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NASA NTRS2002

ISO Key Project: Exploring The Full Range of Quasar/AGN Properties

While most of the work on this program has been completed, as previously reported, the portion of the program dealing with the sub topic of ISO LWS data analysis and reduction for the LWS Extragalactic Science Team and its leader, Dr. Howard Smith, is still active. This program in fact continues to generate results, and newly available computer modeling has extended the value of the datasets, As a result the team has requested and been granted an obtained a no-cost extension to this program, through December 31, 2003. The essence of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic data bases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program has the following goals: (1) refine the data analysis of ISO observations, to obtain deeper and better SNR results on selected sources. The ISO data itself underwent "pipeline 10" reductions in early 2001, and additional "hands-on data reduction packages" were supplied by the ISO teams in 2001. The Fabry-Perot database in particularly sensitive to noise can slight calibration errors. (2) model the atomic and molecular line shapes, in particular the OH lines, using revised Monte-Carlo techniques developed by the SWAS team at the Center for Astrophysics; (3) attend scientific meetings and workshops; (4) do E&PO activities related to infrared astrophysics and/or spectroscopy.

Wilkes, Belinda↗

NASA NTRS2003

Infrared Spectroscopy of Star Formation in Galactic and Extragalactic Regions

In this program we proposed to perform a series of spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, and to take advantage of other spectroscopic databases including the first results from SIRTF. Our emphasis has been on star formation in external, bright IR galaxies, but other areas of research have included young, low or high mass pre-main sequence stars in star formation regions, and the galactic center. The OH lines in the far infrared were proposed as one key focus of this inquiry, because the Principal Investigator (H. Smith) had a full set of OH IR lines from IS0 observations. It was planned that during the proposed 2-1/2 year timeframe of the proposal other data (including perhaps from SIRTF) would become available, and we intended to be responsive to these and other such spectroscopic data sets. The program has the following goals: 1) Refine the data analysis of IS0 observations to obtain deeper and better SNR results on selected sources. The IS0 data itself underwent pipeline 10 reductions in early 2001, and the more 'hands-on data reduction packages' have been released. The IS0 Fabry-Perot database is particularly sensitive to noise and can have slight calibration errors, and improvements are anticipated. We plan to build on these deep analysis tools and contribute to their development. Model the atomic and molecular line shapes, in particular the OH lines, using revised montecarlo techniques developed by the Submillimeter Wave Astronomy Satellite (SWAS) team at the Center for Astrophysics. 2) 3) Use newly acquired space-based SIRTF or SOFIA spectroscopic data as they become available, and contribute to these observing programs as appropriate. 4) Attend scientific meetings and workshops. 5) E&PO activities, especially as related to infrared astrophysics and/or spectroscopy.

Smith, Howard A.↗

NASA NTRS2004

Infrared Spectroscopy of Star Formation in Galactic and Extragalactic Regions

Frogel, Jay↗

NASA NTRS2005

Explore Full Range of QSO/AGN Properties

The goal of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory s Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic databases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program had the following goals: 1) Refine the data analysis of IS0 observations to obtain deeper and better SNR results on selected sources. The IS0 data itself underwent "pipeline 10" reductions in early 2001, and additional "hands-on data reduction packages" were supplied by the IS0 teams in 2001. The Fabry-Perot database is particularly sensitive to noise and slight calibration errors. 2) Model the atomic and molecular line shapes, in particular the OH lines, using revised monte- carlo techniques developed by the SWAS team at the Center for Astrophysics; 3) Attend scientific meetings and workshops; 4) Do E&PO activities related to infrared astrophysics and/or spectroscopy.

