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NASA NTRS2005

Multiangle Imaging Spectroradiometer (MISR) Global Aerosol Optical Depth Validation Based on 2 Years of Coincident Aerosol Robotic Network (AERONET) Observations

Performance of the Multiangle Imaging Spectroradiometer (MISR) early postlaunch aerosol optical thickness (AOT) retrieval algorithm is assessed quantitatively over land and ocean by comparison with a 2-year measurement record of globally distributed AERONET Sun photometers. There are sufficient coincident observations to stratify the data set by season and expected aerosol type. In addition to reporting uncertainty envelopes, we identify trends and outliers, and investigate their likely causes, with the aim of refining algorithm performance. Overall, about 2/3 of the MISR-retrieved AOT values fall within [0.05 or 20% x AOT] of Aerosol Robotic Network (AERONET). More than a third are within [0.03 or 10% x AOT]. Correlation coefficients are highest for maritime stations (approx.0.9), and lowest for dusty sites (more than approx.0.7). Retrieved spectral slopes closely match Sun photometer values for Biomass burning and continental aerosol types. Detailed comparisons suggest that adding to the algorithm climatology more absorbing spherical particles, more realistic dust analogs, and a richer selection of multimodal aerosol mixtures would reduce the remaining discrepancies for MISR retrievals over land; in addition, refining instrument low-light-level calibration could reduce or eliminate a small but systematic offset in maritime AOT values. On the basis of cases for which current particle models are representative, a second-generation MISR aerosol retrieval algorithm incorporating these improvements could provide AOT accuracy unprecedented for a spaceborne technique.

global meaurement↗

NASA NTRS2007

Risk Assessment of Bone Fracture During Space Exploration Missions to the Moon and Mars

The possibility of a traumatic bone fracture in space is a concern due to the observed decrease in astronaut bone mineral density (BMD) during spaceflight and because of the physical demands of the mission. The Bone Fracture Risk Module (BFxRM) was developed to quantify the probability of fracture at the femoral neck and lumbar spine during space exploration missions. The BFxRM is scenario-based, providing predictions for specific activities or events during a particular space mission. The key elements of the BFxRM are the mission parameters, the biomechanical loading models, the bone loss and fracture models and the incidence rate of the activity or event. Uncertainties in the model parameters arise due to variations within the population and unknowns associated with the effects of the space environment. Consequently, parameter distributions were used in Monte Carlo simulations to obtain an estimate of fracture probability under real mission scenarios. The model predicts an increase in the probability of fracture as the mission length increases and fracture is more likely in the higher gravitational field of Mars than on the moon. The resulting probability predictions and sensitivity analyses of the BFxRM can be used as an engineering tool for mission operation and resource planning in order to mitigate the risk of bone fracture in space.

Lewandowski, Beth E.↗

NASA NTRS2008

Risk Assessment of Bone Fracture During Space Exploration Missions to the Moon and Mars

Lewandowski, Beth E.↗

NASA NTRS2013

Effects of Tunable Data Compression on Geophysical Products Retrieved from Surface Radar Observations with Applications to Spaceborne Meteorological Radars

This paper presents results and analyses of applying an international space data compression standard to weather radar measurements that can easily span 8 orders of magnitude and typically require a large storage capacity as well as significant bandwidth for transmission. By varying the degree of the data compression, we analyzed the non-linear response of models that relate measured radar reflectivity and/or Doppler spectra to the moments and properties of the particle size distribution characterizing clouds and precipitation. Preliminary results for the meteorologically important phenomena of clouds and light rain indicate that for a 0.5 dB calibration uncertainty, typical for the ground-based pulsed-Doppler 94 GHz (or 3.2 mm, W-band) weather radar used as a proxy for spaceborne radar in this study, a lossless compression ratio of only 1.2 is achievable. However, further analyses of the non-linear response of various models of rainfall rate, liquid water content and median volume diameter show that a lossy data compression ratio exceeding 15 is realizable. The exploratory analyses presented are relevant to future satellite missions, where the transmission bandwidth is premium and storage requirements of vast volumes of data, potentially problematic.

cloud properties↗

NASA NTRS2016

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Gregory, Irene M.↗

NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗

NASA NTRSDate not supplied

Detecting Hail from Space: Algorithms, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global climatologies of severe hail using several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the late 1980’s using the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We developed a passive-microwave algorithm that corresponds tightly to radar reflectivity and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

NASA NTRSDate not supplied

Remote Sensing of Hail from Space: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

NASA NTRSDate not supplied

Spaceborne Remote Sensing of Hail: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

NASA NTRSDate not supplied

Sampling Functions from Gaussian Processes and Structured Covariance Gaussian Networks

When learning aerodynamic models from data, it is critical to incorporate estimates of model uncertainty. This motivates the design of probabilistic aerodynamic databases which can be sampled to generate physically and statistically plausible aerodynamic models. In this talk we discuss how to sample deterministic functions from two different kinds of probabilistic models and demonstrate their use. First, Gaussian Process Regressors (GPRs) are a widely used probabilistic kernel-based model which can be thought of as Gaussian distributions over functions. GPRs are generally trained by maximizing the marginal likelihood of seeing the training data over the kernel parameter space. Sample functions are easily generated by drawing points from the Gaussian distribution at desired input points. However, when the points are not known ahead of time, the classical sampling approach is not possible since successive function samples will generate different function realizations. We present an approach for sampling consistent function evaluations from a GPR over multiple samples. Second, we describe a neural network architecture which learns a conditional Gaussian distribution by maximizing the marginal likelihood at each point in the input space. We then discuss and compare several options for generating sample functions which match this distribution. Finally, we demonstrate the use of these probabilistic aerodynamic models in an atmospheric reentry simulation.

