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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding the Spatiotemporal Variability of Tropical Orographic Rainfall Using Convective Plume Buoyancy

Abstract Mechanical forcing by orography affects precipitating convection across many tropical regions, but controls on the intensity and horizontal extent of the orographic precipitation peak and rain shadow remain poorly understood. A recent theory explains this control of precipitation as arising from modulation of lower-tropospheric temperature and moisture by orographic mechanical forcing, setting the distribution of convective rainfall by controlling parcel buoyancy. Using satellite and reanalysis data, we evaluate this theory by investigating spatiotemporal precipitation variations in six mountainous tropical regions spanning South and Southeast Asia, and the Maritime Continent. We show that a strong relationship holds in these regions between daily precipitation and a measure of convective plume buoyancy. This measure depends on boundary layer thermodynamic properties and lower-free-tropospheric moisture and temperature. Consistent with the theory, temporal variations in lower-free-tropospheric temperature are primarily modulated by orographic mechanical lifting through changes in cross-slope wind speed. However, winds directed along background horizontal moisture gradients also influence lower-tropospheric moisture variations in some regions. The buoyancy measure is also shown to explain many aspects of the spatial patterns of precipitation. Finally, we present a linear model with two horizontal dimensions that combines mountain wave dynamics with a linearized closure exploiting the relationship between precipitation and plume buoyancy. In some regions, this model skillfully captures the spatial structure and intensity of rainfall; it underestimates rainfall in regions where time-mean ascent in large-scale convergence zones shapes lower-tropospheric humidity. Overall, these results provide new understanding of fundamental processes controlling subseasonal and spatial variations in tropical orographic precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying the Impacts of Grain-scale Heterogeneity on Mechanical Response

Driven by the exceedingly high computational demands of simulating mechanical response in complex engineered systems with finely resolved finite element models, there is a critical need to optimally reduce the fidelity of such simulations. The minimum required fidelity is constrained by error tolerances on the simulation results, but error bounds are often impossible to obtain a priori. One such source of error is the variability of material properties within a body due to spatially non-uniform processing conditions and inherent stochasticity in material microstructure. This study seeks to quantify the effects of microstructural heterogeneity on component- and system-scale performance to aid in the choice of an appropriate material model and spatial resolution for finite element analysis.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Nimbus hydrological observations over the watersheds of the Niger and Indus rivers

As a result of studying the Nimbus imagery over these two watersheds, it is felt that a perspective and understanding of the large scale hydrological processes and their interrelationship has been obtained which could be obtained by no other means in so short a time. In the case of the Niger River a much better appreciation of the flooding process has been obtained along with the role of the Inland Delta in this process. Obviously a knowledge of the spatial and temporal distribution of the snow-melt process in the Indus River watershed is now available that was obtained with minimal effort, as compared to the effort and time that would be required using conventional methods. It seems clear that even the low resolution data easily available from meteorological satellites can be a valuable source of information in the better management of the water resources in these regions.

Salomonson, V. V.↗
NASA NTRS1990

Quantitative characterization of spatial distribution of particles in materials: Application to materials processing

Most engineering materials contain second phase particles or fibers which serve to reinforce the matrix phase. The effect of reinforcements on material properties is usually analyzed in terms of the average volume fraction and spacing of reinforcements, quantities which are global microstructural characteristics. However, material properties can also depend on local microstructural characteristics; for example, on how uniformly the reinforcing phase is distributed in the material. The analysis method will then be applied to a materials processing problem to discover how processing parameters can be selected to maximize redistribution of the reinforcing phase during processing. Several mathematical analysis methods could be adapted to the problem of characterizing the distribution of particles in materials. A tessellation-based method was selected. In the first phase of the investigation, a software package was written to automate the analysis. Typical results are shown. The analysis technique allows the degree to which particles are clustered together, the size and spacing of particle clusters, and the particle density in clusters to be found. The analysis methods were applied to computer-generated distributions and to a few real particle-containing materials. Methods for analyzing a nonuniform particle distribution in a material can be applied to two broad classes of materials science problems: understanding how the resulting particle distribution affects properties. The analysis method described is applied to a materials processing problem: how to select extrusion conditions to maximize the redistribution of reinforcing particles that are initially nonuniformly distributed. In addition, the tessellation-based method to analyze star distributions in spiral galaxies was adapted, illustrating the diverse types of problems to which the analysis method can be applied.

