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At least 739 records · Page 41

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NASA NTRS1988

Preliminary statistical survey of plasmaspheric ion properties from observations by DE 1/RIMS

The paper presents mean temperatures and densities of plasmaspheric H(+) ions obtained from observations by the retarding ion mass spectrometer on Dynamics Explorer 1. Composition is shown in terms of ratios of densities of the various ion species to those of H(+). The spatial variations are indicated in terms of L shell profiles, with separate profiles for local morning and evening sides.

Comfort, R. H.↗

NASA NTRS1981

Procedures for analysis of spatial relationships among ship survey data and sea surface temperature

The establishment of a limited spatial data base for the U.S. eastern seaboard vicinity is discussed along with the demonstration of computer assisted analysis techniques for investigating spatial patterns and relationships among ship survey data and remotely sensed sea surface temperature. Ship survey variables included concentrations of two zooplankton, two icthyoplankton, and two fish species, in addition to physical data of depth to bottom and surface and bottom water temperatures. Continuous spatial distributions of these data were created by both weighted nearest neighbor and iterative smoothing interpolation techniques. Maps of surface water temperature were created by digitizing GOES satellite images. All mapped data were spatially registered by conversion of latitude and longitude coordinates to rotated Lambert conic conformal rectilinear coordinates and stored in grid format of approximately one hundred square kilometers per cell. The analysis of these data include the generation of statistical summaries and maps describing the joint occurrence among variables.

Berry, J. K.↗

NASA NTRS1987

Analyses and assessments of span wise gust gradient data from NASA B-57B aircraft

Analysis of turbulence measured across the airfoil of a Cambera B-57 aircraft is reported. The aircraft is instrumented with probes for measuring wind at both wing tips and at the nose. Statistical properties of the turbulence are reported. These consist of the standard deviations of turbulence measured by each individual probe, standard deviations and probability distribution of differences in turbulence measured between probes and auto- and two-point spatial correlations and spectra. Procedures associated with calculations of two-point spatial correlations and spectra utilizing data were addressed. Methods and correction procedures for assuring the accuracy of aircraft measured winds are also described. Results are found, in general, to agree with correlations existing in the literature. The velocity spatial differences fit a Gaussian/Bessel type probability distribution. The turbulence agrees with the von Karman turbulence correlation and with two-point spatial correlations developed from the von Karman correlation.

Frost, Walter↗

NASA NTRS1993

Concepts for conformal and body-axis attitude information for spatial awareness presented in a helmet-mounted display

A piloted simulation study has been conducted to evaluate two methods of presenting attitude information in a helmet-mounted display (HMD) for spatial awareness in a fighter airplane. One method, the body-axis concept, displayed the information relative to the body axis of the airplane. The quantitative results of this study favored the body-axis concept. Although no statistically significant differences were noted for either the pilots' understanding of roll attitude or target position, the pilots made pitch judgment errors three times more often with the conformal display. The subjective results showed the body-axis display did not cause attitude confusion, a prior concern with this display. In the posttest comments, the pilots overwhelmingly selected the body-axis display as the display of choice.

Jones, Denise R.↗

NASA NTRS1996

Statistical Models of Landscape Pattern and the Effects of Coarse Resolution of Satellite Imagery on Estimation of Area

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on ERS-1 SAR and fire scars on Landsat MSS imagery were measured. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions - a power distribution related to fractal processes or a simple exponential distribution. Comparison of the distribution of small bum scars as observed with Landsat to the distribution observed with AVHRR showed distortions due to the coarse spatial resolution of AVHRR caused a net overestimation of bum area. This bias was primarily caused by detection in 2 or 3 AVHRR pixels of bums whose true size was on the order of an AVHRR pixel.

Hlavka, Christine A.↗

NASA NTRS1995

Vertical Scales of Turbulence at the Mt. Wilson Observatory

The vertical scales of turbulence at the Mt. Wilson observatory are inferred from data from the University of California at Berkeley Infrared Spatial Interferometer (ISI), by modeling path length fluctuations observed in the interferometric paths to celestial objects and those in instrumental ground- based paths. The correlations between the stellar and ground-based path length fluctuations and the temporal statistic of those fluctuations are modeled on various time scales to constrain the vertical scales.

