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NASA NTRS2005

Java Radar Analysis Tool

Java Radar Analysis Tool (JRAT) is a computer program for analyzing two-dimensional (2D) scatter plots derived from radar returns showing pieces of the disintegrating Space Shuttle Columbia. JRAT can also be applied to similar plots representing radar returns showing aviation accidents, and to scatter plots in general. The 2D scatter plots include overhead map views and side altitude views. The superposition of points in these views makes searching difficult. JRAT enables three-dimensional (3D) viewing: by use of a mouse and keyboard, the user can rotate to any desired viewing angle. The 3D view can include overlaid trajectories and search footprints to enhance situational awareness in searching for pieces. JRAT also enables playback: time-tagged radar-return data can be displayed in time order and an animated 3D model can be moved through the scene to show the locations of the Columbia (or other vehicle) at the times of the corresponding radar events. The combination of overlays and playback enables the user to correlate a radar return with a position of the vehicle to determine whether the return is valid. JRAT can optionally filter single radar returns, enabling the user to selectively hide or highlight a desired radar return.

Zaczek, Mariusz P.↗

NASA NTRS2013

A Storm Surge and Inundation Model of the Back River Watershed at NASA Langley Research Center

This report on a Virginia Institute for Marine Science project demonstrates that the sub-grid modeling technology (now as part of Chesapeake Bay Inundation Prediction System, CIPS) can incorporate high-resolution Lidar measurements provided by NASA Langley Research Center into the sub-grid model framework to resolve detailed topographic features for use as a hydrological transport model for run-off simulations within NASA Langley and Langley Air Force Base. The rainfall over land accumulates in the ditches/channels resolved via the model sub-grid was tested to simulate the run-off induced by heavy precipitation. Possessing both the capabilities for storm surge and run-off simulations, the CIPS model was then applied to simulate real storm events starting with Hurricane Isabel in 2003. It will be shown that the model can generate highly accurate on-land inundation maps as demonstrated by excellent comparison of the Langley tidal gauge time series data (CAPABLE.larc.nasa.gov) and spatial patterns of real storm wrack line measurements with the model results simulated during Hurricanes Isabel (2003), Irene (2011), and a 2009 Nor'easter. With confidence built upon the model's performance, sea level rise scenarios from the ICCP (International Climate Change Partnership) were also included in the model scenario runs to simulate future inundation cases.

Loftis, Jon Derek↗

NASA NTRS2015

Wind Magnetic Clouds for 2010-2012: Model Parameter Fittings, Associated Shock Waves, and Comparisons to Earlier Periods

We fitted the parameters of magnetic clouds (MCs) as identified in the Wind spacecraft data from early 2010 to the end of 2012 using the model of Lepping, Jones, and Burlaga (J. Geophys. Res. 95, 1195, 1990). The interval contains 48 MCs and 39 magnetic cloud-like (MCL) events. This work is a continuation of MC model fittings of the earlier Wind sets, including those in a recent publication, which covers 2007 to 2009. This period (2010 - 2012) mainly covers the maximum portion of Solar Cycle 24. Between the previous and current interval, we document 5.7 years of MCs observations. For this interval, the occurrence frequency of MCs markedly increased in the last third of the time. In addition, over approximately the last six years, the MC type (i.e. the profile of the magnetic-field direction within an MC, such as North-to-South, South-to-North, all South) dramatically evolved to mainly North-to-South types when compared to earlier years. Furthermore, this evolution of MC type is consistent with global solar magnetic-field changes predicted by Bothmer and Rust (Coronal Mass Ejections, 139, 1997). Model fit parameters for the MCs are listed for 2010 - 2012. For the 5.7 year interval, the observed MCs are found to be slower, weaker in estimated axial magnetic-field intensity, and shorter in duration than those of the earlier 12.3 years, yielding much lower axial magnetic-field fluxes. For about the first half of this 5.7 year period, i.e. up to the end of 2009, there were very few associated MC-driven shock waves (distinctly fewer than the long-term average of about 50 % of MCs). But since 2010, such driven shocks have increased markedly, reflecting similar statistics as the long-term averages. We estimate that 56 % of the total observed MCs have upstream shocks when the full interval of 1995 - 2012 is considered. However, only 28 % of the total number of MCLs have driven shocks over the same period. Some interplanetary shocks during the 2010 - 2012 interval are seen to apparently occur without an obvious MC-driver, probably indicating an encounter with a distant flank of a MC-driven shock. Some of these may be driven by a different kind of structure, however.

