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NASA NTRS2014

Detecting Trend and Seasonal Changes in Bathymetry Derived from HICO Imagery: A Case Study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallow water inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used. Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than +/-20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as low as 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

coastal marine↗
NASA NTRS2014

Detecting Trend and Seasonal Changes in Bathymetry Derived from HICO Imagery: A Case Study of Shark Bay, Western Australia

The Hyperspectral Imager for the Coastal Ocean (HICO) aboard the International Space Station has offered for the first time a dedicated space-borne hyperspectral sensor specifically designed for remote sensing of the coastal environment. However, several processing steps are required to convert calibrated top-of-atmosphere radiances to the desired geophysical parameter(s). These steps add various amounts of uncertainty that can cumulatively render the geophysical parameter imprecise and potentially unusable if the objective is to analyze trends and/or seasonal variability. This research presented here has focused on: (1) atmospheric correction of HICO imagery; (2) retrieval of bathymetry using an improved implementation of a shallowwater inversion algorithm; (3) propagation of uncertainty due to environmental noise through the bathymetry retrieval process; (4) issues relating to consistent geo-location of HICO imagery necessary for time series analysis, and; (5) tide height corrections of the retrieved bathymetric dataset. The underlying question of whether a temporal change in depth is detectable above uncertainty is also addressed. To this end, nine HICO images spanning November 2011 to August 2012, over the Shark Bay World Heritage Area, Western Australia, were examined. The results presented indicate that precision of the bathymetric retrievals is dependent on the shallow water inversion algorithm used.Within this study, an average of 70% of pixels for the entire HICO-derived bathymetry dataset achieved a relative uncertainty of less than +/-20%. A per-pixel t-test analysis between derived bathymetry images at successive timestamps revealed observable changes in depth to as lowas 0.4 m. However, the present geolocation accuracy of HICO is relatively poor and needs further improvements before extensive time series analysis can be performed.

Geolocations accuracy↗
NASA NTRS2015

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗
NASA NTRS2015

Extension and Statistical Analysis of the GACP Aerosol Optical Thickness Record.

The primary product of the Global Aerosol Climatology Project (GACP) is a continuous record of the aerosol optical thickness (AOT) over the oceans. It is based on channel-1 and -2 radiance data from the Advanced Very High Resolution Radiometer (AVHRR) instruments flown on successive National Oceanic and Atmospheric Administration (NOAA) platforms. We extend the previous GACP dataset by four years through the end of 2009 using NOAA-17 and -18 AVHRR radiances recalibrated against MODerate resolution Imaging Spectroradiometer (MODIS) radiance data, thereby making the GACP record almost three decades long. The temporal overlap of over three years of the new NOAA-17 and the previous NOAA-16 record reveals an excellent agreement of the corresponding global monthly mean AOT values, thereby confirming the robustness of the vicarious radiance calibration used in the original GACP product. The temporal overlap of the NOAA-17 and -18 instruments is used to introduce a small additive adjustment to the channel-2 calibration of the latter resulting in a consistent record with increased data density. The Principal Component Analysis (PCA) of the newly extended GACP record shows that most of the volcanic AOT variability can be isolated into one mode responsible for ~12% of the total variance. This conclusion is confirmed by a combined PCA analysis of the GACP, MODIS, andMulti-angle Imaging SpectroRadiometer (MISR) AOTs during the volcano-free period fromFebruary 2000 to December 2009.We show that the modes responsible for the tropospheric AOT variability in the three datasets agree well in terms of correlation and spatial patterns. A previously identified negative AOT trend which started in the late 1980s and continued into the early 2000s is confirmed. Its magnitude and duration indicate that it was caused by changes in tropospheric aerosols. The latest multi-satellite segment of the GACP record shows that this trend tapered off, with no noticeable AOT change after 2002. This result is consistent with the MODIS andMISR AOT records as well as with the recent gradual reversal frombrightening to dimming revealed by surface flux measurements in many aerosol producing regions. Thus the robustness of the GACP record is confirmed, increasing our confidence in the validity of the negative trend. Although the nominal negative GACP AOT trend could partially be an artifact of increasing aerosol absorption, we argue that the time dependence of the GACP record, including the latest flat period, is more consistent with the actual decrease in the tropospheric AOT.

