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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

The GEOS-iODAS: Description and Evaluation

This report documents the GMAO's Goddard Earth Observing System sea ice and ocean data assimilation systems (GEOS iODAS) and their evolution from the first reanalysis test, through the implementation that was used to initialize the GMAO decadal forecasts, and to the current system that is used to initialize the GMAO seasonal forecasts. The iODAS assimilates a wide range of observations into the ocean and sea ice components: in-situ temperature and salinity profiles, sea level anomalies from satellite altimetry, analyzed SST, and sea-ice concentration. The climatological sea surface salinity is used to constrain the surface salinity prior to the Argo years. Climatological temperature and salinity gridded data sets from the 2009 version of the World Ocean Atlas (WOA09) are used to help constrain the analysis in data sparse areas. The latest analysis, GEOS ODAS5.2, is diagnosed through detailed studies of the statistics of the innovations and analysis departures, comparisons with independent data, and integrated values such as volume transport. Finally, the climatologies of temperature and salinity fields from the Argo era, 2002-2011, are presented and compared with the WOA09.

Climate↗
NASA NTRS1987

Monitoring global vegetation using Nimbus-7 37 GHz data - Some empirical relations

The difference of the vertically and horizontally polarized brightness temperatures observed by the 37 GHz channel of the SMMR on board the Nimbus-7 satellite are correlated temporally with three indicators of vegetation density, namely the temporal variation of the atmospheric CO2 concentration at Mauna Loa (Hawaii), rainfall over the Sahel and the normalized difference vegetation index derived from the AVHRR on board the NOAA-7 satellite. SMMR 37 GHz and AVHRR provide complementary data sets for monitoring global vegetation, the 37 GHz data being more suitable for arid and semiarid regions as these data are more sensitive to changes in sparse vegetation. The 37-GHz data might be useful for understanding desertification and indexing Co2 exchange between the biosphere and the atmosphere.

Choudhury, B. J.↗
NASA NTRS1997

Illustrating Surface Shape in Volume Data via Principal Direction-Driven 3D Line Integral Convolution

The three-dimensional shape and relative depth of a smoothly curving layered transparent surface may be communicated particularly effectively when the surface is artistically enhanced with sparsely distributed opaque detail. This paper describes how the set of principal directions and principal curvatures specified by local geometric operators can be understood to define a natural 'flow' over the surface of an object, and can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape information in a perceptually intuitive way. The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures. By advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate a single scan-converted solid stroke texture that may intuitively represent the essential shape information of any level surface in the volume. To generate longer strokes over more highly curved areas, where the directional information is both most stable and most relevant, and to simultaneously downplay the visual impact of directional information in the flatter regions, one may dynamically redefine the length of the filter kernel according to the magnitude of the maximum principal curvature of the level surface at the point around which it is applied.

Interrante, Victoria↗
NASA NTRS2015

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model↗
NASA NTRS2021

Validation of Soil Moisture Data Products from the NASA SMAP Mission

The National Aeronautics and Space Administration (NASA)Soil Moisture Active Passive(SMAP) mission has been validatingits soil moisture (SM) products since the start of data production onMarch 31, 2015. Prior to launch, the mission defined a set of criteria for core validation sites (CVS) that enable the testing of the key mission SM accuracy requirement(unbiased root-mean-square error <0.04 m3/m3). Thevalidation approach also includes other (“sparse network”) in situSM measurements, satellite SM products, model-based SM products, and field experiments. Over the past six years, the SMAP SM products have been analyzed with respect to thesereference data,and the analysis approaches themselves have been scrutinizedin an effort to best understand the products’ performance. Validation of themost recent SMAP Level 2 and 3 SMretrievalproducts (R17000) shows that the L-band (1.4 GHz) radiometer-based SM record continues to meet mission requirements. The products aregenerallyconsistentwith SM retrievals from the European Space Agency (ESA)Soil Moisture Ocean Salinity mission, althoughthere aredifferencesin some regions. The high-resolution (3-km) SM retrieval product,generated by combining Copernicus Sentinel-1 data with SMAP observations,performswithin expectations. Currently, however,there is limited availability of3-kmCVSdatato support extensive validation at this spatial scale. The most recent (version 5)SMAP Level4 SMdata assimilation productprovidingsurface and root-zone SM with complete spatio-temporal coverageat 9-km resolution also meets performance requirements. The SMAP SM validation program will continue throughout the mission life; futureplans include expanding ittoforestedand high-latituderegions

