Search NASA⌕ Search

SEARCH · Search NASA

Results for “cloud computing, data cloud”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Analysis of Physical Properties of Dust Suspended in the Mars Atmosphere

Methods for iteratively determining the infrared optical constants for dust suspended in the Mars atmosphere are described. High quality spectra for wavenumbers from 200 to 2000 1/cm were obtained over a wide range of view angles by the Mariner 9 spacecraft, when it observed a global Martian dust storm in 1971-2. In this research, theoretical spectra of the emergent intensity from Martian dust clouds are generated using a 2-stream source-function radiative transfer code. The code computes the radiation field in a plane-parallel, vertically homogeneous, multiply scattering atmosphere. Calculated intensity spectra are compared with the actual spacecraft data to iteratively retrieve the optical properties and opacity of the dust, as well as the surface temperature of Mars at the time and location of each measurement. Many different particle size distributions a-re investigated to determine the best fit to the data. The particles are assumed spherical and the temperature profile was obtained from the CO2 band shape. Given a reasonable initial guess for the indices of refraction, the searches converge in a well-behaved fashion, producing a fit with error of less than 1.2 K (rms) to the observed brightness spectra. The particle size distribution corresponding to the best fit was a lognormal distribution with a mean particle radius, r(sub m) 0.66 pm, and variance, omega(sup 2) = 0.412 (r(sub eff) = 1.85 microns, v(sub eff) =.51), in close agreement with the size distribution found to be the best fit in the visible wavelengths in recent studies. The optical properties and the associated single scattering properties are shown to be a significant improvement over those used in existing models by demonstrating the effects of the new properties both on heating rates of the Mars atmosphere and in example spectral retrieval of surface characteristics from emission spectra.

Snook, Kelly↗
NASA NTRS1987

Characteristics of gravity waves generated by surface topography on Venus - Comparison with the VEGA Balloon results

Data from the 1985 VEGA Venus Balloon Mission indicate that the mountainous region known as Aphrodite influences atmospheric motions at balloon float altitudes near 54 km, an altitude located within the middle cloud region. It is shown that stationary gravity waves, generated by surface topography and Doppler-shifted by a wind blowing over the terrain, can propagate upward to the middle cloud layers. Under the right circumstances, waves are amplified considerably in excess of their amplification due to the decrease of density with altitude. The additional amplification is due to resonance that results from variations of static stability and mean zonal wind with altitude. Computed atmospheric propagation characteristics, combined with terrain slopes in Aphrodite estimated from Pioneer Venus radar altimeter data, can be sufficient to produce wind amplitudes at 54 km comparable to those observed by the VEGA-2 balloon as it overflew Aphrodite. The dominant waves have horizontal wavelengths of the order of several hundred kilometers.

Young, Richard E.↗
NASA NTRS2022

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗
NASA NTRS2016

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes.

0↗
NASA NTRSDate not supplied

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗
NASA NTRS2018

Overview of the Digitization Workflow Post Image Acquisition of Apollo Lunar and Antarctic Meteorite Samples Using Agisoft Photoscan for the NASA 3D Astromaterials Virtual Samples Collection

The 3D Virtual Astromaterials Samples (3DVAS) collection is a multi-year funded project to create a digital database of sixty Apollo Lunar and Antarctic Meteorite samples following non-destructive documentation conservation protocols. After initial image processing, the photos are evaluated and processed using unique structure-from-motion photogrammetric techniques in a high performance modelling software designed to create a 3D model from 2D images: Agisoft Photoscan Pro. Agisoft Photoscan Pro uses image processing algorithms and techniques originating in computer vision to resolve 3D models for accurate and detailed visualization of a subject. The software provides a stepwise process that is tailored per model based on spatial and specular reflectance properties, for example. The process includes: photo alignment, creation of a dense point cloud, mesh, and finally texture. Photo alignment is dependent on model properties. The 3DVAS process requires a special rotation platform with calibrated photogrammetric targets, specific distance rotation protocols, and a contrasting background for alignment and scale accuracy. As a result of the photographic process, alignment will complete with two mirrored hemispheres that, in a sense, represent the 2D images overlapping to create a 3D model. Each dense point cloud is analyzed with provided statistical measures in a gradual selection process to eliminate outliers. The point cloud is reduced to include only data valuable to the final model. When a precise dense point cloud is achieved, a mesh and texture are applied. Each model is scaled with scale bar accuracies within 100 microns. Each sample has its own intimate process for modelling; there is no standard for the parameters required in the final creation of a high resolution model. By processing multiple samples, a skill is gained in practice to allow a close definition of the original sample and will result in the most detailed version of the sample shell. This process completes one-fifth of the 3DVAS protocol for providing accurate digital documentation. Each model shell is merged with X-ray Computed Tomography data to create a full volumetric sample. All 3DVAS data will be served on NASA's Astromaterials Acquisition and Curation website with an early subset of data available in 2019 and the 3D Virtual Astromaterials Samples Collection launch in 2020.

