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At least 559 records · Page 31

Effects of Kapton Sample Cell Windows on the Detection Limit of Smectite: Implications for CheMin on the Mars Science Laboratory Mission

The CheMin instrument on the Mars Science Laboratory (MSL) rover Curiosity is an X-ray diffraction (XRD) and X-ray fluorescence (XRF) instrument capable of providing the mineralogical and chemical compositions of rocks and soils on the surface of Mars. CheMin uses a microfocus X-ray tube with a Co target, transmission geometry, and an energy-discriminating X-ray sensitive CCD to produce simultaneous 2-D XRD patterns and energy-dispersive X-ray histograms from powdered samples. CheMin has two different window materials used for sample cells -- Mylar and Kapton. Instrument details are provided elsewhere. Fe/Mg-smectite (e.g., nontronite) has been identified in Gale Crater, the MSL future landing site, by CRISM spectra. While large quantities of phyllosilicate minerals will be easily detected by CheMin, it is important to establish detection limits of such phases to understand capabilities and limitations of the instrument. A previous study indicated that the (001) peak of smectite at 15 Ang was detectable in a mixture of 1 wt.% smectite with olivine when Mylar is the window material for the sample cell. Complications arise when Kapton is the window material because Kapton itself also has a diffraction peak near 15 Ang (6.8 deg 2 Theta). This study presents results of mineral mixtures of smectite and olivine to determine smectite detection limits for Kapton sample cells. Because the intensity and position of the smectite (001) peak depends on the hydration state, we also analyzed mixtures with "hydrated" and "dehydrated"h smectite to examine the effects of hydration state on detection limits.

Achilles, C. N.↗

Precipitation Characteristics of ISCCP Cloud Regimes for Improving Model Hydrological Budgets

The key in unraveling relationships between precipitation and atmospheric circulations is their common linkage to clouds. Clouds can be described in a variety of ways and several approaches can be adopted to examine their connections to precipitation. We claim that when cloud regimes (aka weather states) from the International Satellite Cloud Climatology Project (ISCCP) are used to conditionally sample/sort and average precipitation data, useful insight and GCM-appropriate diagnostics on the origins and distribution of precipitation can be obtained. The ISCCP cloud regimes are mesoscale (2.5 ) cloud mixtures determined by cluster analysis on joint histograms of cloud optical thickness and cloud top pressure inferred from geostationary and polar orbiter satellite passive retrievals. The ISCCP cloud regime data are combined with GPCP IDD merged surface precipitation data and/or higher temporal and spatial resolution TRMM Multi-Satellite Precipitation Analysis (TMPA) data. The analysis is performed separately for three geographical zones, tropics, and northern/southern midlatitudes (for GPCP; only the tropics can be examined with TMPA data). Our presentation aspires to provide answers to the following questions: (l) What is the mean and variability of surface precipitation produced by each cloud regime at the time of regime occurrence? (2) What is the relative contribution of each cloud regime to the total precipitation within its geographical zone? (3) What is the geographical distribution of precipitation corresponding to particular cloud regime? (4) To what extent are the cloud regimes distinct in terms of their precipitation characteristics and is the regime ordering in terms of convective strength consistent with the observed precipitation intensity?

Lee, D.↗

Combined EDL-Mobility Planning for Planetary Missions

This paper presents an analysis framework for planetary missions that have coupled mobility and EDL (Entry-Descent-Landing) systems. Traditional systems engineering approaches to mobility missions such as MERs (Mars Exploration Rovers) and MSL (Mars Science Laboratory) independently study the EDL system and the mobility system, and does not perform explicit trade-off between them or risk minimization of the overall system. A major challenge is that EDL operation is inherently uncertain and its analysis results such as landing footprint are described using PDF (Probability Density Function). The proposed approach first builds a mobility cost-to-go map that encodes the driving cost of any point on the map to a science target location. The cost could include variety of metrics such as traverse distance, time, wheel rotation on soft soil, and closeness to hazards. It then convolves the mobility cost-to-go map with the landing PDF given by the EDL system, which provides a histogram of driving cost, which can be used to evaluate the overall risk of the mission. By capturing the coupling between EDL and mobility explicitly, this analysis framework enables quantitative tradeoff between EDL and mobility system performance, as well as the characterization of risks in a statistical way. The simulation results are presented with a realistic Mars terrain data

mission analysis↗

Thermographic Imaging of the Space Shuttle During Re-Entry Using a Near Infrared Sensor

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiter s hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASA s next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness. Keywords: HYTHIRM, Space Shuttle thermography, hypersonic imaging, near infrared imaging, histogram analysis, singular value decomposition, eigenvalue image sharpness