SMAP↗
NASA NTRS2007

Efficient Implementation of an Optimal Interpolator for Large Spatial Data Sets

Interpolating scattered data points is a problem of wide ranging interest. A number of approaches for interpolation have been proposed both from theoretical domains such as computational geometry and in applications' fields such as geostatistics. Our motivation arises from geological and mining applications. In many instances data can be costly to compute and are available only at nonuniformly scattered positions. Because of the high cost of collecting measurements, high accuracy is required in the interpolants. One of the most popular interpolation methods in this field is called ordinary kriging. It is popular because it is a best linear unbiased estimator. The price for its statistical optimality is that the estimator is computationally very expensive. This is because the value of each interpolant is given by the solution of a large dense linear system. In practice, kriging problems have been solved approximately by restricting the domain to a small local neighborhood of points that lie near the query point. Determining the proper size for this neighborhood is a solved by ad hoc methods, and it has been shown that this approach leads to undesirable discontinuities in the interpolant. Recently a more principled approach to approximating kriging has been proposed based on a technique called covariance tapering. This process achieves its efficiency by replacing the large dense kriging system with a much sparser linear system. This technique has been applied to a restriction of our problem, called simple kriging, which is not unbiased for general data sets. In this paper we generalize these results by showing how to apply covariance tapering to the more general problem of ordinary kriging. Through experimentation we demonstrate the space and time efficiency and accuracy of approximating ordinary kriging through the use of covariance tapering combined with iterative methods for solving large sparse systems. We demonstrate our approach on large data sizes arising both from synthetic sources and from real applications.

Memarsadeghi, Nargess↗
NASA NTRS1987

Physical mechanisms of heat, momentum and turbulence fluxes

In a qualitative way, the physical mechanisms which generate fluxes of heat, momentum, and turbulence in the atmosphere are discussed. This material is presented to acquaint people with the Earth science aspects of turbulence as important processes in the atmosphere. To attempt to describe turbulent fluxes of heat, momentum, and moisture in precise mathematical detail becomes an intractable problem. It is burdened by an eighth order set of equations involving more variables than equations. It is a closure problem which requires complicated assumptions that are not necessarily always satisfied, variable boundary conditions, and sparse observational data. Therefore, we must approach the problem in a simplified manner to obtain any kind of solution involving the variables of shear, stress, and heat, moisture, and momentum fluxes. There are other problems, of course, in which the inclusion of the planetary boundary layer is extremely important. Air pollution studies, air-sea exchanges, mesoscale models, and so on, must account for the planetary layer in very specific terms. Some of the physical mechanisms that are involved in generating fluxes are described.

Theon, John S.↗
NASA NTRS2007

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

Robertson, Franklin↗
NASA NTRS2010

An Aircraft-Based Upper Troposphere Lower Stratosphere O3, CO, and H2O Climatology for the Northern Hemisphere

We present a climatology of O3, CO, and H2O for the upper troposphere and lower stratosphere (UTLS), based on a large collection of high ]resolution research aircraft data taken between 1995 and 2008. To group aircraft observations with sparse horizontal coverage, the UTLS is divided into three regimes: the tropics, subtropics, and the polar region. These regimes are defined using a set of simple criteria based on tropopause height and multiple tropopause conditions. Tropopause ]referenced tracer profiles and tracer ]tracer correlations show distinct characteristics for each regime, which reflect the underlying transport processes. The UTLS climatology derived here shows many features of earlier climatologies. In addition, mixed air masses in the subtropics, identified by O3 ]CO correlations, show two characteristic modes in the tracer ]tracer space that are a result of mixed air masses in layers above and below the tropopause (TP). A thin layer of mixed air (1.2 km around the tropopause) is identified for all regions and seasons, where tracer gradients across the TP are largest. The most pronounced influence of mixing between the tropical transition layer and the subtropics was found in spring and summer in the region above 380 K potential temperature. The vertical extent of mixed air masses between UT and LS reaches up to 5 km above the TP. The tracer correlations and distributions in the UTLS derived here can serve as a reference for model and satellite data evaluation

Tilmes, S.↗
NASA NTRS2007

Representation-Independent Iteration of Sparse Data Arrays

An approach is defined that describes a method of iterating over massively large arrays containing sparse data using an approach that is implementation independent of how the contents of the sparse arrays are laid out in memory. What is unique and important here is the decoupling of the iteration over the sparse set of array elements from how they are internally represented in memory. This enables this approach to be backward compatible with existing schemes for representing sparse arrays as well as new approaches. What is novel here is a new approach for efficiently iterating over sparse arrays that is independent of the underlying memory layout representation of the array. A functional interface is defined for implementing sparse arrays in any modern programming language with a particular focus for the Chapel programming language. Examples are provided that show the translation of a loop that computes a matrix vector product into this representation for both the distributed and not-distributed cases. This work is directly applicable to NASA and its High Productivity Computing Systems (HPCS) program that JPL and our current program are engaged in. The goal of this program is to create powerful, scalable, and economically viable high-powered computer systems suitable for use in national security and industry by 2010. This is important to NASA for its computationally intensive requirements for analyzing and understanding the volumes of science data from our returned missions.

