Engineering Papers⌕ Search

SEARCH · Engineering Papers

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 685 records · Page 38

Constraining the break of spatial diffeomorphism invariance with Planck data

The current most accepted paradigm for the early universe cosmology, the inflationary scenario, shows a good agreement with the recent Cosmic Microwave Background (CMB) and polarization data. However, when the inflation consistency relation is relaxed, these observational data exclude a larger range of red tensor tilt values, prevailing the blue ones which are not predicted by the minimal inflationary models. Recently, it has been shown that the assumption of spatial diffeomorphism invariance breaking (SDB) in the context of an effective field theory of inflation leads to interesting observational consequences. Among them, the possibility of generating a blue tensor spectrum, which can recover the specific consistency relation of the String Gas Cosmology, for a certain choice of parameters. We use the most recent CMB data to constrain the SDB model and test its observational viability through a Bayesian analysis assuming as reference an extended ΛCDM+tensor perturbation model, which considers a power-law tensor spectrum parametrized in terms of the tensor-to-scalar ratio, r , and the tensor spectral index, n {sub t} . If the inflation consistency relation is imposed, r =−8 n {sub t} , we obtain a strong evidence in favor of the reference model whereas if such relation is relaxed, a weak evidence in favor of the model with diffeomorphism breaking is found. We also use the same CMB data set to make an observational comparison between the SDB model, standard inflation and String Gas Cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

Heat Flow and Magnetization in the Oceanic Lithosphere

Two aspects of the processing and interpretation of satellite measurements of the geomagnetic field are described. One deals with the extraction of the part of the geomagnetic field that originates from sources in the earth's atmosphere. The other investigates the possibility of using the thermal state of the oceanic lithosphere to further constrain modelling and interpretation of magnetic anomalies. It is shown that some of the magnetic signal in crustal anomaly maps can be an artifact of the mathematical algorithms that have been used to separate the crustal field from the observed data. Strong magnetic anomalies can be distorted but are probably real, but weak magnetic anomalies can arise from leakage of power from short wavelengths, and will also appear in anomaly maps as repetitions of the strong crustal anomaly. The distortion and the ghost anomalies follow the magnetic dip lines in a way that is similar to actual MAGSAT anomaly fields. This phenomenon will also affect the lower degree spherical harmonic terms in the power spectrum of the crustal field. A model of the magnetic properties of the oceanic crust that has been derived from direct measurements of the rock magnetic properties of oceanic rocks is presented. The average intensity of magnetization in the oceanic crust is not strong enough to explain magnetic anomalies observed over oceanic areas. This is the case for both near surface observations (ship and aeromagnetic data) and satellite altitude observations. It is shown that magnetic sources in the part of the upper mantle that is situated above the Curie isotherm, if sufficiently strong, can produce satellite magnetic anomalies that are comparable to MAGSAT data. The method developed for the study of depth to the Curie isotherm and magnetic anomalies can also be used in inverse modelling of satellite magnetic anomalies when the model is to be adjusted with an annihilator.

Hayling, Kjell Lennart↗

Regional-scale flows in mountainous terrain. Part 1: A numerical and observational comparison

This study uses observed data and a numerical simulation to examine the generation of thermally driven flows across the Colorado mountain barrier on meso-beta to meso-alpha scales. The observations were collected from remote surface observing systems at exposed mountaintop locations throughout the state of Colorado, over the summers of 1984-88, as part of the Rocky Mountain Peaks Experiment (ROMPEX). The data show the development of a recurrent circulation system across the Colorado mountain barrier, operating on a diurnal timescale. From the observations, the basic structure of the flow system appears as a daytime inflow toward the highest terrain, and a nocturnal outflow away from it. However, when examined in detail, the flow system exhibits more unusual behavior, especially west of the barrier crest. Here, winds in the early evening are occasionally observed to onset abruptly from an easterly direction, generally counter to the upper-level winds. Observations from ROMPEX for 26 August 1985 are used to provide comparison data for a numerical simulation with the Regional Atmospheric Modeling System (RAMS). This three-dimensional case study experiment is initialized with data from the National Meteorological Center and incorporates two-way interactive grid nesting. From the observed data and case study simulation, four distinct phases of the regional-scale circulation system have been identified. In the development phase, a deep mountain-plains solenoid is generated through terrain heating along the Front Range. This circulation system transforms in the late afternoon transition phase into a westward-propagating density current (WPDC). The third phase, called the 'density-current propagation phase,' occurs as the WPDC moves westward across the mountains, leaving in its wake strong southeasterly flow at the mountaintop level. This current appears to be the cause of the peculiar easterly component winds found in the ROMPEX mountaintop observations along the western slope. In the final late-night adjustment phase, the WPDC dissipates near the western edge of the Colorado mountains and steady southerly flow evolves over the high mountain terrain. This southerly flow is the steady response to the differential heating that develops between the low-lying plains and the intermountain region.