Zalameda, Joseph N.↗

OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems

Structured grid solvers such as NASA's OVERFLOW compressible Navier-Stokes flow solver can generate large data files that contain convergence histories for flow equation residuals, turbulence model equation residuals, component forces and moments, and component relative motion dynamics variables. Most of today's large-scale problems can extend to hundreds of grids, and over 100 million grid points. However, due to the lack of efficient tools, only a small fraction of information contained in these files is analyzed. OVERSMART (OVERFLOW Solution Monitoring And Reporting Tool) provides a comprehensive report of solution convergence of flow computations over large, complex grid systems. It produces a one-page executive summary of the behavior of flow equation residuals, turbulence model equation residuals, and component forces and moments. Under the automatic option, a matrix of commonly viewed plots such as residual histograms, composite residuals, sub-iteration bar graphs, and component forces and moments is automatically generated. Specific plots required by the user can also be prescribed via a command file or a graphical user interface. Output is directed to the user s computer screen and/or to an html file for archival purposes. The current implementation has been targeted for the OVERFLOW flow solver, which is used to obtain a flow solution on structured overset grids. The OVERSMART framework allows easy extension to other flow solvers.

Kao, David L.↗

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/ WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June July August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.

Teixeira, J.↗

X-Ray Diffraction Reference Intensity Ratios of Amorphous and Poorly Crystalline Phases: Implications for CheMin on the Mars Science Laboratory

The CheMin instrument on the Mars Science Laboratory (MSL) rover Curiosity is an X-ray diffraction (XRD) and X-ray fluorescence (XRF) instrument capable of providing the mineralogical and chemical compositions of rocks and soils on the surface of Mars. CheMin uses a microfocus X-ray tube with a Co target, transmission geometry, and an energy-discriminating X-ray sensitive CCD to produce simultaneous 2-D XRD patterns and energy-dispersive X-ray histograms from powdered samples. Piezoelectric vibration of the cell is used to randomize the sample to reduce preferred orientation effects. Instrument details are provided in [1, 2, 3]. Analyses of rock and soil samples by the Mars Exploration Rovers (MER) show nanophase ferric oxide (npOx) is a significant component of the Martian global soil [4] and is thought to be one of the major contributing phases that the Curiosity rover will encounter if a soil sample is analyzed in Gale Crater. Because of the nature of this material, npOx will likely contribute to an X-ray amorphous or short-order component of a XRD pattern measured by the CheMin instrument.

Morris, R. V.↗

Application of Statistically Derived CPAS Parachute Parameters

The Capsule Parachute Assembly System (CPAS) Analysis Team is responsible for determining parachute inflation parameters and dispersions that are ultimately used in verifying system requirements. A model memo is internally released semi-annually documenting parachute inflation and other key parameters reconstructed from flight test data. Dispersion probability distributions published in previous versions of the model memo were uniform because insufficient data were available for determination of statistical based distributions. Uniform distributions do not accurately represent the expected distributions since extreme parameter values are just as likely to occur as the nominal value. CPAS has taken incremental steps to move away from uniform distributions. Model Memo version 9 (MMv9) made the first use of non-uniform dispersions, but only for the reefing cutter timing, for which a large number of sample was available. In order to maximize the utility of the available flight test data, clusters of parachutes were reconstructed individually starting with Model Memo version 10. This allowed for statistical assessment for steady-state drag area (CDS) and parachute inflation parameters such as the canopy fill distance (n), profile shape exponent (expopen), over-inflation factor (C(sub k)), and ramp-down time (t(sub k)) distributions. Built-in MATLAB distributions were applied to the histograms, and parameters such as scale (sigma) and location (mu) were output. Engineering judgment was used to determine the "best fit" distribution based on the test data. Results include normal, log normal, and uniform (where available data remains insufficient) fits of nominal and failure (loss of parachute and skipped stage) cases for all CPAS parachutes. This paper discusses the uniform methodology that was previously used, the process and result of the statistical assessment, how the dispersions were incorporated into Monte Carlo analyses, and the application of the distributions in trajectory benchmark testing assessments with parachute inflation parameters, drag area, and reefing cutter timing used by CPAS.