Thomas, Andi B.↗
NASA NTRS1980

Application of an automatic cloud tracking technique to Meteosat water vapor and infrared observations

The automatic cloud tracking system was applied to METEOSAT 6.7 micrometers water vapor measurements to learn whether the system can track the motions of water vapor patterns. Data for the midlatitudes, subtropics, and tropics were selected from a sequence of METEOSAT pictures for 25 April 1978. Trackable features in the water vapor patterns were identified using a clustering technique and the features were tracked by two different methods. In flat (low contrast) water vapor fields, the automatic motion computations were not reliable, but in areas where the water vapor fields contained small scale structure (such as in the vicinity of active weather phenomena) the computations were successful. Cloud motions were computed using METEOSAT infrared observations (including tropical convective systems and midlatitude jet stream cirrus).

Endlich, R. M.↗
NASA NTRS1992

Calculations of surface radiation in arid regions - A case study

The surface and satellite data measured during the preliminary field experiment for the Land-Atmosphere Interactions Experiment conducted at the Heihe River basin in western China are used to investigate the difficulties encountered in the derivation of the surface radiation budget in arid regions. The surface radiation is derived by coupling theoretical radiative transfer calculations with satellite cloud retrievals. For cloud-free cases, the modeled downward solar fluxes are systematically larger than the measured fluxes. It is found that the error can be reduced and that good agreement between the computed and measured surface solar fluxes can be obtained by using an aerosol single-scattering albedo of 0.5 and an optical thickness of about 0.2 in the afternoon hours. For all the cases studied when both surface and satellite data are available, the mean errors are 4.3 and -4.7 W/sq m for the net downward surface solar flux and the downward surface IR flux, respectively. The rms errors are 17.4 and 22.1 W/sq m for the respective surface fluxes. The importance of aerosols in surface radiation calculations is underscored.

Chou, Ming-Dah↗
NASA NTRS2016

Evaluation of the Sensitivity of the Amazonian Diurnal Cycle to Convective Intensity in Reanalyses

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics-specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Itterly, Kyle F.↗
NASA NTRSDate not supplied

Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Model

In-flight icing is an important consideration that affects aircraft design, performance and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of ice accretion testing conducted in the NASA Icing Research Tunnel on a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small MVD = 25 μm and a large MVD = 110 μm. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. The results for the small MVD cloud conditions were consistent with previous work and showed the changing ice morphology from rime ice at colder temperatures to highly 3D scallop ice in the range of -8.7 ˚C to -3.8 ˚C. The results for the large MVD cloud conditions exhibited some differences in the ice accretion morphology from the small MVD conditions. Scallop-like ice features were observed at total temperature of -3.8˚C. The large MVD ice accretion at lower temperatures tended to be smoother than the corresponding ice accretion for small MVD. The thickness of the main ice shape tended to be larger for the small MVD conditions compared to the corresponding large MVD ice shape while the latter had more ice farther downstream. The measured ice mass was approximately equal between the corresponding small and large MVD ice shapes up to a freezing fraction of 0.6. For higher freezing fraction, the large MVD ice shapes weighed more. Cloud MVD variation from 50 μm to 230 μm while holding the scaling parameters constant resulted in very minor differences in the ice shapes, mostly in the upper and lower surface chordwise extents. Ice volume was computed from 3D scan data and used to calculate a ratio of ice mass to volume. The resulting values were in the range of 240 to 455 Kg/m3. While this is consistent with analogous values previously reported in the literature, more data are needed to determine a specific trend in this ratio as a function of freezing fraction and the corresponding governing physical phenomena. This work has resulted in a significant experimental database of ice accretion for small and large MVD conditions applicable to large-scale swept wings.