aerosols↗
NASA NTRS2015

Investigation of Spiral Bevel Gear Condition Indicator Validation via AC-29-2C Combining Test Rig Damage Progression Data with Fielded Rotorcraft Data

This is the final of three reports published on the results of this project. In the first report, results were presented on nineteen tests performed in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig on spiral bevel gear sets designed to simulate helicopter fielded failures. In the second report, fielded helicopter HUMS data from forty helicopters were processed with the same techniques that were applied to spiral bevel rig test data. Twenty of the forty helicopters experienced damage to the spiral bevel gears, while the other twenty helicopters had no known anomalies within the time frame of the datasets. In this report, results from the rig and helicopter data analysis will be compared for differences and similarities in condition indicator (CI) response. Observations and findings using sub-scale rig failure progression tests to validate helicopter gear condition indicators will be presented. In the helicopter, gear health monitoring data was measured when damage occurred and after the gear sets were replaced at two helicopter regimes. For the helicopters or tails, data was taken in the flat pitch ground 101 rotor speed (FPG101) regime. For nine tails, data was also taken at 120 knots true airspeed (120KTA) regime. In the test rig, gear sets were tested until damage initiated and progressed while gear health monitoring data and operational parameters were measured and tooth damage progression documented. For the rig tests, the gear speed was maintained at 3500RPM, a one hour run-in was performed at 4000 in-lb gear torque, than the torque was increased to 8000 in-lbs. The HUMS gear condition indicator data evaluated included Figure of Merit 4 (FM4), Root Mean Square (RMS) or Diagnostic Algorithm 1(DA1), + 3 Sideband Index (SI3) and + 1 Sideband Index (SI1). These were selected based on their sensitivity in detecting contact fatigue damage modes from analytical, experimental and historical helicopter data. For this report, the helicopter dataset was reduced to fourteen tails and the test rig data set was reduced to eight tested gear sets. The damage modes compared were separated into three cases. For case one, both the gear and pinion showed signs of contact fatigue or scuffing damage. For case two, only the pinion showed signs of contact fatigue damage or scuffing. Case three was limited to the gear tests when scuffing occurred immediately after the gear run-in. Results of this investigation highlighted the importance of understanding the complete monitored systems, for both the helicopter and test rig, before interpreting health monitoring data. Further work is required to better define these two systems that include better state awareness of the fielded systems, new sensing technologies, new experimental methods or models that quantify the effect of system design on CI response and new methods for setting thresholds that take into consideration the variance of each system.

spiral bevel gears↗
NASA NTRS2015

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

variability↗
NASA NTRS2015

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗
NASA NTRS2015

Overview of the Airborne Tropical TRopopause EXperiment (ATTREX)

The NASA Airborne Tropical TRopopause EXperiment (ATTREX) is a series of airborne campaigns focused on understanding physical processes in the Tropical Tropopause Layer (TTL) and their role in atmospheric chemistry and climate. ATTREX is using the high-altitude, long-duration NASA Global Hawk Unmanned Air System to make in situ and remote-sensing measurements spanning the Pacific. A particular ATTREX emphasis is to better understand the dehydration of air as it passes through the cold tropical tropopause region. The ATTREX payload contains 12 in situ and remote sensing instruments that measure water vapor, clouds, multiple gaseous tracers (CO, CO2, CH4, NMHC, SF6, CFCs, N2O), reactive chemical compounds (O3, BrO, NO2), meteorological parameters, and radiative fluxes. ATTREX flight series have been conducted in the fall of 2011 from Armstrong Flight Research Center (AFRC) in California, in the winter of 2013 from AFRC, and in the winter/spring of 2014 from Guam. The first two flight series provided extensive sampling of the central and eastern Pacific, whereas the last flight series permitted sampling in the western Pacific. The sampling strategy has primarily involved repeated ascents and descents through the depth of the TTL (about 13-19 km). Over 100 TTL profiles were obtained on each flight series. The ATTREX dataset includes TTL water vapor measurements with unprecedented accuracy, ice crystal size distributions and habits. The cloud and water measurements provide unique information about TTL cloud formation, the persistence of super-saturation with respect to ice, and dehydration. The plethora of tracers measured on the Global Hawk flights are providing unique information about TTL transport pathways and time scales. The meteorological measurements are revealing dynamical phenomena controlling the TTL thermal structure, and the radiation measurements are providing information about heating rates associated with TTL clouds and water vapor. This presentation will provide an overview of the ATTREX flights, examples of measurements from the flights, and plans for modeling/analysis of the ATTREX dataset.