Parse, J. B.↗
NASA NTRS2011

AIRS-Observed Interrelationships of Anomaly Time-Series of Moist Process-Related Parameters and Inferred Feedback Values on Various Spatial Scales

In the beginning, a good measure of a GMCs performance was their ability to simulate the observed mean seasonal cycle. That is, a reasonable simulation of the means (i.e., small biases) and standard deviations of TODAY?S climate would suffice. Here, we argue that coupled GCM (CG CM for short) simulations of FUTURE climates should be evaluated in much more detail, both spatially and temporally. Arguably, it is not the bias, but rather the reliability of the model-generated anomaly time-series, even down to the [C]GCM grid-scale, which really matter. This statement is underlined by the social need to address potential REGIONAL climate variability, and climate drifts/changes in a manner suitable for policy decisions.

Molnar, Gyula I.↗
NASA NTRS1991

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Davis, Frank W.↗
NASA NTRS1994

Data assimilation and model evaluation experiment datasets

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Lai, Chung-Cheng A.↗
NASA NTRS1991

Recent advances in the ITO/InP solar cell

It was demonstrated that Indium Tin Oxide (ITO)/InP solar cells can now be made on as-received p(-) bulk substrates which are of nearly equal quality to those which could previously only be made on epitaxially grown p(-) InP base layers. Although this advancement is due in part to both increases in substrate quality and a better understanding of back contact formation, it appears that the passivation/compensation effects resulting from having H2 in the sputtering gas tends to reduce significantly the performance differences previously observed between these two substrates. It is shown that since high efficiency ITO/InP cells can be made from as-received substrates, and since the type conversion process is not highly spatially dependent, large area ITO/InP cells (4 sq cm) with efficiencies approaching 17 percent (Global) can be made. Furthermore, the measured open circuit voltages (V sub OC) and quantum efficiencies (QEs) from these large cells suggest that, when they are processed using optimum grid designs, the efficiencies will be nearly equal to that of the smaller cells thus far produced. It has been shown, through comparative experiments involving ITO/InP and IO/InP cells, that Sn may not be the major cause of type conversion of the InP surface and thus further implies that the ITO may not be an essential element in this type of device. Specifically, very efficient photovoltaic solar cells were made by sputtering (Sn free) In2O3 showing that type conversion and subsequent junction formation will occur even in the absence of the sputtered SN species. The result suggests that sputter damage may indeed be the important mechanism(s) of type conversion. Finally, an initial study of the stability of the ITO/InP cell done over the course of about one year has indicated that the J(sub SC) (short circuit current) and the fill factor (FF) are measurably stable within experimental certainty.

Gessert, T. A.↗
NASA NTRS1983

Massively parallel processor computer

An apparatus for processing multidimensional data with strong spatial characteristics, such as raw image data, characterized by a large number of parallel data streams in an ordered array is described. It comprises a large number (e.g., 16,384 in a 128 x 128 array) of parallel processing elements operating simultaneously and independently on single bit slices of a corresponding array of incoming data streams under control of a single set of instructions. Each of the processing elements comprises a bidirectional data bus in communication with a register for storing single bit slices together with a random access memory unit and associated circuitry, including a binary counter/shift register device, for performing logical and arithmetical computations on the bit slices, and an I/O unit for interfacing the bidirectional data bus with the data stream source. The massively parallel processor architecture enables very high speed processing of large amounts of ordered parallel data, including spatial translation by shifting or sliding of bits vertically or horizontally to neighboring processing elements.

Fung, L. W.↗
NASA NTRS2014

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Light Detection & Ranging (LIDAR)↗
NASA NTRS2003

Software for Acoustic Rendering

SLAB is a software system that can be run on a personal computer to simulate an acoustic environment in real time. SLAB was developed to enable computational experimentation in which one can exert low-level control over a variety of signal-processing parameters, related to spatialization, for conducting psychoacoustic studies. Among the parameters that can be manipulated are the number and position of reflections, the fidelity (that is, the number of taps in finite-impulse-response filters), the system latency, and the update rate of the filters. Another goal in the development of SLAB was to provide an inexpensive means of dynamic synthesis of virtual audio over headphones, without need for special-purpose signal-processing hardware. SLAB has a modular, object-oriented design that affords the flexibility and extensibility needed to accommodate a variety of computational experiments and signal-flow structures. SLAB s spatial renderer has a fixed signal-flow architecture corresponding to a set of parallel signal paths from each source to a listener. This fixed architecture can be regarded as a compromise that optimizes efficiency at the expense of complete flexibility. Such a compromise is necessary, given the design goal of enabling computational psychoacoustic experimentation on inexpensive personal computers.