Icing↗
NASA NTRSDate not supplied

Large-Drop Ice Accretion Test Results for a Large Scale Swept Wing Section

In-flight icing is an important consideration that affects aircraft design, performance and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of ice accretion testing conducted in the NASA Icing Research Tunnel on a large swept wing typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small MVD = 25 μm and a large MVD = 110 μm. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. The results for the small MVD cloud conditions were consistent with previous work and showed the changing ice morphology from rime ice at colder temperatures to highly 3D scallop ice in the range of -8.7 ˚C to -3.8 ˚C. The results for the large MVD cloud conditions exhibited some differences in the ice accretion morphology. Scallop-like ice features were observed at total temperature of -3.8˚C. The large MVD ice accretion at lower temperatures tended to be smoother than the corresponding ice accretion for small MVD. The thickness of the main ice shape tended to be larger for the small MVD conditions compared to the corresponding large MVD ice shape while the latter had more ice farther downstream. The measured ice mass was approximately equal between the corresponding small and large MVD ice shapes up to a freezing fraction of 0.6. For higher freezing fraction, the large MVD ice shapes weighed more. Cloud MVD variation from 50 μm to 230 μm while holding the scaling parameters constant resulted in very minor differences in the ice shapes, mostly in the upper and lower surface chordwise extents. Ice volume was computed from 3D scan data and used to calculate a ratio of ice mass to volume. The resulting values were in the range of 240 to 455 Kg/m3. While this is consistent with analogous values previously reported in the literature, more data are needed to determine a specific trend in this ratio as a function of freezing fraction and the corresponding governing physical phenomena. This work has resulted in a significant experimental database of ice accretion for small and large MVD conditions applicable to large-scale swept wings.

Icing↗
NASA NTRS2009

Comparison of Anomalies and Trends of OLR as Observed by CERES and Computed from Geophysical Parameters Derived from Analysis of AIRS/AMSU Data

Anomalies and trends of outgoing longwave radiation (OLR) serve as important indicators of climate change. Several satellite based instruments currently provide information related to OLR. CERES, on board the EOS Aqua and Terra satellites, contains broad band radiometers that measure total flux and short-wave flux, from which OLR is determined. AIRS is a high spectral resolution IR sounder on EOS Aqua that measures IR radiances covering most of the spectral interval 650 cm-1 to 2670 cm-1. These observations enable the determination of detailed information about atmospheric temperature, moisture, and ozone profiles, as well as surface skin temperatures and cloud parameters. The AIRS OLR product is the total flux over the spectral interval 2 cm-1 to2750 cm-1 computed for the surface and atmospheric state determined from AIRS observations. We compared spatial anomalies and trends of OLR, over the seven year period September 2002 through August 2009, as observed by CERES and computed using Version 5 AIRS products. These two sets of OLR anomalies and trends, obtained in very different ways, agree with each other almost perfectly in essentially every detail. This important finding shows that a very stable high spectral infra-red sounder such as AIRS corroborates the anomalies and trends of OLR obtained from CERES. More significantly, anomalies and trends of the individual geophysical parameters derived from AIRS explain the detailed causes of the anomalies and trends of CERES OLR. Both sets of results show that global mean OLR has been decreasing at a rate of 0.12 W/m2/yr over the seven year time period under study. Both also confirm that the primary cause of this is due to changes in the tropics, in which OLR has been decreasing at a rate of 0.27 W/m2/yr. AIRS products show that the decrease of tropical OLR is a result of increasing tropical atmospheric water vapor and cloud cover over the time period studied, which in turn is responding to a very strong E1 Nino/ La Nina cycle. Equatorial ocean temperatures between 160E and 120W cooled considerably during this time period, with corresponding local decreases in mid-tropospheric humidity and cloud cover, resulting in increases in local OLR. This was more than compensated by substantial increases in water vapor and cloud cover elsewhere in the tropics, resulting in a net decrease in tropical OLR.

Susskind, Joel↗
NASA NTRS1973

Remote sensing of ocean currents

The author has identified the following significant results. Fourteen field experiments in support of the NOAA investigation of ocean color boundary determination using ERTS-1 data have been conducted since June 1972. The boundary between coastal waters and the Loop Current has been detected by ERTS-1 as a result of sea state changes as well as color differences. Computer enchancement of MSS data are revealing many features not shown in the NDPF product. Analysis of the 24 channel MSS data shows that a thermal IR channel is required on an ERTS MSS to distinguish between atmospheric and sea state effects. Cloud cover analysis suggests the need for daily coverage of this type sensor for routinely useful oceanographic applications.

Maul, G. A.↗
NASA NTRS1980

Collapse and equilibrium of rotating, adiabatic clouds

A numerical hydrodynamics computer code analysis of the collapse and establishment of equilibrium of adiabatic gas clouds restricted to axial symmetry found that the clouds are originally uniform in density and rotation. The method can compare the dynamic collapse and approach to equilibrium with the data on incompressible uniformly rotating equilibrium clouds and on equilibrium structures of differentially rotating polytropes. It is concluded that the stellar formation theory indicates that the low alpha fragments produced at the termination of the dynamic isothermal collapse phase of interstellar clouds may undergo significant dynamic collapse in an adiabatic regime leading to transitory ring formation and additional fragmentation on a smaller scale.