Mt. Wilson Observatory↗

NASA NTRS1981

Some statistical problems inherent in measuring precipitation

A formula permitting calculation of the mean-square error of the mean value of a random variable due to periodic sampling is derived and applied to estimating the sampling error for satellite observation of the mean rainfall during the GARP Atlantic Tropical Experiment (GATE). The effects of both spatial resolution and frequency of observation on the sampling error are summarized in graphs. It is found that four observations per day are sufficient to determine the monthly mean rainfall over an area of 2.5 deg square (280km x 280km) to within a standard deviation of 5 percent of its mean value; two samples per day would yield an error with a standard deviation slightly less than 10 percent of the mean. A satellite instrument with less frequent sampling may produce significantly greater error in the estimate of monthly mean rainfall.

Flueck, J. A.↗

NASA NTRS1986

Statistical characterization of sea surface geometry for a wave slope field discontinuous in the mean square

Statistics of two-dimensional wave groups, of steep wave events, and of a cascade pattern manifested in the surface geometry in a developed sea state are derived. A systematic view is presented of the spectral moment problem, highlighting its physical meaning and showing its relationship with the theory of random fields. A solution of this problem is suggested that is appropriate to the case of wind-generated surface waves. The solution method treats the surface elevation field as specified on a spatial (temporal) running grid, developing an averaging procedure which employs the Taylor microscale as the mesh size. The technique is illustrated by first exposing errors in direct calculations of the effective surface impedance for a coherently reflected L-band radio wave. The technique is then used to study wave groups and steep waves for a Gaussian, two-dimensional, time-varying surface. Finally, the theory is applied to estimate breaking wave statistics,

Glazman, R. E.↗

NASA NTRS1987

Spectral characteristics and the extent of paleosols of the Palouse formation

Three spectral models defining the spatial distribution of soil areas by levels of amorphous iron, organic carbon, and the ratio of amorphous iron to organic carbon were developed and field verification studies were conducted. The models used particular Thematic Mapper band ratios selected by statistical correlation with soil chemical data. The ability of the models to indicate erosion severity and to differentiate between iron enriched and carbonate paleosols is discussed. In addition, the effect of vegetation cover on paleosols is addressed.

Frazier, B. E.↗

NASA NTRS1994

Structural analysis of airborne flux estimates over a region

Aircraft-based observations of turbulence fields of velocity, moisture, and temperature are used to study coherent turbulent structures that dominate turbulent transfer of moisture and heat above three different eco-systems. Flux traces are defragmented, to reconstruct the presumed full size (along the sampled transect) of these structures, and flux traces are simplified by elimination of those that contribute negligibly to the flux estimate. Structures are analyzed in terms of size, spatial distribution, and contribution to the flux, in the four 'quadrant' modes of eddy-covariance transfer (excess up/down and deficit up/down). The effect of nonlinear detrending of moisture and temperature data on this 'structural analysis,' over surfaces with heterogeneous surface wetness, is also examined. Results over grassland, wetland, and moist and dry agricultural land, show that nonlinear detrending may provide a more physically realistic description of structures. Significant differences are observed between structure size and associated relative flux contribution, between moist and dry areas, with smaller structures playing a more important role over the moist areas. Structure size generally increases with height, as spatial reorganization from smaller structures into larger ones takes place. This coincides with a gradual loss of surface 'signature' (position and clustering of plumes above localized source areas). The data are expected to provide a basis for an eventual statistical description of boundary-layer transfer events , and help to interpret the link between boundary-layer transfer and hydrological surface conditions.