ATTREX↗
NASA NTRS2014

Overview of the Airborne Tropical TRopopause EX

The NASA Airborne Tropical TRopopause EXperiment (ATTREX) is a series of airborne campaigns focused on understanding physical processes in the Tropical Tropopause Layer (TTL) and their role in atmospheric chemistry and climate. ATTREX is using the high-altitude, long-duration NASA Global Hawk Unmanned Air System to make in situ and remote-sensing measurements spanning the Pacific. A particular ATIREX emphasis is to better understand the dehydration of air as it passes through the cold tropical tropopause region. The ATTREX payload contains 12 in situ and remote sensing instruments that measure water vapor, clouds, multiple gaseous tracers (CO, CO2, CH4, NMHC, SF6, CFCs, N2O), reactive chemical compounds (O3, BrO, NO2), meteorological parameters, and radiative fluxes. ATTREX flight series have been conducted in the fall of 2011 from Armstrong Flight Research Center (AFRC) in California, in the winter of 2013 from AFRC, and in the winter/spring of 2014 from Guam. The first two f light series provided extensive sampling of the central and eastern Pacific, whereas the last flight series permitted sampling in the western Pacific. The sampling strategy has primarily involved repeated ascents and descents through the depth of the TTL (about 13-19 km). Over 100 TTL profiles were obtained on each flight series. The ATTREX dataset includes TTL water vapor measurements with unprecedented accuracy, ice crystal size distributions and habits. The cloud and water measurements provide unique information about TTL cloud formation, the persistence of supersaturation with respect to ice, and dehydration. The plethora of tracers measured on the Global Hawk flights are providing unique information about TTL transport pathways and time scales. The meteorological measurements are revealing dynamical phenomena controlling the TTL thermal structure, and the radiation measurements are providing information about heating rates associated with TTL clouds and water vapor. This presentation will provide an overview of the ATTREX flights, examples of measurements from the flights, and plans for modeling/analysis of the ATTREX dataset.

Airborne↗
NASA NTRS2015

High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem

Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.

HRSI↗
NASA NTRS2015

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

Sun-Mack, Sunny↗
NASA NTRS2014

High Spectral Resolution Lidar and MPLNET Micro Pulse Lidar Aerosol Optical Property Retrieval Intercomparison During the 2012 7-SEAS Field Campaign at Singapore

From August 2012 to February 2013 a High Resolution Spectral Lidar (HSRL; 532 nm) was deployed at that National University of Singapore near a NASA Micro Pulse Lidar NETwork (MPLNET; 527 nm) site. A primary objective of the MPLNET lidar project is the production and dissemination of reliable Level 1 measurements and Level 2 retrieval products. This paper characterizes and quantifies error in Level 2 aerosol optical property retrievals conducted through inversion techniques that derive backscattering and extinction coefficients from MPLNET elastic single-wavelength datasets. MPLNET Level 2 retrievals for aerosol optical depth and extinction/backscatter coefficient profiles are compared with corresponding HSRL datasets, for which the instrument collects direct measurements of each using a unique optical configuration that segregates aerosol and cloud backscattered signal from molecular signal. The intercomparison is performed, and error matrices reported, for lower (0-5km) and the upper (>5km) troposphere, respectively, to distinguish uncertainties observed within and above the MPLNET instrument optical overlap regime.