Boss, A. P.↗
NASA NTRS1991

Heat transfer measurements from a smooth NACA 0012 airfoil

Local convective heat transfer coefficients were measured from a smooth NACA 0012 airfoil having a chord length of 0.533 m. Flight data were taken for the smooth airfoil at Reynolds numbers based on chord in the range 1.24 to 2.50 million and at various angles of attack up to 4 deg. During these flight tests, the freestream velocity turbulence intensity was found to be very low. Wind tunnel data were acquired in the Reynolds number range 1.20 to 4.52 million and at angles of attack from -4 to +8 deg. The turbulence intensity in the IRT was 0.5-0.7 percent with the cloud-generating sprays off. A direct comparison between the results obtained in flight and in the IRT showed that the higher level of turbulence intensity in the IRT had little effect on the heat transfer for the lower Reynolds numbers but caused a moderate increase in heat transfer at the higher Reynolds numbers. Turning on the cloud-generating spray nozzle atomizing air in the IRT did not alter the heat transfer. The present data were compared with leading-edge cylinder and flat plate heat transfer correlations that are often used to estimate airfoil heat transfer in computer codes.

Poinsatte, Philip E.↗
NASA NTRS1999

Modeling of Sub-Grid Heterogeneity and its Impact on GCM Global Radiation Balance

The spatial and temporal variability of high, low, and mid-level clouds is obtained from ISCCP D1 data. Monthly mean global maps of the observed cloud variability are used to re-scale GCM prognostic cloud optical depths and radiative parameters via the Monte Carlo cloud heterogeneity parameterization that utilizes the existing plane-parallel GCM radiative transfer model to compute radiative fluxes for inhomogeneous cloud distributions. The GCM radiative fluxes at TOA and the ground surface are then compared to ERBE and GEBA results. These comparisons show that including sub-grid cloud variability in the GCM radiative model improves agreement between the GCM radiative energy budget components and observations,

Lacis, Andrew↗
NASA NTRS2000

Tropospheric Ozone Profile Information Derived From "Cloud Slicing"

This study introduces a new approach to obtain ozone vertical profile information given coincident satellite measurements of both cloud-top pressure and above-cloud column ozone. This method is denoted "cloud slicing". In this study information of cloud-top pressure is derived from Geostationary Orbital Earth Satellite (GOES) infrared data, while above-cloud column ozone is obtained from the Earth Probe total ozone mapping spectrometer (TOMS) instrument. Several case examples are presented showing the feasibility of this technique as well as providing new geophysical results. Because the TOMS instrument measures backscattered UV radiation, it does detect ozone lying below dense water vapor clouds. This opaque property of TOMS can be used directly in conjunction with co-located cloud-top pressure data to derive ozone profile information in the troposphere. The cloud slicing method is an extension of the "Convective Cloud Differential" (CCD) method. In the CCD method, tropospheric column ozone (i.e., the total vertical column of ozone lying in the troposphere) is computed by taking total column ozone with low reflectivity (R less than 0.2) and subtracting from this a nearby measurement of above-cloud column ozone amount under conditions of high reflectivity (R greater than 0.9). (High reflectivity away from snow/ice conditions coincides with strong convection and tropopause-level clouds). The key element in determining tropospheric ozone profile information from the cloud slicing method is to have simultaneous and co-located measurements of both above-cloud column ozone and cloud-top pressure.

Ziemke, Jerald R.↗
NASA NTRS2003

Spatial Analysis of Great Lakes Regional Icing Cloud Liquid Water Content

Abstract Clustering of cloud microphysical conditions, such as liquid water content (LWC) and drop size, can affect the rate and shape of ice accretion and the airworthiness of aircraft. Clustering may also degrade the accuracy of cloud LWC measurements from radars and microwave radiometers being developed by the government for remotely mapping icing conditions ahead of aircraft in flight. This paper evaluates spatial clustering of LWC in icing clouds using measurements collected during NASA research flights in the Great Lakes region. We used graphical and analytical approaches to describe clustering. The analytical approach involves determining the average size of clusters and computing a clustering intensity parameter. We analyzed flight data composed of 1-s-frequency LWC measurements for 12 periods ranging from 17.4 minutes (73 km) to 45.3 minutes (190 km) in duration. Graphically some flight segments showed evidence of consistency with regard to clustering patterns. Cluster intensity varied from 0.06, indicating little clustering, to a high of 2.42. Cluster lengths ranged from 0.1 minutes (0.6 km) to 4.1 minutes (17.3 km). Additional analyses will allow us to determine if clustering climatologies can be developed to characterize cluster conditions by region, time period, or weather condition. Introduction

Ryerson, Charles C.↗