Magnetic clouds↗

NASA NTRS2019

North American Extreme Precipitation Events and Related Large-Scale Meteorological Patterns: a Review of Statistical Methods, Dynamics, Modeling, and Trends

This paper surveys the current state of knowledge regarding Large-Scale Meteorological Patterns (LSMPs) associated with short-duration (less than one week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some 4 promising analysis techniques have been identified and the LSMP perspective is useful for evaluating model dynamics.

Mathew Barlow↗

NASA NTRS2013

TPSAS-NF1676L-17243-DND

This presentation captures ERA Project's effort in using integrated cost-schedule-risk analysis tool, identifying and capturing explicit relationships between program funds, schedule, and discrete risks. The project team merged a myriad of cost and schedule data for timely, objective, uncertainty analysis of the ITD's budget and schedule. The project team conducted detailed schedule uncertainty analysis showing schedule activities and how their interrelationships were impacted, representing an impressive advance beyond routine Gantt charts. Furthermore, the ERA Project collected discrete risk events including their impacts to costs and/or schedule and interwove these risks into cost and schedule logic networks, providing the foundation to conduct cost and schedule analyses. The team integrated this data into the analysis model, providing probabilistic results that were then used by the ERA Project's senior management for decision-making purposes. The ERA Project management team, through technical and pathfinder expertise in integrating cost, schedule, risk, and technical content, consistently provided risk-informed recommendations to Implementing Centers and ISRP senior management which ultimately ensured the successful ARMD Key Decision Point (KDP) review of the ERA Phase 2 ITD Portfolio and increased the likelihood of achieving technical objectives within cost and schedule constraints.

Gaudy M Bezos-O'Connor↗

NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗

NASA NTRS2023

Primordial or Secondary? Testing Models of Debris Disk Gas with ALMA

The origin and evolution of gas in debris disks are still not well understood. Secondary gas production from cometary material or a primordial origin have been proposed. So far, observations have mostly concentrated on CO, with only a few C observations available. We overview the C and CO content of debris disk gas and test the state of the-art models. We use new and archival Atacama Large Millimeter/submillimeter Array (ALMA) observations of CO and C I emission, complemented by C II data from Herschel, for a sample of 14 debris disks. This expands the number of disks with ALMA measurements of both CO and C I by 10 disks. We present new detections of C I emission toward three disks: HD 21997, HD 121191, and HD 121617. We use a simple disk model to derive gas masses and column densities. We find that current state-of-the-art models of secondary gas production overpredict the C 0 content of debris disk gas. This does not rule out a secondary origin, but might indicate that the models require an additional C removal process. Alternatively, the gas might be produced in transient events rather than a steady-state collisional cascade. We also test a primordial gas origin by comparing our results to a simplified thermochemical model. This yields promising results, but more detailed work is required before a conclusion can be reached. Our work demonstrates that the combination of C and CO data is a powerful tool to advance our understanding of debris disk gas.