MPL↗
NASA NTRS2016

An Efficient Ray-Tracing Method for Determining Terrain Intercepts in EDL Simulations

The calculation of a ray's intercept from an arbitrary point in space to a prescribed surface is a common task in computer simulations. The arbitrary point often represents an object that is moving according to the simulation, while the prescribed surface is fixed in a defined frame. For detailed simulations, this surface becomes complex, taking the form of real-world objects such as mountains, craters or valleys which require more advanced methods to accurately calculate a ray's intercept location. Incorporation of these complex surfaces has commonly been implemented in graphics systems that utilize highly optimized graphics processing units to analyze such features. This paper proposes a simplified method that does not require computationally intensive graphics solutions, but rather an optimized ray-tracing method for an assumed terrain dataset. This approach was developed for the Mars Science Laboratory mission which landed on the complex terrain of Gale Crater. First, this paper begins with a discussion of the simulation used to implement the model and the applicability of finding surface intercepts with respect to atmosphere modeling, altitude determination, radar modeling, and contact forces influencing vehicle dynamics. Next, the derivation and assumptions of the intercept finding method are presented. Key assumptions are noted making the routines specific to only certain types of surface data sets that are equidistantly spaced in longitude and latitude. The derivation of the method relies on ray-tracing, requiring discussion on the formulation of the ray with respect to the terrain datasets. Further discussion includes techniques for ray initialization in order to optimize the intercept search. Then, the model implementation for various new applications in the simulation are demonstrated. Finally, a validation of the accuracy is presented along with the corresponding data sets used in the validation. A performance summary of the method will be shown using the analysis from the Mars Science Laboratory's terminal descent sensing model. Alternate uses will also be shown for determining horizon maps and orbiter set times.

Shidner, Jeremy D.↗
NASA NTRS2016

Summary of the Results from the Lunar Orbiter Laser Altimeter after Seven Years in Lunar Orbit

In June 2009 the Lunar Reconnaissance Orbiter (LRO) spacecraft was launched to the Moon. The payload consists of 7 science instruments selected to characterize sites for future robotic and human missions. Among them, the Lunar Orbiter Laser Altimeter (LOLA) was designed to obtain altimetry, surface roughness, and reflectance measurements. The primary phase of lunar exploration lasted one year, following a 3-month commissioning phase. On completion of its exploration objectives, the LRO mission transitioned to a science mission. After 7 years in lunar orbit, the LOLA instrument continues to map the lunar surface. The LOLA dataset is one of the foundational datasets acquired by the various LRO instruments. LOLA provided a high-accuracy global geodetic reference frame to which past, present and future lunar observations can be referenced. It also obtained high-resolution and accurate global topography that were used to determine regions in permanent shadow at the lunar poles. LOLA further contributed to the study of polar volatiles through its unique measurement of surface brightness at zero phase, which revealed anomalies in several polar craters that may indicate the presence of water ice. In this paper, we describe the many LOLA accomplishments to date and its contribution to lunar and planetary science.

LRO↗
NASA NTRS2016

Uncertainty Estimates of Psychoacoustic Thresholds Obtained from Group Tests

Adaptive psychoacoustic test methods, in which the next signal level depends on the response to the previous signal, are the most efficient for determining psychoacoustic thresholds of individual subjects. In many tests conducted in the NASA psychoacoustic labs, the goal is to determine thresholds representative of the general population. To do this economically, non-adaptive testing methods are used in which three or four subjects are tested at the same time with predetermined signal levels. This approach requires us to identify techniques for assessing the uncertainty in resulting group-average psychoacoustic thresholds. In this presentation we examine the Delta Method of frequentist statistics, the Generalized Linear Model (GLM), the Nonparametric Bootstrap, a frequentist method, and Markov Chain Monte Carlo Posterior Estimation and a Bayesian approach. Each technique is exercised on a manufactured, theoretical dataset and then on datasets from two psychoacoustics facilities at NASA. The Delta Method is the simplest to implement and accurate for the cases studied. The GLM is found to be the least robust, and the Bootstrap takes the longest to calculate. The Bayesian Posterior Estimate is the most versatile technique examined because it allows the inclusion of prior information.