James, Mark↗
NASA NTRS2006

Flight Operations Analysis Tool

Flight Operations Analysis Tool (FLOAT) is a computer program that partly automates the process of assessing the benefits of planning spacecraft missions to incorporate various combinations of launch vehicles and payloads. Designed primarily for use by an experienced systems engineer, FLOAT makes it possible to perform a preliminary analysis of trade-offs and costs of a proposed mission in days, whereas previously, such an analysis typically lasted months. FLOAT surveys a variety of prior missions by querying data from authoritative NASA sources pertaining to 20 to 30 mission and interface parameters that define space missions. FLOAT provides automated, flexible means for comparing the parameters to determine compatibility or the lack thereof among payloads, spacecraft, and launch vehicles, and for displaying the results of such comparisons. Sparseness, typical of the data available for analysis, does not confound this software. FLOAT effects an iterative process that identifies modifications of parameters that could render compatible an otherwise incompatible mission set.

Easter, Robert↗
NASA NTRS1983

The impact of satellite soundings and their distribution on forecast accuracy

The impact of satellite data is found to vary considerably from one map to another and from one geographic region to another. However, the impact of satellite data is generally small in comparison with forecast error. On the average, over land areas (where good conventional data permit accurate verification), the impact of satellite data on 48-hr forecasts of 500-mb height is seen to be neutral. Indirect numerical evidence is found, however, that satellite data has a marked positive impact in the lower and middle troposphere in ocean regions, especially those regions where conventional data are sparse. The impact over oceans is found to be especially noticeable in maps depicting the mean differences between the satellite and the conventional-data-only maps averaged over the period of the data set (January 1-14, 1980), both for analyses and for forecasts to 48 hours.

Thomasell, A., Jr.↗
NASA NTRS2009

Synthesis and Assimilation Systems - Essential Adjuncts to the Observing System

Assimilation systems synthesize diverse in-situ and satellite data streams into full four-dimensional state estimates by combining the strengths of each data set and also of the model. The resulting analysis provides an integrated view of the information in the various observations as well as derived estimates of unobserved quantities. Assimilation systems are particularly important for the ocean where subsurface observations, even today, are sparse and intermittent compared with the scales needed to represent ocean variability and where satellites only sense the surface. Increasingly, models and assimilation systems are being used to provide information about the current observing system and to help in the design plans for new observations. Whether it is as a user of observations or a contributor to evaluation of the observing system, ocean synthesis and assimilation systems are now an integral part of the global ocean observing and information system. Major advances have been made over the last decade under the auspices of WCRP's Climate Variability and Predictability Project (CLIVAR) and the Global Ocean Data Assimilation Experiment (GODAE). In addition to advances in the assimilation systems, there have been major developments in the observing system, with satellite altimetry, the tropical moored buoy arrays in the Pacific and Atlantic, and more recently Argo. These developments have led to significant advances in our understanding and prediction of ocean variations at both mesoscale and climate scales. Many challenges remain. Some of these challenges lie in the observations themselves, some in the assimilation systems that, even in the more recent era of unprecedented observations from satellite altimetry and Argo, provide different views of climate variations. Yet there are many examples of successful applications from ocean assimilation products. Use of these systems for assessing the observing system helps identify the strengths of each observation type, and indicates that none of the current observations is redundant. Indeed, the indication is that the ocean remains under-sampled and that further improvements in the observing system are needed for both climate monitoring and prediction. Future developments will be increasingly towards consistent analyses across components of the Earth system using, e.g., coupled atmosphere-ocean models.

Rienecker, Michele M.↗
NASA NTRS2013

A Global Ozone Climatology from Ozone Soundings via Trajectory Mapping: A Stratospheric Perspective

This study explores a domain-filling trajectory approach to generate a global ozone climatology from sparse ozonesonde data. Global ozone soundings of 51,898 profiles at 116 stations over 44 years (1965-2008) are used, from which forward and backward trajectories are performed for 4 days, driven by a set of meteorological reanalysis data. Ozone mixing ratios of each sounding from the surface to 26 km altitude are assigned to the entire path along the trajectory. The resulting global ozone climatology is archived monthly for five decades from the 1960s to the 2000s with grids of 5 degree 5 degree 1 km (latitude, longitude, and altitude). It is also archived yearly from 1965 to 2008. This climatology is validated at 20 ozonesonde stations by comparing the actual ozone sounding profile with that found through the trajectories, using the ozone soundings at all the stations except one being tested. The two sets of profiles are in good agreement, both individually with correlation coefficients between 0.975 and 0.998 and root mean square (RMS) differences of 87 to 482 ppbv, and overall with a correlation coefficient of 0.991 and an RMS of 224 ppbv. The ozone climatology is also compared with two sets of satellite data, from the Satellite Aerosol and Gas Experiment (SAGE) and the Optical Spectrography and InfraRed Imager System (OSIRIS). Overall, the ozone climatology compares well with SAGE and OSIRIS data by both seasonal and zonal means. The mean difference is generally under 20 above 15 km. The comparison is better in the northern hemisphere, where there are more ozonesonde stations, than in the southern hemisphere; it is also better in the middle and high latitudes than in the tropics, where assimilated winds are imperfect in some regions. This ozone climatology can capture known features in the stratosphere, as well as seasonal and decadal variations of these features. Furthermore, it provides a wealth of detail about longitudinal variations in the stratosphere such as the spring ozone maximum over the Canadian Arctic. It also covers higher latitudes than current satellite data. The climatology shows clearly the depletion of ozone from the 1970s to the mid 1990s and ozone recovery in the 2000s. When this climatology is used as the upper boundary condition in an Environment Canada operational chemical forecast model, the forecast is improved in the vicinity of the upper tropospherelower stratosphere region. As this ozone climatology is neither dependent on a priori data or photochemical modeling, it provides independent information and insight that can supplement satellite data and model simulations and enhance our understanding of stratospheric ozone.