Bossert, James E.↗

Observations and Laboratory Data of Planetary Organics

Many efforts are underway to search for evidence of prebiotic materials in the outer solar system. Current and planned Mars missions obtain remote sensing observations that can be used to address the potential presence of prebiotic materials. Additional missions to, and continuing earth-based observations of, more distant solar system objects will also provide remote sensing observations that can be used to address the potential presence of prebiotic materials. I will present an overview of on-going observations, associated laboratory investigations of candidate materials, and theoretical modeling of observational data. In the past the room temperature reflectance spectra of many residues created from HC-bearing gases and solids have been reported. The results of an investigation of what effect temperatures more representative of outer solar system surfaces (50-140K) have on the reflectance spectra of these residues, and the associated interpretations, will be presented. The relatively organic-rich Tagish Lake Meteorite has been suggested as a spectral analog for Dtype asteroids. Using a new approach that relies upon iterative use of Hapke theory and Kraniers-Kronig analysis the optical constants of TLM were estimated. The approach and results of the analysis will be presented. Use of optical constants in scattering theories, such as the Hapke theory, provide the ability to determine quantitative estimates of the relative abundances and grain sizes of candidate surface components. This approach has been applied to interpret the reflectance spectra of several outer solar system surfaces. A summary will be provided describing the results of such modeling efforts.

Roush, Ted L.↗

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗

Earth observing system. Output data products and input requirements, version 2.0. Volume 1: Instrument data product characteristics

Information on Earth Observing System (EOS) output data products and input data requirements that has been compiled by the Science Processing Support Office (SPSO) at GSFC is presented. Since Version 1.0 of the SPSO Report was released in August 1991, there have been significant changes in the EOS program. In anticipation of a likely budget cut for the EOS Project, NASA HQ restructured the EOS program. An initial program consisting of two large platforms was replaced by plans for multiple, smaller platforms, and some EOS instruments were either deselected or descoped. Updated payload information reflecting the restructured EOS program superseding the August 1991 version of the SPSO report is included. This report has been expanded to cover information on non-EOS data products, and consists of three volumes (Volumes 1, 2, and 3). Volume 1 provides information on instrument outputs and input requirements. Volume 2 is devoted to Interdisciplinary Science (IDS) outputs and input requirements, including the 'best' and 'alternative' match analysis. Volume 3 provides information about retrieval algorithms, non-EOS input requirements of instrument teams and IDS investigators, and availability of non-EOS data products at seven primary Distributed Active Archive Centers (DAAC's).

Lu, Yun-Chi↗

Integrating Earth Observations and Socioeconomic Data to Identify Vulnerable Populations and Support Environmental Justice Initiatives

Part of NASA’s Earth Applied Sciences, DEVELOP is a dual capacity building program that introduces communities to applications of NASA Earth observation data to help inform environmental decision making. These projects are conducted by small teams of students, recent graduates, and early and transitioning career professionals and are tailored specifically to end-user decision making processes. Since 2018, a collaboration between NASA DEVELOP, Groundwork USA and its network of trusts, the AGU Thriving Earth Exchange, and local communities such as the City of Cambridge and the City of San Diego, has culminated in a campaign of 14 projects focused on assessing vulnerability to environmental threats such as extreme heat and flooding. These projects have explored the integration of satellite data and socio-economic data to discern populations at risk of being negatively impacted and align with Groundwork’s Climate Safe Neighborhoods Initiative that explores the relationship between historical race-based housing segregation and current and predicted impacts of climate change. This presentation will introduce an overview of the DEVELOP projects using Earth observations to support vulnerabilities assessments and community resilience, the collaboration with Groundwork USA, and future plans for environmental justice efforts at NASA.