Oliversen, Ronald↗

DOE OSTI2026

Strong Lens Discoveries in DESI Legacy Imaging Surveys DR10 with Two Deep Learning Architectures

Abstract We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches. This is the first catalog of lens candidates covering nearly the entirety of the extragalactic sky south of declination δ ≈ +32 ∘ , all observed by DECam, covering ∼14,000 deg 2 . We impose a z -band magnitude cut of <20 in AB magnitude. We deploy a residual neural network and EfficientNet as an ensemble trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. The predictions from these two base models are aggregated using a meta-learner. After applying our ensemble to the survey data, we exclude known candidates and systems, and use our own visual inspection portal to rank images in the top 0.01 percentile of all neural network recommendations. We have found 811 lens candidates, five of which are confirmed through Euclid Quick Data Release (Q1). These include 484 new candidates in the Legacy Surveys DR9 footprint, all parts of which have been searched for strong lenses at least once before, either by our group or others. Combining the discoveries from this work with those from the first three papers in this series (335, 1210, and 1512), we have discovered a total of 3868 new candidates in the DESI Legacy Surveys.

Inchausti, Jose Carlos [University of San Francisc↗

NASA NTRS2021

Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction with Satellite Data for Rural Areas

This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multichemical transport model (CTM) (GEOS-Chem, WRF-Chem, and CMAQ) outputs, and ground observations. In Part I of the study, an ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125–300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non rural areas, referred to as “extended ground truth” or EGT, for the present day. Lastly, we applied the KF technique to reduce the forecast bias for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three CTMs for both today and next day show the best performance. Together, the two-part study develops a multimodel and multi-AOD bias-correction technique that has the potential to improve PM2.5 forecasts in both rural and non rural areas in near real time, and be readily implemented at state levels.

Huanxin Zhang↗

NASA NTRS1972

Pioneer 7 observations of the August 29, 1966, interplanetary shock-wave ensemble.

The detailed plasma (except for electrons) and magnetic field data from Pioneer 7 are presented for a proposed double-shock ensemble. The Ames Research Center plasma probe data are compared with that of the MIT probe. These data are compared with MHD theory to show that the discontinuities themselves satisfy the magnetic Hugoniot equations. The data are also compared with the theoretical predictions for the double-shock structure. The theory requires as input only the forward shock velocity, the original ambient solar wind conditions, and a reasonable assumption regarding the density and azimuthal magnetic field in the 'new' solar wind which is detected after passage of the reverse shock. A unique solution is then obtained for the theoretical piston and reverse shock positions as well as for the temporal plasma behavior for both infinite and finite electrical conductivities.

Dryer, M.↗

DOE OSTI2025

Joint state-parameter estimation for the reduced fracture model via the united filter

Here, in this paper, we introduce an effective United Filter method for jointly estimating the solution state and physical parameters in flow and transport problems within fractured porous media. Fluid flow and transport in fractured porous media are critical in subsurface hydrology, geophysics, and reservoir geomechanics. Reduced fracture models, which represent fractures as lower-dimensional interfaces, enable efficient multi-scale simulations. However, reduced fracture models also face accuracy challenges due to modeling errors and uncertainties in physical parameters such as permeability and fracture geometry. To address these challenges, we propose a United Filter method, which integrates the Ensemble Score Filter (EnSF) for state estimation with the Direct Filter for parameter estimation. EnSF, based on a score-based diffusion model framework, produces ensemble representations of the state distribution without deep learning. Meanwhile, the Direct Filter, a recursive Bayesian inference method, estimates parameters directly from state observations. The United Filter combines these methods iteratively: EnSF estimates are used to refine parameter values, which are then fed back to improve state estimation. Numerical experiments demonstrate that the United Filter method surpasses the state-of-the-art Augmented Ensemble Kalman Filter, delivering more accurate state and parameter estimation for reduced fracture models. This framework also provides a robust and efficient solution for PDE-constrained inverse problems with uncertainties and sparse observations.