SAGE↗
NASA NTRS2021

Weather Intelligent Navigation Data and Models for Aviation Planning (WINDMAP)

WINDMAP addresses the emerging needs in the aviation community of providing real-time weather forecasting to improve the safety of low altitude aircraft operations. This is accomplished through the integration of real-time observations from autonomous systems, such as drones and urban air taxis, with numerical weather prediction models and flight management and safety systems. To solve this problem, several technical challenges have been identified. These include (1) developing autonomous UAS capable of conducting observations accurately and reliably; (2) determining the number and frequency of required observations and the sensitivity of these observations in data sparse regions of the lower atmosphere;(3) assimilating dense observational data into models in real-time with sufficient resolution and accuracy; (4) developing novel physics-based reduced order models capable of incorporating diverse data sets; and (5)integrating real-time forecasting into UTM and DAA (detect-and-avoid) architectures for path planning and navigation. The goal of this proposed effort is to demonstrate the value of using small UAS to collect measurements of the dynamic and thermodynamic properties of the lower atmosphere at scales that match or exceed the spatio-temporal resolution of today’s best numerical weather prediction models

Koushik Datta↗
NASA NTRS1980

Korean coastal water depth/sediment and land cover mapping /1:25,000/ by computer analysis of Landsat imagery

Computer analysis was applied to single data Landsat MSS imagery of a coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map, and featuring large dynamic sediment transport processes. Supervised image processing yielded a test classification map containing five water depth/sediment classes, two shoreline/tidal classes and five coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%; the training sets were selected by direct examination of the digitally displayed imagery. The unsupervised ISOCLAS (Senkus, 1976) clustering analysis was performed to assess the relative value of this approach to image classification in areas of sparse or nonexistent ground control. Results indicate that it is feasible to produce quantitative maps for detailed study of dynamic coastal processes given a Landsat image data base at sufficiently frequent time intervals.

Park, K. Y.↗
NASA NTRS1990

Two-dimensional shape recognition using sparse distributed memory

Researchers propose a method for recognizing two-dimensional shapes (hand-drawn characters, for example) with an associative memory. The method consists of two stages: first, the image is preprocessed to extract tangents to the contour of the shape; second, the set of tangents is converted to a long bit string for recognition with sparse distributed memory (SDM). SDM provides a simple, massively parallel architecture for an associative memory. Long bit vectors (256 to 1000 bits, for example) serve as both data and addresses to the memory, and patterns are grouped or classified according to similarity in Hamming distance. At the moment, tangents are extracted in a simple manner by progressively blurring the image and then using a Canny-type edge detector (Canny, 1986) to find edges at each stage of blurring. This results in a grid of tangents. While the technique used for obtaining the tangents is at present rather ad hoc, researchers plan to adopt an existing framework for extracting edge orientation information over a variety of resolutions, such as suggested by Watson (1987, 1983), Marr and Hildreth (1980), or Canny (1986).

Kanerva, Pentti↗
NASA NTRS1972

A detailed gravimetric geoid of North America, Eurasia, and Australia

A detailed gravimetric geoid of North America, the North Atlantic, Eurasia, and Australia computed from a combination of satellite-derived and surface 1 x 1 gravity data, is presented. Using a consistent set of parameters, this geoid is referenced to an absolute datum. The precision of this detailed geoid is + or - 2 meters in the continents but may be in the range of 5 to 7 meters in those areas where data was sparse. Comparisons of the detailed gravimetric geoid with results of Rice for the United States, Bomford and Fischer in Eurasia, and Mather in Australia are presented. Comparisons are also presented with geoid heights from satellite solutions for geocentric station coordinates in North America, the Caribbean, Europe, and Australia.

Vincent, S.↗