Search NASA⌕ Search

SEARCH · Search NASA

Results for “Observation Data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Biogeochemical Protocols and Diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF [subscript] 6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Carbon↗
NASA NTRS1977

A search for hard X-rays from five strong extragalactic radio sources

Data from the University of California at San Diego (UCSD) hard X-ray instrument on OSO-7 have been used to search the regions containing 3C 390.3, M87, 3C 273, 3C 111, and 3C 129. We have a weak detection of 3C 390.3 and a possible detection of 3C 111. Sensitive upper limits on hard X-rays have been obtained for the other objects. The available observational data indicate a correlation between hard X-ray emission, self-absorbed gigahertz radio emission, and strong optical emission lines in extragalactic sources. Self-Compton X-ray models have been calculated for the sources observed in this paper, and the angular sizes, lifetimes, and B fields in these sources have been estimated. These model calculations agree with existing VLBI and time variability data.

Mushotzky, R. F.↗
NASA NTRS2021

Strong Regional Influence of Climatic Forcing Datasets on Global Crop Model Ensembles

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Agricultural Model Intercomparison and Improvement↗
DOE OSTI2025

Differential cross section measurements for the production of top quark pairs and of additional jets using dilepton events from pp collisions at $\sqrt{s}$ = 13 TeV

Differential cross sections for top quark pair ($\textrm{t}\overline{\textrm{t}}$) production are measured in proton-proton collisions at a center-of-mass energy of 13 TeV using a sample of events containing two oppositely charged leptons. The data were recorded with the CMS detector at the CERN Large Hadron Collider and correspond to an integrated luminosity of 138 fb −1 . The differential cross sections are measured as functions of kinematic observables of the $\textrm{t}\overline{\textrm{t}}$ system, the top quark and antiquark and their decay products, as well as of the number of additional jets in the event. The results are presented as functions of up to three variables and are corrected to the parton and particle levels. When compared to standard model predictions based on quantum chromodynamics at different levels of accuracy, it is found that the calculations do not always describe the observed data. The deviations are found to be largest for the multi-differential cross sections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Recommended conventions for reporting results from direct dark matter searches

Abstract The field of dark matter detection is a highly visible and highly competitive one. In this paper, we propose recommendations for presenting dark matter direct detection results particularly suited for weak-scale dark matter searches, although we believe the spirit of the recommendations can apply more broadly to searches for other dark matter candidates, such as very light dark matter or axions. To translate experimental data into a final published result, direct detection collaborations must make a series of choices in their analysis, ranging from how to model astrophysical parameters to how to make statistical inferences based on observed data. While many collaborations follow a standard set of recommendations in some areas, for example the expected flux of dark matter particles (to a large degree based on a paper from Lewin and Smith in 1995), in other areas, particularly in statistical inference, they have taken different approaches, often from result to result by the same collaboration. We set out a number of recommendations on how to apply the now commonly used Profile Likelihood Ratio method to direct detection data. In addition, updated recommendations for the Standard Halo Model astrophysical parameters and relevant neutrino fluxes are provided. The authors of this note include members of the DAMIC, DarkSide, DARWIN, DEAP, LZ, NEWS-G, PandaX, PICO, SBC, SENSEI, SuperCDMS, and XENON collaborations, and these collaborations provided input to the recommendations laid out here. Wide-spread adoption of these recommendations will make it easier to compare and combine future dark matter results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks. Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bridging the Gap between Cosmological Simulations with Graph Neural Networks and Domain Adaptation

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross dataset tasks (up to 28% better relative error and up to almost an order of magnitude better χ 2 ). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

CHANDRA OBSERVATIONS OF COMETS C/2012 S1 (ISON) AND C/2011 L4 (PanSTARRS)

We present our results on the Chandra X-ray Observatory Advanced CCD Imaging Spectrometer (ACIS) observations of the bright Oort Cloud comets C/2012 S1 (ISON) and C/2011 L4 (PanSTARRS). ISON was observed between 2013 October 31–November 06 during variable speed solar wind (SW), and PanSTARRS was observed between 2013 April 17–23 during fast SW. ISON produced an extended parabolic X-ray morphology consistent with a collisionally thick coma, while PanSTARRS demonstrated only a diffuse X-ray-emitting region. We consider these emissions to be from charge exchange (CX) and model each comet's emission spectrum from first principles accordingly. Our model agrees with the observational spectra and also generates composition ratios for heavy, highly charged SW ions interacting with the cometary atmosphere. We compare our derived SW ion compositions to observational data and find a strong agreement between them. These results further demonstrate the utility of CX emissions as a remote diagnostics tool of both astrophysical plasma interaction and SW composition. In addition, we observe potential soft X-ray emissions via ACIS around 0.2 keV from both comets that are correlated in intensity to the hard X-ray emissions between 0.4–1.0 keV. We fit our CX model to these emissions, but our lack of a unique solution at low energies makes it impossible to conclude if they are cometary CX in origin. Finally, we discuss probable emission mechanism sources for the soft X-rays and explore new opportunities these findings present in understanding cometary emission processes via Chandra.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1980

