sign of the determinant of the Jacobian, computed as part of the bidiagonal reduction in the SVD algorithm, eliminates slope discontinuities at the zeros of the smallest singular value. We use the method to search for spatially quasi-periodic traveling water waves that bifurcate from large-amplitude periodic waves. The water wave equations are formulated in a conformal mapping framework to facilitate the computation of the quasi-periodic Dirichlet-Neumann operator. We find examples of pure gravity waves with zero surface tension and overhanging gravity-capillary waves. In both cases, the waves have two spatial quasi-periods whose ratio is irrational. We follow the secondary branches via numerical continuation beyond the realm of linearization about solutions on the primary branch to obtain traveling water waves that extend over the real line with no two crests or troughs of exactly the same shape. The pure gravity wave problem is of relevance to ocean waves, where capillary effects can be neglected. Such waves can only exist through secondary bifurcation as they do not persist to zero amplitude. The gravity-capillary wave problem demonstrates the effectiveness of using the signed smallest singular value as a test function for multi-parameter bifurcation problems. This test function becomes mesh independent once the mesh is fine enough.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Scaled Vecchia Approximation for Fast Computer-Model Emulation

Many scientific phenomena are studied using computer experiments consisting of multiple runs of a computer model while varying the input settings. Gaussian processes (GPs) are a popular tool for the analysis of computer experiments, enabling interpolation between input settings, but direct GP inference is computationally infeasible for large datasets. We adapt and extend a powerful class of GP methods from spatial statistics to enable the scalable analysis and emulation of large computer experiments. Specifically, we apply Vecchia’s ordered conditional approximation in a transformed input space, with each input scaled according to how strongly it relates to the computer-model response. The scaling is learned from the data by estimating parameters in the GP covariance function using Fisher scoring. Our methods are highly scalable, enabling estimation, joint prediction, and simulation in near-linear time in the number of model runs. In several numerical examples, our approach substantially outperformed existing methods.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2002

Determining Greenland Ice Sheet Accumulation Rates from Radar Remote Sensing

An important component of NASA's Program for Arctic Regional Climate Assessment (PARCA) is a mass balance investigation of the Greenland Ice Sheet. The mass balance is calculated by taking the difference between the areally Integrated snow accumulation and the net ice discharge of the ice sheet. Uncertainties in this calculation Include the snow accumulation rate, which has traditionally been determined by interpolating data from ice core samples taken from isolated spots across the ice sheet. The sparse data associated with ice cores juxtaposed against the high spatial and temporal resolution provided by remote sensing , has motivated scientists to investigate relationships between accumulation rate and microwave observations as an option for obtaining spatially contiguous estimates. The objective of this PARCA continuation proposal was to complete an estimate of surface accumulation rate on the Greenland Ice Sheet derived from C-band radar backscatter data compiled in the ERS-1 SAR mosaic of data acquired during, September-November, 1992. An empirical equation, based on elevation and latitude, is used to determine the mean annual temperature. We examine the influence of accumulation rate, and mean annual temperature on C-band radar backscatter using a forward model, which incorporates snow metamorphosis and radar backscatter components. Our model is run over a range of accumulation and temperature conditions. Based on the model results, we generate a look-up table, which uniquely maps the measured radar backscatter, and mean annual temperature to accumulation rate. Our results compare favorably with in situ accumulation rate measurements falling within our study area.

Jezek, Kenneth C.↗

NASA NTRS2020

Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: the Case of Rio deJaneiro, Brazil

Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001-2019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4mm/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12-35%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.

IMERG↗

DOE OSTI2026

Beyond interpolation: Physics-inspired gating transformers for extrapolating irradiation conditions to novel nuclear fuels

The qualification of advanced nuclear fuels relies on irradiation experiments in test reactors that emulate commercial conditions. Designing these tests requires accurate prediction of key irradiation quantities, particularly heat generation rate and burnup, yet obtaining them typically involves computationally expensive multi-step simulation workflows. We propose a physics-inspired gating transformer (PIGT) that integrates an inverse-square, distance-based attenuation into the encoder representation to bias attention toward physically relevant spatial relationships while retaining data-driven flexibility. Using MiniFuel irradiation data from the High Flux Isotope Reactor at Oak Ridge National Laboratory, we benchmark against ensemble methods, feedforward and recurrent networks, convolutional models, and standard transformers. While baseline models perform well under interpolation, they exhibit a pronounced generalization gap when evaluated on fuels not included in the training set. The proposed model consistently improves extrapolative accuracy and stability, yielding the strongest performance on unseen fuel configurations. These results indicate that a lightweight physics structure embedded within attention mechanisms can substantially improve robustness, enabling more reliable surrogate predictions to accelerate the design of nuclear fuel irradiation experiments.