Bayesian inference↗

NASA NTRS2002

Infrared Spectroscopy of Star Formation in Galactic and Extragalactic Regions

This report details work done in a project involving spectroscopic studies, including data analysis and modeling, of star-formation regions using an ensemble of archival space-based data including some from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, and other spectroscopic databases. We will include four kinds of regions: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star-formation regions; (3) star formation in external, bright IR (infrared) galaxies; and (4) the galactic center. During this period, work proceeded fully on track and on time. Details on workshops and conferences attended and research results are presented. A preprint article entitled 'The Far Infrared Lines of OH as Molecular Cloud Diagnostics' is included as an appendix.

Smith, Howard A.↗

NASA NTRS2003

ISO Key Project: Exploring the Full Range of Quasar/Agn Properties

While most of the work on this program has been completed, as previously reported, the portion of the program dealing with the subtopic of ISO LWS data analysis and reduction for the LWS Extragalactic Science Team and its leader, Dr. Howard Smith, is still active. This program in fact continues to generate results, and newly available computer modeling has extended the value of the datasets. As a result the team requests a one-year no-cost extension to this program, through 31 December 2004. The essence of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star-formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic databases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star-formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program has the following goals: 1) Refine the data analysis of ISO observations to obtain deeper and better SNR results on selected sources. The ISO data itself underwent 'pipeline 10' reductions in early 2001, and additional 'hands-on data reduction packages' were supplied by the ISO teams in 2001. The Fabry-Perot database is particularly sensitive to noise and slight calibration errors; 2) Model the atomic and molecular line shapes, in particular the OH lines, using revised Monte-Carlo techniques developed by the SWAS team at the Center for Astrophysics; 3) Attend scientific meetings and workshops; 4) Perform E&PO activities related to infrared astrophysics and/or spectroscopy.

Wilkes, Belinda↗

DOE OSTI2024

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

NASA NTRS2011

Calibrated Noise Measurements with Induced Receiver Gain Fluctuations

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory in science and engineering. These limitations were encountered when modeling the performance of radiometer calibration architectures and algorithms in the presence of non stationary receiver fluctuations. Analyses of measured signals have traditionally been limited to a single measurement series. Whereas in a radiometer that samples a set of noise references, the data collection can be treated as an ensemble set of measurements of the receiver state. Noise Assisted Data Analysis is a growing field of study with significant potential for aiding the understanding and modeling of non stationary processes. Typically, NADA entails adding noise to a signal to produce an ensemble set on which statistical analysis is performed. Alternatively as in radiometric measurements, mixing a signal with calibrated noise provides, through the calibration process, the means to detect deviations from the stationary assumption and thereby a measurement tool to characterize the signal's non stationary properties. Data sets comprised of calibrated noise measurements have been limited to those collected with naturally occurring fluctuations in the radiometer receiver. To examine the application of NADA using calibrated noise, a Receiver Gain Modulation Circuit (RGMC) was designed and built to modulate the gain of a radiometer receiver using an external signal. In 2010, an RGMC was installed and operated at the National Institute of Standards and Techniques (NIST) using their Noise Figure Radiometer (NFRad) and national standard noise references. The data collected is the first known set of calibrated noise measurements from a receiver with an externally modulated gain. As an initial step, sinusoidal and step-function signals were used to modulate the receiver gain, to evaluate the circuit characteristics and to study the performance of a variety of calibration algorithms. The receiver noise temperature and time-bandwidth product of the NFRad are calculated from the data. Statistical analysis using temporal-dependent calibration algorithms reveals that the natural occurring fluctuations in the receiver are stationary over long intervals (100s of seconds); however the receiver exhibits local non stationarity over the interval over which one set of reference measurements are collected. A variety of calibration algorithms have been applied to the data to assess algorithms' performance with the gain fluctuation signals. This presentation will describe the RGMC, experiment design and a comparative analysis of calibration algorithms.