Capacity Building↗

Missing data in multi-omics integration: Recent advances through artificial intelligence

Biological systems function through complex interactions between various ‘omics (biomolecules), and a more complete understanding of these systems is only possible through an integrated, multi-omic perspective. This has presented the need for the development of integration approaches that are able to capture the complex, often non-linear, interactions that define these biological systems and are adapted to the challenges of combining the heterogenous data across ‘omic views. A principal challenge to multi-omic integration is missing data because all biomolecules are not measured in all samples. Due to either cost, instrument sensitivity, or other experimental factors, data for a biological sample may be missing for one or more ‘omic techologies. Recent methodological developments in artificial intelligence and statistical learning have greatly facilitated the analyses of multi-omics data, however many of these techniques assume access to completely observed data. A subset of these methods incorporate mechanisms for handling partially observed samples, and these methods are the focus of this review. We describe recently developed approaches, noting their primary use cases and highlighting each method's approach to handling missing data. We additionally provide an overview of the more traditional missing data workflows and their limitations; and we discuss potential avenues for further developments as well as how the missing data issue and its current solutions may generalize beyond the multi-omics context.

97 MATHEMATICS AND COMPUTING↗

The Main Pillar: Assessment of Space Weather Observational Asset Performance Supporting Nowcasting, Forecasting and Research to Operations

Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations.

Extreme events↗

Barotropic stability of realistic stratospheric jets

The stability of realistic jets is examined in a linearized barotropic model on a sphere. Approximately non-dispersive modes associated with a region of negative basic state absolute vorticity gradient on the poleward side of the jet are examined in detail. As in previous studies, broader jets and those which peak at higher latitudes produce poleward modes that are less dispersive. Jet profiles derived from observational data at 10, 5, and 2 mb for three Southern Hemisphere winter months are used in the model, and the results are compared with quasi-nondispersive features (QNDF) which have been observed in satellite data in the Southern Hemisphere winter stratosphere. Characteristics of the barotropically unstable modes compare remarkably well with those of the observed modes. The barotropic model results for a month in which these features are not observed indicate the presence of equatorward modes at wavenumbers 3 and 4 which grow considerably faster than the quasi-nondispersive poleward modes. The appearance of westward moving modes in the summer hemisphere during June and in analytical profiles with a realistic global structure is also noted.

Manney, Gloria L.↗

Multilevel Algorithm for Atmospheric Data Assimilation

A multiscale algorithm for the problem of optimal statistical interpolation of observed data has been developed. This problem includes the calculation of the vector of the 'analyzed' (best estimated) atmosphere flow field w(sup a) by the formula: w(sup a) = w(sup f) + P(sup f) H(sup T) y, where the quantity y is defined by the equation (H P(sup f) H(sup T) + R)y = w(sup o) - H w(sup f), using the given model forecast first guess w(sup f) and the vector of observations w(sup o); H is an interpolation operator from the regular grid to the observation network, P(sup f) is the forecast error covariance matrix, and R is the observation error covariance matrix. At this initial stage the case of univariate analysis of single level radiosonde height data is considered. The matrix R is assumed to be diagonal, and the matrix P(sup f) is assumed to be given by the formula P(sub ij)(sup f) = sigma(sub i)(sup f) mu(sub ij) sigma(sub j)(sub f), where mu(sub ij) is a smooth, decreasing function of the distance between the i-th and the j-th points. In this paper we describe a multiscale iterative process based on a multiresolution, simultaneous displacement technique and a localized variational calculation of iteration parameters.

Brandt, Achi↗

OSIRIS-REx, bringing back a bit of an asteroid

The OSIRIS-REx mission will provide invaluable ground-truth validation for the computer models in a case study that set out to determine the timeframe within which we must launch either a kinetic impactor or a nuclear explosive carrier and develop a conceptual design for that spacecraft. From the on-asteroid data gathered when the spacecraft touches down and, eventually, from hands-on research here on Earth, we will get a reality check for what we think we know about Bennu’s material composition (boulders, chunks, and dust), shape, mass, density, and so on. Gravimetric data could reveal whether the asteroid is hollow. Back on Earth, researchers will run various tests on the material. We may have enough information to develop a theoretical equation of state. We could then compare it to its closest match in SESAME, the Los Alamos database of equations of state. Armed with that data, we will rerun the models to see how much each scenario changes. Comparing data from the touchdown and sample return to the earlier, remotely observed data from Bennu will help us calibrate remote observations of other objects in the future. Then we can more precisely model the effects of our deflection and disruption strategies and refine the spacecraft design.