Radiative transfer↗

NASA NTRS2014

Modeling the Deterioration of Engine and Low Pressure Compressor Performance During a Roll Back Event Due to Ice Accretion

The main focus of this study is to apply a computational tool for the flow analysis of the engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. A data point was selected for analysis during which the engine experienced a full roll back event due to the ice accretion on the blades and flow path of the low pressure compressor. The computational tool consists of the Numerical Propulsion System Simulation (NPSS) engine system thermodynamic cycle code, and an Euler-based compressor flow analysis code, that has an ice particle melt estimation code with the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Decreasing the performance characteristics of the low pressure compressor (LPC) within the NPSS cycle analysis resulted in matching the overall engine performance parameters measured during testing at data points in short time intervals through the progression of the roll back event. Detailed analysis of the fan-core and LPC with the compressor flow analysis code simulated the effects of ice accretion by increasing the aerodynamic blockage and pressure losses through the low pressure compressor until achieving a match with the NPSS cycle analysis results, at each scan. With the additional blockages and losses in the LPC, the compressor flow analysis code results were able to numerically reproduce the performance that was determined by the NPSS cycle analysis, which was in agreement with the PSL engine test data. The compressor flow analysis indicated that the blockage due to ice accretion in the LPC exit guide vane stators caused the exit guide vane (EGV) to be nearly choked, significantly reducing the air flow rate into the core. This caused the LPC to eventually be in stall due to increasing levels of diffusion in the rotors and high incidence angles in the inlet guide vane (IGV) and EGV stators. The flow analysis indicating compressor stall is substantiated by the video images of the IGV taken during the PSL test, which showed water on the surface of the IGV flowing upstream out of the engine, indicating flow reversal, which is characteristic of a stalled compressor.

Veres, Joseph P.↗

NASA NTRS2014

Modeling the Deterioration of Engine and Low Pressure Compressor Performance During a Roll Back Event Due to Ice Accretion

Jorgenson, Philip C. E.↗

NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗

NASA NTRS1997

A Model for Lower Hybrid Wave Excitation Compared with Observations by Viking

The mechanism of lower hybrid wave (LHW) excitation due to the O+ relative drift in a plasma subjected to low-frequency waves (LFWs) is used for analysis of Viking satellite data for events in the cusp/cleft region. In some cases, such a mechanism leads to LHW energy densities and ion distribution functions close to those observed, suggesting the proposed mechanism is a plausible candidate to explain certain classes of LHW generation events in space plasmas.

Khazanov, G. V.↗

NASA NTRS2007

Modeling Malaria Transmission in Thailand and Indonesia

Malaria Modeling and Surveillance is a project in the NASA Applied Sciences Public Health Applications Program. The main objectives of this project are: 1) identification of the potential breeding sites for major vector species: 2) implementation of a malaria transmission model to identify they key factors that sustain or intensify malaria transmission; and 3) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity. Remote sensing and GIs are the essential elements of this project. The NASA Earth science data sets used in this project include AVHRR Pathfinder, TRMM, MODIS, NSIPP and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of precipitation, temperatures, humidity and vegetation. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Examples for spatio-temporal modeling of malaria transmissions in Southeast Asia are given. Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to Southeast Asia. The model and techniques are equally applicable to other regions of the world, when appropriate epidemiological and vector ecological parameters are used as input.

Kiang, Richard↗

NASA NTRS1993

Scientific goals of the Cooperative Multiscale Experiment (CME)

Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.

Cotton, William↗

NASA NTRS2015

High-Energy Electromagnetic Offline Follow-Up of Ligo-Virgo Gravitational-Wave Binary Coalescence Candidate Events

We present two different search methods for electromagnetic counterparts to gravitational-wave (GW) events from ground-based detectors using archival NASA high-energy data from the Fermi Gamma-ray Burst Monitor (GBM) and RXTE All-sky Monitor (ASM) instruments. To demonstrate the methods, we use a limited number of representative GW background noise events produced by a search for binary neutron star coalescence over the last two months of the LIGO-Virgo S6/VSR3 joint science run. Time and sky location provided by the GW data trigger a targeted search in the high-energy photon data. We use two custom pipelines: one to search for prompt gamma-ray counterparts in GBM, and the other to search for a variety of X-ray afterglow model signals in ASM. We measure the efficiency of the joint pipelines to weak gamma-ray burst counterparts, and a family of model X-ray afterglows. By requiring a detectable signal in either electromagnetic instrument coincident with a GW event, we are able to reject a large majority of GW candidates. This reduces the signal-to-noise ratio of the loudest surviving GW background event by around 15-20 percent.