Racette, Paul↗

NASA NTRS1991

Structure of a swirl-stabilized spray flame by imaging, laser Doppler velocimetry, and phase Doppler anemometry

Data are presented which describe the mean structure of a steady, swirl-stabilized, kerosene spray flame in the near-injector region of a research furnace. The data presented include ensemble-averaged results of schlieren, luminosity, and extinction imaging, measurement of the gas phase velocity field by laser Doppler velocimetry, and characterization of the condensed phase velocity by phase Doppler anemometry. The results of these studies define six key regions in the flame: the dense spray region; the rich, two-phase, fuel jet; the main air jet; the internal product recirculation zone; the external product recirculation zone; and the gaseous diffusion flame zone. The first five of these regions form a conical mixing layer which prepares the air and fuel for combustion. The air and fuel jets comprise the central portion of this mixing layer and are bounded on either side by the hot product gases of the internal and external recirculation zones. Entrainment of these product gases into the air/fuel streams provides the energy required to evaporate the fuel spray and initiate combustion. Intermittency of the internal recirculation and spray jet flows accounts for unexpected behavior observed in the aerodynamics of the two phases. The data reported herein are part of the database being accumulated on this spray flame for the purpose of detailed comparison with numerical modeling.

Edwards, C. F.↗

NASA NTRS2022

The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model

This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test such hypothesis across the Contiguous United States during April 2015 – December 2018. The performance of the proposed methodology is assessed for several modeled vegetation and water variables (evapotranspiration, net ecosystem exchange, and soil moisture) in terms of random errors and anomaly correlation coefficients against a set of independent validation datasets (i.e., Global Land Evaporation Amsterdam Model, FLUXCOM, and International Soil Moisture Network). Results show that the assimilation of leaf area index mostly improves the estimation of evapotranspiration and net ecosystem exchange, whereas the assimilation of surface soil moisture alone improves surface soil moisture content, especially in the western US, in terms of both root mean squared error and anomaly correlation coefficient. The joint assimilation of vegetation and soil moisture information combines the results of individual vegetation and soil moisture assimilations and reduces errors (and increases correlations with the reference datasets) in evapotranspiration, net ecosystem exchange, and surface soil moisture simulated by the land surface model. However, because soil moisture satellite observations only provide information on the water content in the top 5 cm of the soil column, the impact of the proposed data assimilation technique on root zone soil moisture is limited. This work moves one step forward in the direction of improving our estimation and understanding of land surface interactions using a multi-variate data assimilation approach, which can be particularly useful in regions of the world where ground observations are sparse or missing altogether.

Data assimilation↗

NASA NTRS2003

Resonance Effects in the NASA Transonic Flutter Cascade Facility

Investigations of unsteady pressure loadings on the blades of fans operating near the stall flutter boundary are carried out under simulated conditions in the NASA Transonic Flutter Cascade facility (TFC). It has been observed that for inlet Mach numbers of about 0.8, the cascade flowfield exhibits intense low-frequency pressure oscillations. The origins of these oscillations were not clear. It was speculated that this behavior was either caused by instabilities in the blade separated flow zone or that it was a tunnel resonance phenomenon. It has now been determined that the strong low-frequency oscillations, observed in the TFC facility, are not a cascade phenomenon contributing to blade flutter, but that they are solely caused by the tunnel resonance characteristics. Most likely, the self-induced oscillations originate in the system of exit duct resonators. For sure, the self-induced oscillations can be significantly suppressed for a narrow range of inlet Mach numbers by tuning one of the resonators. A considerable amount of flutter simulation data has been acquired in this facility to date, and therefore it is of interest to know how much this tunnel self-induced flow oscillation influences the experimental data at high subsonic Mach numbers since this facility is being used to simulate flutter in transonic fans. In short, can this body of experimental data still be used reliably to verify computer codes for blade flutter and blade life predictions? To answer this question a study on resonance effects in the NASA TFC facility was carried out. The results, based on spectral and ensemble averaging analysis of the cascade data, showed that the interaction between self-induced oscillations and forced blade motion oscillations is very weak and can generally be neglected. The forced motion data acquired with the mistuned tunnel, when strong self-induced oscillations were present, can be used as reliable forced pressure fluctuations provided that they are extracted from raw data sets by an ensemble averaging procedure.