97 MATHEMATICS AND COMPUTING↗

The puzzling chemical composition of GJ 436B'S atmosphere: Influence of tidal heating on the chemistry

The dissipation of the tidal energy deposited on eccentric planets may induce a heating of the planet that affects its atmospheric thermal structure. Here we study the influence of tidal heating on the atmospheric composition of the eccentric (e = 0.16) 'hot Neptune' GJ 436b, for which inconclusive chemical abundances are retrieved from multiwavelength photometric observations carried out during primary transit and secondary eclipse. We build up a one-dimensional model of GJ 436b's atmosphere in the vertical direction and compute the pressure-temperature and molecular abundances profiles for various plausible internal temperatures of the planet (up to 560 K) and metallicities (from solar to 100 times solar), using a radiative-convective model and a chemical model which includes thermochemical kinetics, vertical mixing, and photochemistry. We find that the CO/CH{sub 4} abundance ratio increases with metallicity and tidal heating, and ranges from 1/20 to 1000 within the ranges of metallicity and internal temperature explored. Water vapor locks most of the oxygen and reaches a very high abundance, whatever the metallicity and internal temperature of the planet. The CO{sub 2}/H{sub 2}O abundance ratio increases dramatically with metallicity, and takes values between 10{sup –5}-10{sup –4} with solar elemental abundances and ∼0.1 for a metallicity 100 times solar. None of the atmospheric models based on solid physical and chemical grounds provide a fully satisfactory agreement with available observational data, although the comparison of calculated spectra and observations seems to point to models with a high metallicity and efficient tidal heating, in which high CO/CH{sub 4} abundance ratios and warm temperatures in the dayside atmosphere are favored.

79 ASTRONOMY AND ASTROPHYSICS↗

A Graphical Model for Fusing Diverse Microbiome Data

This paper develops a Bayesian graphical model for fusing disparate types of count data. The motivating application is the study of bacterial communities from diverse high-dimensional features, in this case, transcripts, collected from different treatments. In such datasets, there are no explicit correspondences between the communities and each corresponds to different factors, making data fusion challenging. We introduce a flexible multinomial-Gaussian generative model for jointly modeling such count data. This latent variable model jointly characterizes the observed data through a common multivariate Gaussian latent space that parameterizes the set of multinomial probabilities of the transcriptome counts. The covariance matrix of the latent variables induces a covariance matrix of co-dependencies between all the transcripts, effectively fusing multiple data sources. We present a computationally scalable variational Expectation-Maximization (EM) algorithm for inferring the latent variables and the parameters of the model. Here, the inferred latent variables provide a common dimensionality reduction for visualizing the data and the inferred parameters provide a predictive posterior distribution. In addition to simulation studies that demonstrate the variational EM procedure, we apply our model to a bacterial microbiome dataset.

59 BASIC BIOLOGICAL SCIENCES↗

A framework for inferring and analyzing pharmacotherapy treatment patterns

Background: To discover pharmacotherapy prescription patterns and their statistical associations with outcomes through a clinical pathway inference framework applied to real-world data. Methods: We apply machine learning steps in our framework using a 2006 to 2020 cohort of veterans with major depressive disorder (MDD). Outpatient antidepressant pharmacy fills, dispensed inpatient antidepressant medications, emergency department visits, self-harm, and all-cause mortality data were extracted from the Department of Veterans Affairs Corporate Data Warehouse. Results: Our MDD cohort consisted of 252,179 individuals. During the study period there were 98,417 emergency department visits, 1,016 cases of self-harm, and 1,507 deaths from all causes. The top ten prescription patterns accounted for 69.3% of the data for individuals starting antidepressants at the fluoxetine equivalent of 20-39 mg. Additionally, we found associations between outcomes and dosage change. Conclusions: For 252,179 Veterans who served in Iraq and Afghanistan with subsequent MDD noted in their electronic medical records, we documented and described the major pharmacotherapy prescription patterns implemented by Veterans Health Administration providers. Ten patterns accounted for almost 70% of the data. Associations between antidepressant usage and outcomes in observational data may be confounded. The low numbers of adverse events, especially those associated with all-cause mortality, make our calculations imprecise. Furthermore, our outcomes are also indications for both disease and treatment. Despite these limitations, we demonstrate the usefulness of our framework in providing operational insight into clinical practice, and our results underscore the need for increased monitoring during critical points of treatment.