gamma-ray burst: general↗

NASA NTRS1983

The Spectral Properties of Gamma-ray Bursts: a Review of Recent Development

Developments in the spectroscopy of gamma ray bursts (GRB) are reviewed. The general question of the validity of the spectral results, particularly with regard to features in the spectrum, is discussed. Confirmations of these spectral features are summarized. Results from the KONUS experiments on Venera 13 and 14 are reviewed. The status of models of the continuum spectrum is summarized. A number of different radiation mechanisms appear capable of fitting the data. These include thermal bremsstrahlung, thermal synchrotron and inverse Compton. Rapid variability of the spectra shape on time scales 76] 0.25 sec. was reported. The characteristic energy of the spectrum was observed to vary over nearly an order of magnitude during individual events. A strong correlation between spectral hardness and luminosity was found. Low-energy (50 keV) absorption features and high-energy (400 keV) emission features continue to appear in GRB spectra. Understanding the origin of these lines in the context of the existing continuum models remains a difficult problem.

Teegarden, B. J.↗

NASA NTRS2008

Using Black Hole Mergers to Explore Structure Formation

Observations of gravitational waves from massive black hole mergers will open a new window into the era of structure formation in the early universe. Past efforts have concentrated on calculating merger rates using different physical assumptions, resulting in merger rate estimates that span a wide range (0.1 - 1 0A4 mergers/year). We develop a semi-analytical, phenomenological model of massive black hole mergers that includes plausible combinations of several physical parameters, which we then turn around to determine how well observations with the Laser Interferometer Space Antenna (LISA) will be able to enhance our understanding of the universe during the critical z approx. 5 - 30 epoch. Our approach involves generating synthetic LISA observable data (total BH masses, BH mass ratios, redshifts, merger rates), which are then analyzed using a Markov Chain Monte Carlo method, thus finding constraints for the physical parameters of the mergers. We find that our method works well at estimating merger parameters and that the number of merger events is a key discriminant among models, therefore making our method robust against observational uncertainties. Our approach can also be extended to more physically-driven models and more general problems in cosmology.

Alicea-Munoz, E.↗

NASA NTRS1975

The auditory neural network in man

The principles of anatomy and physiology necessary for understanding brain wave recordings made from the scalp of normal people are briefly discussed. Brain waves evoked by sounds are described and certain of their features are related to the physical aspects of the stimulus and to the psychological state of the listener. The position is taken that data obtained through scalp probes can reveal a large amount of detail about brain functioning and that analysis of such records enable detection of the response of the nervous system to an acoustic message at the moment of its inception and to the progress of the message through the brain. Brain events responsible for distinguishing between similar signals and making decisions about them appear to generate characteristic and identifiable electrical waves. Some theoretical speculation about these data are introduced with the aim of generating a more heuristic model of the functioning brain.

Galambos, R.↗

NASA NTRS1994

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

The thrust of the proposed effort under this contract is aimed at improving techniques to track water vapor data in sequences of imagery from geostationary satellites. In regards to this task, significant testing, evaluation, and progress was accomplished during this period. Sets of winds derived from Meteosat data were routinely produced during Atlantic hurricane events in the 1993 season. These wind sets were delivered via Internet in real time to the Hurricane Research Division in Miami for their evaluation in a track forecast model. For eighteen cases in which 72-hour forecasts were produced, thirteen resulted in track forecast improvements (some quite significant). In addition, quality-controlled Meteosat water vapor winds produced by NESDIS were validated against rawinsondes, yielding an 8 m/s RMS. This figure is comparable to upper-level cloud drift wind accuracies. Given the complementary horizontal coverage in cloud-free areas, we believe that water vapor vectors can supplement cloud-drift wind information to provide good full-disk coverage of the upper tropospheric flow. The impact of these winds on numerical analysis and forecasts will be tested in the next reporting period.

Velden, Christopher S.↗