Lepicovsky, J.↗

DOE OSTI2025

A Greening Future Elevates Flash Drought Risk in Northern Mid‐to‐High Latitudes

Flash droughts have become a growing concern, as they can emerge rapidly and increase the risk of crop failure. Although past studies have investigated the meteorological drivers and future changes of flash drought, why flash drought is more frequent over humid and vegetated regions remains underexplored. This study delves further into the mechanism by which vegetation regulates flash drought and its future change using observations from multiple data sets and large ensemble simulations from three Earth system models. On an interannual timescale, both observations and simulations show robust increases in flash drought frequency and a higher flash-to-sub-seasonal drought ratio during spring or antecedent conditions with dense vegetation, supporting the important role of vegetation in flash drought occurrence, especially in the northern mid-to-high latitudes. In the latter regions, the large ensemble simulations show robust increases in flash drought (e.g., 67% and 46% increases in Eastern U.S. and North Asia in 2050–2100 relative to 1950–2000 under the high emission scenario), where the growing season is lengthening. Although greening might suggest reduced drought stress, it drives precipitation-soil moisture-evapotranspiration decoupling by increasing evapotranspiration partitioning to transpiration. As transpiration can access deep soil water through the plant root system, its increased portion can weaken the constraints of concurrent precipitation on evapotranspiration, thus accelerating soil moisture depletion under high evaporative demand, driving a slow-to-rapid drought transition. How vegetation regulates flash drought by regulating surface moisture budget is supported by observations and simulations. Although warming supports early planting, agriculture may increasingly be threatened by surging flash drought risk.

Drought↗

DOE OSTI2026

How Well Can CMIP6 Models Represent the Observed Influence of the Pacific and Indian Oceans on the Indian Summer Monsoon Rainfall?

This study evaluates the ability of CMIP6 climate models to simulate the observed effects of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) on Indian summer monsoon rainfall (ISMR) variability. Using observational data and the large ensemble historical simulations of seven CMIP6 models from 1950 to 2014, we applied a cyclostationary linear inverse model (CS-LIM) to isolate the impacts of tropical Pacific SSTAs, Indian Ocean SSTAs and their interaction on the interannual variability of ISMR. Overall, CMIP6 models well reproduced the observed enhanced (reduced) ISMR variability from Pacific SSTAs (Indian Ocean SSTAs and the Indo-Pacific interaction), but with varying spatial patterns and magnitudes. While CESM2 and E3SM-2-0 showed the best agreement with observations for the effects of Pacific SSTAs and the Indo-Pacific interaction, respectively, CMIP6 models showed mixed results for the impacts from Indian Ocean SSTAs. Composite analysis of ISMR anomalies during the developing phases of pure and co-occurring El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events revealed that the impacts from Pacific SSTAs were captured reasonably well by E3SM-2-0, CESM2, MIROC6, and MPI-ESM1-2-LR, while E3SM-2-0 also showed the best agreement with observations for the effects from the Indo-Pacific interaction. However, all models showed substantial biases in simulating the Indian Ocean SSTA impacts on ISMR, especially for pure El Niño events. Overall, this study provides new insights into how individual CMIP6 models simulate the isolated impacts from the tropical Pacific and Indian Oceans, which has important applications for improving ISMR predictions and interpreting ISMR future projections.

monsoon↗

DOE OSTI2024

Wilkins: HPC in situ workflows made easy

In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however, face challenges in handling the growing complexity and diverse computational requirements of scientific tasks. In this work, we present Wilkins, an in situ workflow system that is designed for ease-of-use while providing scalable and efficient execution of workflow tasks. Wilkins provides a flexible workflow description interface, employs a high-performance data transport layer based on HDF5, and supports tasks with disparate data rates by providing a flow control mechanism. Wilkins seamlessly couples scientific tasks that already use HDF5, without requiring task code modifications. We demonstrate the above features using both synthetic benchmarks and two science use cases in materials science and cosmology.

HPC↗