Gaussian process regression↗

NASA NTRS2018

Dynamic Adjustment of Simulation Parameters for Efficient Vehicle Prognostics

Model-based diagnostics and prognostics rely on state estimation and uncertainty management algorithms to produce useful information for system operators and maintainers. This information enables more informed operational decisions, condition-based maintenance, and overall mission safety assurance. Typically, uncertainty is associated with vehicle state-of-health estimation and prediction results because of modeling errors, internal or external sources of noise, and sensor inaccuracy. Probabilistic uncertainty management methods including Sequential Monte Carlo simulation are commonly used to reason about state-of-health estimates and predictions in the presence of these sources of uncertainty. However, such algorithms can be computationally expensive as they require a very large number of samples to obtain a sufficiently accurate quantification of the end of life probability distribution. As a result, highly mobile autonomous systems that leverage the prognostic results for mission-level replanning are often constrained in their processing capability because of these computationally expensive simulation approaches. Therefore, in this paper, we investigate algorithmic methods for dynamically adjusting simulation time step as well as number of samples to achieve highly efficient prognostic results while maintaining results accuracy. Results obtained from simulated flight experiments of an electric unmanned aerial vehicle are presented to verify the efficacy of such algorithms.

Prognostics↗

NASA NTRS1995

EGRET observations of the BL Lacertae objects 0716+714 and 0521-365

During the Compton Observatory's viewing programs Phase 1 (1991 April to 1992 November, also known as the All-Sky Survey) and Phase 2 (1992 November to 1993 September), the BL Lac object 0716+714 was in the field of view of the EGRET telescope a total of six times, three times in Phase 1 and three more times in Phase 2, while the BL Lac object 0521-365 was in the field of view of EGRET only once in Phase 1. The source 0716+714 was detected in high-energy gamma rays by EGRET at a flux level of (2.0 +/- 0.4) x 10(exp -7) photons/sq cm/s for E greater than 100 MeV with a 6 sigma significance when it was first observed by EGRET in 1992 January 10 to 23. The corresponding spectral slope of the photon number distribution is determined to be -2.04 +/- 0.33. The gamma-ray flux of 0716+714 showed considerable time variability in subsequent EGRET observations. But the spectral slope stayed about the same within the statistical uncertainties of the EGRET data. The average spectral slope of the four viewing periods during which the photon flux of 0716+714 stayed above the EGRET detection threshold is found to be -1.85 +/- 0.20 from the combined data. The source 0521+365 was detected by EGRET in 1992 May 14 to June 4 at a flux level of (1.8 +/- 0.5) x 10(exp -7) photons/sq cm/s for E greater than 100 MeV with a 4 sigma significance. The corresponding spectral slope of the photon number distribution is found to be 2.16 +/- 0.36. Details of the observations of these two BL Lac objects with the EGRET telescope are presented.

Lin, Y. C.↗

NASA NTRSDate not supplied

Derivation of Integrated Load Distributions from Resampled Computational Data

Principal component analysis (PCA) has been the center of many surrogate models used to characterize fluid flows in recent years. However, little work has been done to character- ize the uncertainty in the PCA transform itself and its effect on derived surrogate models. To explore the uncertainty, a typical interpolated surrogate model is constructed for a represen- tative aerodynamic body from computational data. The computational data is then resampled to explore the robustness of the PCA transformation. The variations of the model predictions during this resampling are analyzed to get a measure of confidence in the PCA transformation, which is then applied to the interpolated surrogate model to get uncertainty on integrated force predictions. An initial test case has been explored with promising results.