60 APPLIED LIFE SCIENCES↗

Stability Functions in the Stable Surface Layer Derived from the Mellor–Yamada–Nakanishi–Niino (MYNN) Scheme

It is desirable that a surface layer scheme in an atmospheric numerical model is consistent with an atmospheric boundary layer scheme incorporated in the same model. In this study, stability functions based on Monin–Obukhov similarity theory for momentum and heat, φ m and φ h , in the stable surface layer are derived from the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme. The resulting stability functions are approximated by φ m = 1 + 4.8z/L and φ h = 0.74 + 6.0z/L, which can be analytically integrated with respect to height z to obtain momentum and heat fluxes, where L is the Obukhov length. The fluxes thus, obtained are compared with those acquired from stability functions in four previous studies: they are nearly the same as those from two of them, and show better agreement with observational data of the Surface Heat Budget of the Arctic Ocean experiment (SHEBA) over sea ice than those from the other two studies. Detailed comparisons of the results of the MYNN scheme with the SHEBA data suggest that significant variations of the fluxes observed during “winter” when the ice was covered with dry snow may have been caused by those of the surface roughness around the observational site. The stability functions obtained from the MYNN scheme predict that the bulk and flux Richardson numbers approach critical values of 0.26 and 0.21, respectively, in the limit of z/L → ∞. These critical values result from the Kolmogorov hypothesis applied to the turbulent dissipation in the MYNN scheme and are considered to correspond to a transition from Kolmogorov to non-Kolmogorov turbulence.

54 ENVIRONMENTAL SCIENCES↗

An eddy-permitting ocean-sea ice general circulation model (E3SMv0-HiLAT03): Description and evaluation

We document modeling setups and present results for simulated ocean and sea ice climate from a recently developed, intermediate-resolution global ocean-sea ice model [Energy Exascale Earth System Model version 0 configured for High-Latitude Application and Testing at 0.3° resolution (E3SMv0-HiLAT03)]. The horizontal resolution of HiLAT03 ranges from 33 km in the tropics to 8.5 km at high latitudes, with 100 vertical levels. This resolution allows the explicit representation of some mesoscale eddies, particularly at lower latitudes, therefore being named as an “eddy-permitting model”. Analyses are presented based on the output of two 186-yr control simulations forced by modern atmospheric conditions of climatological and inter-annually varying data sets, respectively. Results are compared to available observational data sets and the 1° NCAR model, which has somewhat similar ocean physics but a coarser resolution and an earlier version of the sea ice component. Analyses focus on ocean temperature and salinity fields, ocean dynamics and circulations, sea ice concentrations and thicknesses. The HiLAT03 model does reasonably well in most oceanic aspects evaluated here, especially in ocean meridional heat transport, despite the fact that no explicit eddy parameterization is applied. Many Arctic sea ice features are much improved compared with the 1° NCAR model, but the Antarctic summer sea ice is still generally low in concentrations and thicknesses. In addition, we discuss the prolonged deep convection (“Antarctic prolonged polynya”) over the Southern Ocean in the inter-annually forced case.

54 ENVIRONMENTAL SCIENCES↗

Infrared measurements of stratospheric composition

The observational techniques and results of IR measurements of the minor and trace molecular composition of the lower stratosphere are reviewed. Emphasis is given to those theoretical aspects of the formation of emission and absorption spectra which affect the quantitative interpretation of observational data in terms of the vertical distribution of observed molecular species. The principal experimental techniques currently being used are briefly reviewed, followed by a detailed summary of current knowledge of the abundances and spatial variability of the known minor constituents. The question of the determination of the minimum detectable concentration of a constituent molecule and its relationship to the instrumental parameters, the molecular transition intensities, and observation geometry is discussed; upper limit concentrations are given for some additional species of importance in current stratospheric studies.

Farmer, C. B.↗