Fuel qualification↗

DOE OSTI2018

Spatiotemporal interpolation of air pollutants in the Greater Cairo and the Delta, Egypt

Highlights: • Data from network of monitoring stations in Egypt are used for studying SO{sub 2}, NO{sub 2}, and PM{sub 10.} • Trans-Gaussian Spatiotemporal kriging is used as a spatiotemporal interpolation method. • The whole area under study is suffering from high values of PM{sub 10} throughout 2015. • For NO{sub 2} and SO{sub 2}, the highest value is noticed in February. • Concerns must be given to the monitoring network to improve the prediction precision. This paper analyses the spatiotemporal variability of air pollutants in Egypt using monthly averages from the air quality monitoring network from 2011 to 2015. Particulate Matters (PM{sub 10}) Nitrogen Dioxide (NO{sub 2}) and Sulfur Dioxide (SO{sub 2}), measured by the monitoring stations network are studied. A log transformation is applied for the three pollutants to achieve normality. The sum-metric function is utilized for modelling the spatiotemporal variogram as it gave the smallest Mean Squared Error (MSE) compared to other forms namely separable, metric, and product sum models. Therefore, employing the gstat package in R together with the trans-Gaussian spatiotemporal kriging, the maps are generated for the interpolated surfaces for the monthly averages of 2015 and the corresponding standard error values. These maps will help the decision maker to understand and visualize the spatial and temporal variability of the measured pollutants and hence undertake the necessary policies and decisions. The results show that the down town area has the highest pollutants levels. As concerns the temporal dimension, the highest values are depicted during the month of February as compared to the rest of the year. Furthermore, Egypt is suffering from a serious PM{sub 10} problem for the area and period under study that extremely exceed the WHO and Egyptian guidelines.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The algebraic structure of gravitational scrambling

We introduce a new algebraic framework to describe gravitational scrambling, including the semiclassical limit of any out-of-time-order correlation function that is built out of operator insertions separated by approximately the scrambling time. In two dimensions, the scrambling algebra, which we call a modular-twisted product, is defined in terms of two copies of the Leutheusser-Liu half-sided modular inclusion of von Neumann algebras; these describe early- and late-time operators respectively. In limits where the separation between insertions is taken to be either significantly greater or smaller than the scrambling time, the modular-twisted product reduces, respectively, to free- and tensor-product algebras that were previously studied in [arXiv:2209.10454]. In a sense, the modular-twisted product interpolates between these two products. Including the Hamiltonian in the scrambling algebra leads to a Type II$_\infty$ von Neumann algebra with finite renormalized entropies that interpolate between single-QES and multi-QES phases. We also describe how to generalize the modular-twisted product algebra to higher dimensions, including spatially localized boundary excitations.

FOS: Physical sciences↗

NASA NTRS1984

A SAR correlation algorithm which accommodates large-range migration

This paper presents an algorithm for azimuth correlation of synthetic aperture radar (SAR) data with extraordinarily large-range migration which cannot be accommodated by the existing frequency domain interpolation approach used in current Seasat SAR processing. A mathematical model is provided for the SAR range-correlated point-target response both in the spatial and frequency domains. A simple and efficient processing algorithm derived from the exact two-dimensional correlation algorithm is given. This algorithm enables azimuth correlation by two cascaded one-dimensional correlation steps. The first step is to transform the range-correlated SAR data into the frequency domain in azimuth, followed by a newly developed range convolution filter to correct the range-dispersed spectrum of the range-correlated point-target response (RCPTR). The second step is the frequency-domain range migration correction approach for the azimuth compression. Simulation results provided here indicate that this processing algorithm yields a satisfactory compressed impulse response for SAR data with large-range migration whereas previous methods were subject to a broadening of the impulse response along range.

Jin, M. Y.↗

NASA NTRS1985

Modal forced vibration analysis of aerodynamically excited turbosystems

Theoretical aspects of a new capability to determine the vibratory response of turbosystems subjected to aerodynamic excitation are presented. Turbosystems such as advanced turbopropellers with highly swept blades, and axial-flow compressors and turbines can be analyzed using this capability. The capability has been developed and implemented in the April 1984 release of the general purpose finite element program NASTRAN. The dynamic response problem is addressed in terms of the normal modal coordinates of these tuned rotating cyclic structures. Both rigid and flexible hubs/disks are considered. Coriolis and centripetal accelerations, as well as differential stiffness effects are included. Generally non-uniform steady inflow fields and uniform flow fields arbitrarily inclined at small angles with respect to the axis of rotation of the turbosystem are considered sources of aerodynamic excitation. The spatial non-uniformities are considered to be small deviations from a principally uniform inflow. Subsonic and supersonic relative inflows are addressed, with provision for linearly interpolating transonic airloads.

Elchuri, V.↗

NASA NTRS2017

Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.