Miller, Joel D.↗
NASA NTRS1990

A discrepancy within primate spatial vision and its bearing on the definition of edge detection processes in machine vision

The visual perception of form information is considered to be based on the functioning of simple and complex neurons in the primate striate cortex. However, a review of the physiological data on these brain cells cannot be harmonized with either the perceptual spatial frequency performance of primates or the performance which is necessary for form perception in humans. This discrepancy together with recent interest in cortical-like and perceptual-like processing in image coding and machine vision prompted a series of image processing experiments intended to provide some definition of the selection of image operators. The experiments were aimed at determining operators which could be used to detect edges in a computational manner consistent with the visual perception of structure in images. Fundamental issues were the selection of size (peak spatial frequency) and circular versus oriented operators (or some combination). In a previous study, circular difference-of-Gaussian (DOG) operators, with peak spatial frequency responses at about 11 and 33 cyc/deg were found to capture the primary structural information in images. Here larger scale circular DOG operators were explored and led to severe loss of image structure and introduced spatial dislocations (due to blur) in structure which is not consistent with visual perception. Orientation sensitive operators (akin to one class of simple cortical neurons) introduced ambiguities of edge extent regardless of the scale of the operator. For machine vision schemes which are functionally similar to natural vision form perception, two circularly symmetric very high spatial frequency channels appear to be necessary and sufficient for a wide range of natural images. Such a machine vision scheme is most similar to the physiological performance of the primate lateral geniculate nucleus rather than the striate cortex.

Jobson, Daniel J.↗
NASA NTRS1983

Geometric accuracy of LANDSAT-4 MSS image data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CCT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 x 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSATS -1, -2 and -3.

Welch, R.↗
NASA NTRS1984

Geometric Accuracy of LANDSAT-4 MSS Image Data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CTT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 by 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSAT-1, -2 AND -3.

Welch, R.↗
NASA NTRS1984

LANDSAT 4 investigations of Thematic Mapper and multispectral scanner applications

The optimum index factor package was used to choose TM band for color compositing. Processing techniques were also used on TM data over several sites to: (1) reduce the amount of data that needs to be processed and analyzed by using statistical methods or by combining full-resolution products with spatially compressed products; (2) digitally process small subareas to improve the visual appearance of large-scale products or to merge different-resolution image data; and (3) evaluate and compare the information content of the different three-band combinations that can be made using the TM data. Results indicate that for some applications the added spectral information over MSS is even more important than the TM's increased spatial resolution.

Lauer, D. T.↗
NASA NTRS1994

FORTRAN programs to process Magsat data for lithospheric, external field, and residual core components

The FORTRAN programs supplied in this document provide a complete processing package for statistically extracting residual core, external field and lithospheric components in Magsat observations. To process the individual passes: (1) orbits are separated into dawn and dusk local times and by altitude, (2) passes are selected based on the variance of the magnetic field observations after a least-squares fit of the core field is removed from each pass over the study area, and (3) spatially adjacent passes are processed with a Fourier correlation coefficient filter to separate coherent and non-coherent features between neighboring tracks. In the second state of map processing: (1) data from the passes are normalized to a common altitude and gridded into dawn and dusk maps with least squares collocation, (2) dawn and dusk maps are correlated with a Fourier correlation efficient filter to separate coherent and non-coherent features; the coherent features are averaged to produce a total field grid, (3) total field grids from all altitudes are continued to a common altitude, correlation filtered for coherent anomaly features, and subsequently averaged to produce the final total field grid for the study region, and (4) the total field map is differentially reduced to the pole.

Alsdorf, Douglas E.↗
NASA NTRS2006

A Mission to Observe Ice in Clouds from Space

To date there have been multiple satellite missions to observe and retrieve cloud top properties and the liquid in, and precipitation from, clouds. There are currently a few missions that attempt to measure cloud ice properties as a byproduct of other observations. However, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. This presentation will describe the Submillimeter-wave InfraRed Ice Cloud Experiment (SIRICE) concept, a satellite mission designed to acquire global Earth radiance measurements in the infrared and submillimeter-wave region (183-874 GHz). If successful, this mission will bridge the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. The brightness temperatures at submillimeter-wave frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. Scientific justification and the SIRICE approach to measuring ice water path and particle size that span a range encompassing both the hydrologically active and radiatively active components of cloud systems will be presented.

Ackerman, S.↗
NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Tao, W. K.↗