Caramori, Paulo↗

NASA NTRS1995

Vertical Scales of Turbulence at the Mount Wilson Observatory

The vertical scales of turbulence at the Mount Wilson Observatory are inferred from data from the University of California at Berkeley Infrared Spatial Interferometer (ISI), by modeling path length fluctuations observed in the interferometric paths to celestial objects and those in instrumental ground-based paths. The correlations between the stellar and ground-based path length fluctuations and the temporal statistics of those fluctuations are modeled on various timescales to constrain the vertical scales. A Kolmogorov-Taylor turbulence model with a finite outer scale was used to simulate ISI data. The simulation also included the white instrumental noise of the interferometer, aperture-filtering effects, and the data analysis algorithms. The simulations suggest that the path delay fluctuations observed in the 1992-1993 ISI data are largely consistent with being generated by refractivity fluctuations at two characteristic vertical scales: one extending to a height of 45 m above the ground, with a wind speed of about 1 m/ s, and another at a much higher altitude, with a wind speed of about 10 m/ s. The height of the lower layer is of the order of the dimensions of trees and other structures near the interferometer, which suggests that these objects, including elements of the interferometer, may play a role in generating the lower layer of turbulence. The modeling indicates that the high- attitude component contributes primarily to short-period (less than 10 s) fluctuations, while the lower component dominates the long-period (up to a few minutes) fluctuations. The lower component turbulent height, along with outer scales of the order of 10 m, suggest that the baseline dependence of long-term interferometric, atmospheric fluctuations should weaken for baselines greater than a few tens of meters. Simulations further show that there is the potential for improving the seeing or astrometric accuracy by about 30%-50% on average, if the path length fluctuations in the lower component are directly calibrated. Statistical and systematic effects induce an error of about 15 m in the estimate of the lower component turbulent altitude.

Treuhaft, Robert N.↗

NASA NTRS2003

Mathematical Inversion of Lightning Data: Techniques and Applications

A survey of some interesting mathematical inversion studies dealing with radio, optical, and electrostatic measurements of lightning are presented. A discussion of why NASA is interested in lightning, what specific physical properties of lightning are retrieved, and what mathematical techniques are used to perform the retrievals are discussed. In particular, a relatively new multi-station VHF time-of-arrival (TOA) antenna network is now on-line in Northern Alabama and will be discussed. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The LMA supports on-going ground-validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. The LMA also provides detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and offers interesting comparisons with other meteorological/geophysical datasets. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. A new channel mapping retrieval algorithm is introduced for this purpose. To characterize the spatial distribution of retrieval errors, the algorithm has been applied to analyze literally tens of millions of computer-simulated lightning VHF point sources that have been placed at various ranges, azimuths, and altitudes relative to the LMA network. Statistical results are conveniently summarized in high-resolution, color-coded, error maps.

Koshak, William↗

NASA NTRS2010

Influence of Satellite-Based Heterogeneous Vegetation Momentum Roughness on Mesoscale Model Dynamics During IHOP 2002

The sensitivity of mesoscale weather prediction model to a vegetation roughness initialization is investigated for the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database previously derived using a physically based procedure and MODIS imagery, and iii) a MODIS climatologic roughness database that possesses the same spatial heterogeneity as (i) but with mean land class values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations from meteorological stations within the Oklahoma mesonet and surrounding region during IHOP20O2. A sensitivity analysis on the impact the MODIS-based roughness fields is also made through a time-series intercomparison of temperature bias, probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE) the results that, for the current replacement of the standard land-cover type based roughness values with the satellite-derived fields statistically improves model performance for most of the observed variables. Further, the satellite-based roughness enhances the surface wind speed, PBL height and TKE production on the order of 3 to l0 percent, with a lesser effect over grassland and cropland domains, and the greater effect over mixed land cover domains

Jasinski, Michael↗

NASA NTRS2016

Gridded National Inventory of U.S. Methane Emissions

We present a gridded inventory of US anthropogenic methane emissions with 0.1 deg x 0.1 deg spatial resolution, monthly temporal resolution, and detailed scale dependent error characterization. The inventory is designed to be onsistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissionsand Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a widerange of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.

Methane↗

NASA NTRS2018

Introduction to Data Assimilation

Atmospheric data assimilation is a class of techniques used for producing descriptions of fields of air temperature, pressure, humidity, wind, etc. on a spatial grid or in terms of a finite functional representation. These are then used to initialize numerical weather forecasts or to analyze the atmosphere for other purposes. The techniques combine past, present, and even future observations in an approximate statistically optimal way. Various types of statistical or physically-based models and their corresponding adjoints are employed to relate diverse fields in both time and space and to relate what is observed to what is being analyzed. Computationally, the problem is very demanding and onstraining on the techniques that can be employed on a routine basis.