GI↗

DOE OSTI2024

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗

NASA NTRS1977

High resolution imaging X-ray detector for astronomical measurements

The article describes the X-ray detector which will provide second-of-arc images for the HEAO-B X-ray observatory. The instrument uses microchannel plates as a photocathode surface and imaging photoelectron multiplier, and a crossed wire grid as a two-dimensional position-sensitive detector. Position determination is accomplished by electronic interpolation between the coarse grid wires. The detector provides the arrival time and position of each event which occurs within its field of view. Measurements of the spatial resolution (15 microns), temporal resolution (7.8 microsec), image distortion (less than 10 microns), uniformity of efficiency (less than plus or minus 10%), dark counting rate (0.2 cts/sq cm/s), and quantum efficiency (10% at 1.54 keV) of this detector are described. A summary of the procedure which was found useful during the initial turn-on of microchannel plates is given.

Henry, J. P.↗

NASA NTRS1980

Ultraviolet /UV/ emission line mapping of selected regions in the Orion Nebula

Digital processing of data from the International Ultraviolet Explorer (IUE) satellite are used to obtain monochromatic mosaic images of the most prominent UV spectra lines at 35 locations in the central region of the Orion Nebula. The image processing techniques include calculations of the spectrograph orientation and the thermal effects, normalization for exposure time, background subtraction, correction for sensitivity variation within the IUE spectrograph aperture, correction to an absolute flux scale, sample interpolation, and display on graphic devices. The resulting UV emission line intensity maps may be used in conjunction with observations of other wavelength regions to determine the spatial distribution of ionization and abundance levels of carbon and oxygen in Orion.

Turnrose, B. E.↗

NASA NTRS2013

3D Hail Size Distribution Interpolation/Extrapolation Algorithm

Radar data can usually detect hail; however, it is difficult for present day radar to accurately discriminate between hail and rain. Local ground-based hail sensors are much better at detecting hail against a rain background, and when incorporated with radar data, provide a much better local picture of a severe rain or hail event. The previous disdrometer interpolation/ extrapolation algorithm described a method to interpolate horizontally between multiple ground sensors (a minimum of three) and extrapolate vertically. This work is a modification to that approach that generates a purely extrapolated 3D spatial distribution when using a single sensor.

Lane, John↗

NASA NTRS2019

Global Assimilation of L-Band Brightness Temperature Observations from SMAP and SMOS into the Catchment Land Surface Model and Contribution to the Skill of Soil Moisture Estimates

The Soil Moisture Active Passive (SMAP) and Soil Moisture Ocean Salinity (SMOS) missions provide global observations of L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations at a resolution of ~40 km every 2-3 days. These observations have been available since 2015 from SMAP and since 2010 from SMOS.Soil moisture estimates from the separate assimilation of SMAP and SMOS Tb observations into land surface models were previously shown to improve over model-only estimates, thereby demonstrating the value of assimilating L-band Tb observations for soil moisture estimation. The assimilation experiments documented in the literature do not, however, establish whether the joint assimilation of SMAP and SMOS Tbs improves the skill of the resulting soil moisture estimates beyond what can be achieved with either set of observations alone. Moreover, because the published SMAP and SMOS results used different assimilation systems and configurations and applied different evaluation data and procedures, it is unclear whether the assimilation of SMAP-only or SMOS-only Tbs results in better soil moisture skill. In this presentation, we compare the results of three separate assimilation experiments for the period from April 2015 to present. The experiments utilize the SMAP Level-4 Soil Moisture (L4_SM) algorithm, which assimilates L-band Tb observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. Specifically, the three experiments presented here assimilate (i) SMAP Tbs only, as in the L4_SM product, (ii) SMOS Tbs only, after interpolation of 40° incidence angle, and (iii) both SMAP and SMOS Tbs. In all other respects, the configuration of three experiments is identical, as is the validation of the output. Preliminary results suggest that the joint assimilation of SMAP and SMOS Tbs yields the most skillful soil moisture estimates when compared to independent in situ measurements. Moreover, the skill of the SMAP-only assimilation exceeds that of the SMOS-only assimilation. The presentation provides an in-depth evaluation of the skill of the assimilation estimates vs. independent in situ and satellite measurements and in terms of statistics of the observation-minus-forecast residuals and analysis increments.

Reichle, Rolf↗

DOE OSTI2017

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics such as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.

14 SOLAR ENERGY↗

NASA NTRS1996

Objective Interpolation of Scatterometer Winds

Global wind fields are produced by successive corrections that use measurements by the European Remote Sensing Satellite (ERS-1) scatterometer. The methodology is described. The wind fields at 10-meter height provided by the European Center for Medium-Range Weather Forecasting (ECMWF) are used to initialize the interpolation process. The interpolated wind field product ERSI is evaluated in terms of its improvement over the initial guess field (ECMWF) and the bin-averaged ERS-1 wind field (ERSB). Spatial and temporal differences between ERSI, ECMWF and ERSB are presented and discussed.

Tang, Wenquing↗