Rathsam, Jonathan↗
NASA NTRS2016

Graphical Visualization of Human Exploration Capabilities

NASA's pioneering space strategy will require advanced capabilities to expand the boundaries of human exploration on the Journey to Mars (J2M). The Evolvable Mars Campaign (EMC) architecture serves as a framework to identify critical capabilities that need to be developed and tested in order to enable a range of human exploration destinations and missions. Agency-wide System Maturation Teams (SMT) are responsible for the maturation of these critical exploration capabilities and help formulate, guide and resolve performance gaps associated with the EMC-identified capabilities. Systems Capability Organization Reporting Engine boards (SCOREboards) were developed to integrate the SMT data sets into cohesive human exploration capability stories that can be used to promote dialog and communicate NASA's exploration investments. Each SCOREboard provides a graphical visualization of SMT capability development needs that enable exploration missions, and presents a comprehensive overview of data that outlines a roadmap of system maturation needs critical for the J2M. SCOREboards are generated by a computer program that extracts data from a main repository, sorts the data based on a tiered data reduction structure, and then plots the data according to specified user inputs. The ability to sort and plot varying data categories provides the flexibility to present specific SCOREboard capability roadmaps based on customer requests. This paper presents the development of the SCOREboard computer program and shows multiple complementary, yet different datasets through a unified format designed to facilitate comparison between datasets. Example SCOREboard capability roadmaps are presented followed by a discussion of how the roadmaps are used to: 1) communicate capability developments and readiness of systems for future missions, and 2) influence the definition of NASA's human exploration investment portfolio through capability-driven processes. The paper concludes with a description of planned future work to modify the computer program to include additional data and of alternate capability roadmap formats currently under consideration.

Rodgers, Erica M.↗
NASA NTRS2016

Experimental Investigation of Subsonic Turbulent Boundary Layer Flow Over a Wall-Mounted Axisymmetric Hill

An important goal for modern fluid mechanics experiments is to provide datasets which present a challenge for Computational Fluid Dynamics simulations to reproduce. Such "CFD validation experiments" should be well-characterized and well-documented, and should investigate flows which are difficult for CFD to calculate. It is also often convenient for the experiment to be challenging for CFD in some aspects while simple in others. This report is part of the continuing documentation of a series of experiments conducted to characterize the flow around an axisymmetric, modified-cosine-shaped, wall-mounted hill named "FAITH" (Fundamental Aero Investigates The Hill). Computation of this flow is easy in some ways - subsonic flow over a simple shape - while being complex in others - separated flow and boundary layer interactions. The primary set of experiments were performed on a 15.2 cm high, 45.7 cm base diameter machined aluminum model that was tested at mean speeds of 50 m/s (Reynolds Number based on height = 500,000). The ratio of model height to boundary later height was approximately 3. The flow was characterized using surface oil flow visualization, Cobra probe to determine point-wise steady and unsteady 3D velocities, Particle Image Velocimetry (PIV) to determine 3D velocities and turbulence statistics along specified planes, Pressure Sensitive Paint (PSP) to determine mean surface pressures, and Fringe Imaging Skin Friction (FISF) to determine surface skin friction magnitude and direction. A set of pathfinder experiments were also performed in a water channel on a smaller scale (5.1 cm high, 15.2 cm base diameter) sintered nylon model. The water channel test was conducted at a mean test section speed of 3 cm/s (Reynolds Number of 1500), but at the same ratio of model height to boundary layer thickness. Dye injection from both the model and an upstream rake was used to visualize the flow. This report summarizes the experimental set-up, techniques used, and data acquired. It also describes some details of the dataset that is being constructed for use by other researchers, especially the CFD community.

fluid machanics cfd validation wind tunnel↗
NASA NTRS2016

Weather and Climate Change Impacts on Human Mortality in Bangladesh

Weather and climate profoundly affect human health. Several studies have demonstrated a U-, V-, or J-shaped temperature-mortality relationship with increasing death rates at the lower and particularly upper end of the temperature distribution. The objectives of this study were (1) to analyze the relationship between temperature and mortality in Bangladesh for different subpopulations and (2) to project future heat-related mortality under climate change scenarios. We used (non-)parametric Generalized Additive Models adjusted for trend, season and day of the month to analyze the effect of temperature on daily mortality. We found a decrease in mortality with increasing temperature over a wide range of values; between the 90th and 95th percentile an abrupt increase in mortality was observed which was particularly pronounced for the elderly above the age of 65 years, for males, as well as in urban areas and in areas with a high socio-economic status. Daily historical and future temperature values were obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset. This dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5). The derived dose-response functions were used to estimate the number of heat-related deaths occurring during the 1990s (1980-2005), the 2020s (2011-2040) and the 2050s (2041-2070). We estimated that excess deaths due to heat will triple from the 1990s to the 2050s, with an annual number of 0.5 million excess deaths in 1990 to and expected number of 1.5 millions in 2050.

mortality↗