Principal Component Analysis↗

NASA NTRSDate not supplied

Derivation of Integrated Load Distributions from Resampled Computational Data

Computational Fluid Dynamics↗

NASA NTRS1998

Determination of an Infrared Reference Frame

The mission of the European Space Agency's Hipparcos satellite was to provide high precision astrometric and photometric data for over 100,000 stars and somewhat lower precision data on over a million additional stars. These observations were made in the optical band (340 - 850 nm) and resulted in median precisions of better than 1 milli-arcsec (mas) in position and parallax and I mas/yr in proper motion. The Hipparcos frame is inertial within an estimated uncertainty of +/- 0.25 mas/yr. The other important wavelength band for astrometry has been the radio band. A reference frame has been defined based on absolute Very Long Baseline Interferometry (VLBI) positions of several hundreds of radio sources. There have been a number of projects to refine the link between the optical and radio reference frames. In recent years there has been increasing interest in the astrometry of infrared sources. For example, stars with circumstellar shells can be observed in both the optical and radio (e.g. SiO maser emission). The infrared emission from such sources is dominated by thermal dust emission. The spatial distribution of radiation in the three bands is expected to be quite different. In 1982 we proposed a number of infrared-selected sources (S(sub 10 micron) greater than or approx. equal to 100 J(sub y)) for inclusion in the Hipparcos Input Catalog. Most of those sources were observed, and in Sutton (1997) we report the optical astrometric results (position, proper motion, and parallax) for 87 such sources. These sources were selected to have reasonable agreement between infrared and optical positions, and so may be used as primary standards for future infrared astrometry. They are well distributed across the sky, but exhibit some bias towards the galactic plane and the northern hemisphere. We have also obtained a set of 1480 secondary standards (unpublished) A comparison between optical positions and 86 GHz SiO maser positions for 10 sources indicates coincidence at the 0.15 arcsec level, consistent with current uncertainties in the SiO positions. Improved measurements of the SiO maser positions are needed. VLBI data show that SiO maser spots can be distributed in broken rings of radii 10 - 30 mas, presumably centered on the stellar position. However the SiO flux may be distributed asymmetrically, in which case the flux-weighted center of the SiO emission can be different from the stellar position. We have also published a related paper on phase fluctuations in millimeter interferometry (Sutton and Hueckstaedt 1996). Radiometric monitoring of emission from atmospheric water vapor may be a method for correcting for such fluctuations. This is relevant to positional determinations at centimeter and millimeter wavelengths. The integration of visible, infrared, and radio astrometry is one of our principal goals.

Sutton, Edmund C.↗

NASA NTRS2016

Survey of the Frequency Dependent Latitudinal Distribution of the Fast Magnetosonic Wave Mode from Van Allen Probes Electric and Magnetic Field Instrument and Integrated Science Waveform Receiver Plasma Wave Analysis

We present a statistical survey of the latitudinal structure of the fast magnetosonic wave mode detected by the Van Allen Probes spanning the time interval of 21 September 2012 to 1 August 2014. We show that statistically, the latitudinal occurrence of the wave frequency (f) normalized by the local proton cyclotron frequency (f(sub cP)) has a distinct funnel-shaped appearance in latitude about the magnetic equator similar to that found in case studies. By comparing the observed E/B ratios with the model E/B ratio, using the observed plasma density and background magnetic field magnitude as input to the model E/B ratio, we show that this mode is consistent with the extra-ordinary (whistler) mode at wave normal angles (theta(sub k)) near 90 deg. Performing polarization analysis on synthetic waveforms composed from a superposition of extra-ordinary mode plane waves with theta(sub k) randomly chosen between 87 and 90 deg, we show that the uncertainty in the derived wave normal is substantially broadened, with a tail extending down to theta(sub k) of 60 deg, suggesting that another approach is necessary to estimate the true distribution of theta(sub k). We find that the histograms of the synthetically derived ellipticities and theta(sub k) are consistent with the observations of ellipticities and theta(sub k) derived using polarization analysis.We make estimates of the median equatorial theta(sub k) by comparing observed and model ray tracing frequency-dependent probability occurrence with latitude and give preliminary frequency dependent estimates of the equatorial theta(sub k) distribution around noon and 4 R(sub E), with the median of approximately 4 to 7 deg from 90 deg at f/f(sub cP) = 2 and dropping to approximately 0.5 deg from 90 deg at f/f(sub cP) = 30. The occurrence of waves in this mode peaks around noon near the equator at all radial distances, and we find that the overall intensity of these waves increases with AE*, similar to findings of other studies.

Boardsen, Scott A.↗

NASA NTRS1998

Demonstration of a Probabilistic Technique for the Determination of Economic Viability of Very Large Transport Configurations

Over the past few years, modem aircraft design has experienced a paradigm shift from designing for performance to designing for affordability. This report contains a probabilistic approach that will allow traditional deterministic design methods to be extended to account for disciplinary, economic, and technological uncertainty. The probabilistic approach was facilitated by the Fast Probability Integration (FPI) technique; a technique which allows the designer to gather valuable information about the vehicle's behavior in the design space. This technique is efficient for assessing multi-attribute, multi-constraint problems in a more realistic fashion. For implementation purposes, this technique is applied to illustrate how both economic and technological uncertainty associated with a Very Large Transport aircraft concept may be assessed. The assessment is evaluated with the FPI technique to determine the cumulative probability distributions of the design space, as bound by economic objectives and performance constraints. These distributions were compared to established targets for a comparable large capacity aircraft, similar in size to the Boeing 747-400. The conventional baseline configuration design space was determined to be unfeasible and marginally viable, motivating the infusion of advanced technologies, including reductions in drag, specific fuel consumption, wing weight, and Research, Development, Testing, and Evaluation costs. The resulting system design space was qualitatively assessed with technology metric "k" factors. The infusion of technologies shifted the VLT design into regions of feasibility and greater viability. The study also demonstrated a method and relationship by which the impact of new technologies may be assessed in a more system focused approach.

Mavris, Dimitri N.↗

NASA NTRS2001

The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.

Maluf, David A.↗