X-ray quasars

Observational data for the seven quasars or Seyfert-quasar transition objects identified with X-ray sources is reviewed for radio, infrared, optical, ultraviolet, X-ray and gamma-ray frequencies. The observational histories of the quasars 3C 273, MR 2251-178 and 0241+622 and the quasar-like Seyfert nuclei Fairall-9, Mk 509, IC 4329A and IIIZw 2 are discussed in detail, and it is noted that their X-ray variability and spectra do not differentiate them from Seyfert nuclei, supporting the similarity between the several types of active extragalactic nuclei. The space density of the six objects (excluding 3C 273) within 600 Mpc is found to be comparable to that of other Seyferts and quasars, suggesting that X-ray emitting objects constitute a substantial fraction of the luminous transition objects in the neighborhood of the Galaxy. It is also pointed out that observations of the X-ray variability of these objects, which indicates that the X-rays originate from compact regions, represent a promising means for the further understanding of the emission process.

Bradt, H. V.↗
NASA NTRS1984

Two-dimensional infrared detector arrays

An introduction to overall IR array concepts and particular array designs is presented, and examples of laboratory and observational data obtained with IR arrays are given. Hybrid array designs, extrinsic silicon accumulation-mode charge injection devices, and switched-FET or switched-sample photoconductor techniques are summarized. Three recent astronomical observation projects which used IR arrays are examined.

Mccreight, C. R.↗
NASA NTRS1987

On the 9.25 minute X ray oscillations of V471 Tauri

The X-ray oscillations observed in the eclipsing spectroscopic binary V471 Tau by Exosat (Jensen, 1985) and attributed to rotational modulation of an X-ray-opaque pole due to He and metals accreted onto the DA2 white dwarf component (Jensen, 1986) are investigated theoretically. The observational data are summarized in a table and compared with the results of numerical simulations of the accretion of wind/flare material onto the white dwarf. The rotational modulation model is found to reproduce the observed line features only if the magnetic field is strong (about 10 kG), the accretion rate is about 10 to the -15th solar mass/yr, and the polar cap area is much larger than the theoretical lower limit of 5.7 x 10 to the 14th sq cm. It is recommended that nonradial g-mode oscillations of the white dwarf be investigated as an alternative explanation.

Sion, Edward M.↗
NASA NTRS1995

Analytic MHD Theory for Earth's Bow Shock at Low Mach Numbers

A previous MHD theory for the density jump at the Earth's bow shock, which assumed the Alfven M(A) and sonic M(s) Mach numbers are both much greater than 1, is reanalyzed and generalized. It is shown that the MHD jump equation can be analytically solved much more directly using perturbation theory, with the ordering determined by M(A) and M(s), and that the first-order perturbation solution is identical to the solution found in the earlier theory. The second-order perturbation solution is calculated, whereas the earlier approach cannot be used to obtain it. The second-order terms generally are important over most of the range of M(A) and M(s) in the solar wind when the angle theta between the normal to the bow shock and magnetic field is not close to 0 deg or 180 deg (the solutions are symmetric about 90 deg). This new perturbation solution is generally accurate under most solar wind conditions at 1 AU, with the exception of low Mach numbers when theta is close to 90 deg. In this exceptional case the new solution does not improve on the first-order solutions obtained earlier, and the predicted density ratio can vary by 10-20% from the exact numerical MHD solutions. For theta approx. = 90 deg another perturbation solution is derived that predicts the density ratio much more accurately. This second solution is typically accurate for quasi-perpendicular conditions. Taken together, these two analytical solutions are generally accurate for the Earth's bow shock, except in the rare circumstance that M(A) is less than or = 2. MHD and gasdynamic simulations have produced empirical models in which the shock's standoff distance a(s) is linearly related to the density jump ratio X at the subsolar point. Using an empirical relationship between a(s) and X obtained from MHD simulations, a(s) values predicted using the MHD solutions for X are compared with the predictions of phenomenological models commonly used for modeling observational data, and with the predictions of a modified phenomenological model proposed recently. The similarities and differences between these results are illustrated using plots of X and a(s) predicted for the Earth's bow shock. The plots show that the new analytic solutions agree very well with the exact numerical MHD solutions and that these MHD solutions should replace the corresponding phenomenological relations in comparisons with data. Furthermore, significant differences exist between the standoff distances predicted at low M(A) using the MHD models versus those predicted by the new modified phenomenological model. These differences should be amenable to observational testing.