Atmospheric data assimilation↗

NASA NTRS2020

Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign

Although the characteristics of biomass burning events and the ambient ecosystem determine emitted smoke composition, the conditions that modulate the partitioning of black carbon (BC) and brown carbon (BrC) formation are not well understood, nor are the spatial or temporal frequency of factors driving smoke particle evolution, such as hydration, coagulation, and oxidation, all of which impact smoke radiative forcing. In situ data from surface observation sites and aircraft field campaigns offer deep insight into the optical, chemical, and microphysical traits of biomass burning (BB) smoke aerosols, such as single scattering albedo (SSA) and size distribution, but cannot by themselves provide robust statistical characterization of both emitted and evolved particles. Data from the NASA Earth Observing System’s Multi-Angle Imaging SpectroRadiometer (MISR) instrument can provide at least a partial picture of BB particle properties and their evolution downwind, once properly validated. Here we use in situ data from the joint NOAA/NASA 2019 Fire Influence on Regional to Global Environments Experiment-Air Quality (FIREX-AQ) field campaign to assess the strengths and limitations of MISR-derived constraints on particle size, shape, light-absorption, and its spectral slope, as well as plume height and associated wind vectors. Based on the satellite observations, we also offer inferences about aging mechanisms effecting downwind particle evolution, such as gravitational settling, oxidation, secondary particle formation, and the combination of particle aggregation and condensational growth. This work builds upon our previous study, adding confidence to our interpretation of the remote-sensing data based on an expanded suite of in situ measurements for validation. The satellite and in situ measurements offer similar characterizations of particle property evolution as a function of smoke age for the 06 August Williams Flats Fire, and most of the key differences in particle size and absorption can be attributed to differences in sampling and changes in the plume geometry between sampling times. Whereas the aircraft data provide validation for the MISR retrievals, the satellite data offer a spatially continuous mapping of particle properties over the plume, which helps identify trends in particle property downwind evolution that are ambiguous in the sparsely sampled aircraft transects. The MISR data record is more than two decades long, offering future opportunities to study regional wildfire plume behavior statistically, where aircraft data are limited or entirely lacking.

biomass burning↗

NASA NTRS2008

Mapping Electrical Crosstalk in Pixelated Sensor Arrays

Electronic coupling effects such as Inter-Pixel Capacitance (IPC) affect the quantitative interpretation of image data from CMOS, hybrid visible and infrared imagers alike. Existing methods of characterizing IPC do not provide a map of the spatial variation of IPC over all pixels. We demonstrate a deterministic method that provides a direct quantitative map of the crosstalk across an imager. The approach requires only the ability to reset single pixels to an arbitrary voltage, different from the rest of the imager. No illumination source is required. Mapping IPC independently for each pixel is also made practical by the greater S/N ratio achievable for an electrical stimulus than for an optical stimulus, which is subject to both Poisson statistics and diffusion effects of photo-generated charge. The data we present illustrates a more complex picture of IPC in Teledyne HgCdTe and HyViSi focal plane arrays than is presently understood, including the presence of a newly discovered, long range IPC in the HyViSi FPA that extends tens of pixels in distance, likely stemming from extended field effects in the fully depleted substrate. The sensitivity of the measurement approach has been shown to be good enough to distinguish spatial structure in IPC of the order of 0.1%.

focal plane array↗

NASA NTRS1975

The LANDSAT-1 multispectral scanner as a tool in the classification of inland lakes

Relationships between LANDSAT-1 multispectral scanner (MSS) data and the trophic status of a group of lakes in the north-northeastern part of the United States were studied by predicting the magnitudes of two trophic state indicators, estimating lake position on a multivariate trophic scale, and automatically classifying lakes according to their trophic state. Initially, the principal component ordination was employed with 100 lakes. MSS data for some 20 lakes was then extracted from computer-compatible tapes (CCT) using a binary marking technique. The output was in the form of descriptive statistics and photographic concatenations. Color ratios were incorporated into regression models for the prediction of Secchi disc transparency, chlorophyll a, and lake position on the tropic scale. Results indicate that the LANDSAT-1 system, although handicapped by low spectral and spatial resolutions as well as excessive cloud cover, can be used as a supplemental data source in lake survey programs.

Boland, D. H. P.↗