Romero, Leah M.↗

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Dominquez, Jesus A.↗

The NASA Fireball Network

In the summer of 2008, the NASA Meteoroid Environments Office (MEO) began to establish a video fireball network, based on the following objectives: (1) determine the speed distribution of cm size meteoroids, (2) determine the major sources of cm size meteoroids (showers/sporadic sources), (3) characterize meteor showers (numbers, magnitudes, trajectories, orbits), (4) determine the size at which showers dominate the meteor flux, (5) discriminate between re-entering space debris and meteors, and 6) locate meteorite falls. In order to achieve the above with the limited resources available to the MEO, it was necessary that the network function almost fully autonomously, with very little required from humans in the areas of upkeep or analysis. With this in mind, the camera design and, most importantly, the ASGARD meteor detection software were adopted from the University of Western Ontario's Southern Ontario Meteor Network (SOMN), as NASA has a cooperative agreement with Western's Meteor Physics Group. 15 cameras have been built, and the network now consists of 8 operational cameras, with at least 4 more slated for deployment in calendar year 2013. The goal is to have 15 systems, distributed in two or more groups east of automatic analysis; every morning, this server also automatically generates an email and a web page (http://fireballs.ndc.nasa.gov) containing an automated analysis of the previous night's events. This analysis provides the following for each meteor: UTC date and time, speed, start and end locations (longitude, latitude, altitude), radiant, shower identification, light curve (meteor absolute magnitude as a function of time), photometric mass, orbital elements, and Tisserand parameter. Radiant/orbital plots and various histograms (number versus speed, time, etc) are also produced. After more than four years of operation, over 5,000 multi-station fireballs have been observed, 3 of which potentially dropped meteorites. A database containing data on all these events, including the videos and calibration information, has been developed and is being modified to include data from the SOMN and other camera networks.

Cooke, William J.↗

Good Practices in Free-energy Calculations

As access to computational resources continues to increase, free-energy calculations have emerged as a powerful tool that can play a predictive role in drug design. Yet, in a number of instances, the reliability of these calculations can be improved significantly if a number of precepts, or good practices are followed. For the most part, the theory upon which these good practices rely has been known for many years, but often overlooked, or simply ignored. In other cases, the theoretical developments are too recent for their potential to be fully grasped and merged into popular platforms for the computation of free-energy differences. The current best practices for carrying out free-energy calculations will be reviewed demonstrating that, at little to no additional cost, free-energy estimates could be markedly improved and bounded by meaningful error estimates. In energy perturbation and nonequilibrium work methods, monitoring the probability distributions that underlie the transformation between the states of interest, performing the calculation bidirectionally, stratifying the reaction pathway and choosing the most appropriate paradigms and algorithms for transforming between states offer significant gains in both accuracy and precision. In thermodynamic integration and probability distribution (histogramming) methods, properly designed adaptive techniques yield nearly uniform sampling of the relevant degrees of freedom and, by doing so, could markedly improve efficiency and accuracy of free energy calculations without incurring any additional computational expense.

Pohorille, Andrew↗

Visual Image Sensor Organ Replacement

This innovation is a system that augments human vision through a technique called "Sensing Super-position" using a Visual Instrument Sensory Organ Replacement (VISOR) device. The VISOR device translates visual and other sensors (i.e., thermal) into sounds to enable very difficult sensing tasks. Three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. Because the human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns, the translation of images into sounds reduces the risk of accidentally filtering out important clues. The VISOR device was developed to augment the current state-of-the-art head-mounted (helmet) display systems. It provides the ability to sense beyond the human visible light range, to increase human sensing resolution, to use wider angle visual perception, and to improve the ability to sense distances. It also allows compensation for movement by the human or changes in the scene being viewed.

Maluf, David A.↗

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

radiative forcing↗

Adventures in Modern Time Series Analysis: From the Sun to the Crab Nebula and Beyond

With the generation of long, precise, and finely sampled time series the Age of Digital Astronomy is uncovering and elucidating energetic dynamical processes throughout the Universe. Fulfilling these opportunities requires data effective analysis techniques rapidly and automatically implementing advanced concepts. The Time Series Explorer, under development in collaboration with Tom Loredo, provides tools ranging from simple but optimal histograms to time and frequency domain analysis for arbitrary data modes with any time sampling. Much of this development owes its existence to Joe Bredekamp and the encouragement he provided over several decades. Sample results for solar chromospheric activity, gamma-ray activity in the Crab Nebula, active galactic nuclei and gamma-ray bursts will be displayed.

solar chromospheric activity↗

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-cloud Aerosols over Ocean Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

CALIOP and MODIS↗

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

CALIOP and MODIS↗

An Examination of the Nature of Global MODIS Cloud Regimes

We introduce global cloud regimes (previously also referred to as "weather states") derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

radiation↗

OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and MODIS Cloud and Radiance Parameters onto the OMI Footprint

Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.

OMMYDCLD↗