Grabbe, Crockett L.↗
NASA NTRSDate not supplied

Solar Flare Catalog for SPICE Instrument on the Solar Orbiter

Studying the solar corona, the outermost layer of solar atmosphere, is a pivotal part of understanding the dynamic relations between solar activity and the solar wind, which can disrupt the near-Earth environment. Solar flares emit electromagnetic radiation in the solar corona, capable of releasing large amounts of energy in a matter of minutes. Flares can also be associated with Coronal Mass Ejections (CMEs) and affect Earth’s ionosphere. One instrument that can be used to study flares is the Spectral Imaging of the Coronal Environment (SPICE) instrumentaboard the Solar Orbiter (SolO). SPICE is a high-resolution extreme ultraviolet stigmatic slit spectrometer that covers emission lines formed from the solar chromosphere to corona. Since SPICE is a stigmatic slit spectrometer, the instrument can only take in data from a small spatial area on the Sun at a time. Due to the fast and unpredictable nature of flare events, it can be difficult to determine if and when SPICE has observed a flare. For this reason, we have created a catalog of flares observed by SPICE. This catalog of observational data was assembledby cross referencing data between different solar missions, including data from SolO’s E xtreme Ultraviolet Imager (EUI) and Spectrometer Telescope for Imaging X-rays (STIX), Solar Dynamics Observatory’s Atmospheric Imaging Assembly (SDO/AIA) instrument, and the Geostationary Operational Environmental Satellite (GOES-R). Supplemental analysis of the SPICE solar flare data includes Gaussian line fitting for flares of particular interest. The catalog can be utilized to locate and study coronal loop structures and flare ribbons. This SPICE solar flare catalog and additional supplemental analysis allows for the ease of identification of useful SPICE spectral data and multi-instrument analysis in order to study solar flare activity. It will be open for use by the Solar Orbiter and broader Heliophysics communities.

Anneliese L. Schmidt↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks (up to $28\%$ better relative error and up to almost an order of magnitude better $\chi^2$). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Documentation and Validation of the Goddard Earth Observing System (GEOS) Data Assimilation System, Version 4

This document describes the structure and validation of a frozen version of the Goddard Earth Observing System Data Assimilation System (GEOS DAS): GEOS-4.0.3. Significant features of GEOS-4 include: version 3 of the Community Climate Model (CCM3) with the addition of a finite volume dynamical core; version two of the Community Land Model (CLM2); the Physical-space Statistical Analysis System (PSAS); and an interactive retrieval system (iRET) for assimilating TOVS radiance data. Upon completion of the GEOS-4 validation in December 2003, GEOS-4 became operational on 15 January 2004. Products from GEOS-4 have been used in supporting field campaigns and for reprocessing several years of data for CERES.

Suarez, Max J.↗
DOE OSTI2018

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with the observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Widespread Wildfires Over the Western United States in 2020 Linked to Emissions Reductions During COVID-19

Widespread wildfires struck western United States in 2020, directly damaging properties and threatening human lives. Meanwhile, the COVID-19 pandemic rapidly spread across the globe in 2020, which disrupted human activities and resulted in substantial reductions in anthropogenic emissions. Here, we investigate the effects of the emissions reductions of aerosols, precursors, and greenhouse gases during the pandemic on wildfire weather conditions in 2020 over western United States by using an earth system model together with observational data. We show that the COVID-19 emissions reductions in model experiments increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains 10-40% of the observed increase in the risk of wildfires over western United States in 2020. In conclusion, this study suggests that COVID-19-related abrupt emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

The dynamics of the intergalactic medium in the vicinity of clusters of galaxies

Numerical solutions to the problem of infall of matter into clusters of galaxies are presented. It is assumed that the universe can be described by a Friedmann cosmological model with a Hubble constant 50 km/s/Mpc. It is found that physically reasonable models having a deceleration parameter of 1/2 lead to excessive X-ray emission from clusters of galaxies. Models including a heat flux due to thermal conduction, heating of the intracluster medium by galaxy motions, and a gas outflow from the galaxies in the cluster are discussed, and the results are compared with the observational data in both the X-ray and radio bands. It is concluded that the density parameter must be less than 0.2 in order that the predicted X-ray emission not exceed that observed. No models have been found which give a good description of the observed cluster X-ray sources, with the exception of a fully adiabatic model in a high-density universe.

Lea, S. M.↗