SEARCH · Search NASA

Results for “time series”

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.

SourceResearch connectionFrom yearThrough year

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

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

NASA NTRS1988

Airborne time-series measurement of soil moisture using terrestrial gamma radiation

Terrestrial gamma radiation data and independent ground-based core soil moisture data are analyzed. They reveal the possibility of using natural terrestrial gamma radiation collected from a low-flying aircraft to make reliable real-time soil moisture measurements for the upper 20 cm of soil. The airborne data were compared to the crude ground-based soil moisture data set collected at the core sites.

Carroll, Thomas R.↗

NASA NTRS2004

DORIS satellite antenna maps derived from long-term residuals time series

Recent studies have shown that phase pattern models for the Jason-1 GPS antenna significantly benefit GPS-based precise orbit determination (POD) for the satellite. We have used a similar technique to derive DORIS receiver antenna maps, using all available DORIS tracking data over long time periods (from 1993.0 to 2004.0). We demonstrate that the derived correction models are satellite specific. For a given satellite, year-to-year estimations show clear systematic patterns. Some of these systematic patterns are attributable to the derivative of the multi-path effects in the direction of the satellite velocity. For early SPOT data, the patterns can be explained by an offset in the TAI time tagging (typically 8 (mu)s). In a second step, we have applied the SPOT2 antenna correction models in precise orbit determination and in the positioning of ground beacons. Preliminary results on DORIS/SPOT2 show that application of the DORIS antenna maps lead to a slight improvement of the derived POD and geodetic results (typically less than 5%).

precise orbit determination (POD)↗

NASA NTRSDate not supplied

Adventures in Astronomical Time Series Analysis

Welcome to a tour of the volatile, highly active Universe — in stark contrast to earlier serene ``clockwork’’ visions. Innovative data analysis techniques have illuminated explosive physical processes animating these systems. Examples include a Fourier transform suited to the irregular sampling characteristic of much astronomical data, but time domain techniques will be emphasized for these applications: gamma-ray activity in the Crab Nebula, gamma-ray bursts, active galactic nuclei, and gravitational waves. I hope this talk will change some of the ways you carry out statistical data analysis.

Jeffrey D Scargle↗

NASA NTRS1981

A radar image time series

A set of ten side-looking radar images of a mining area in Arizona that were aquired over a period of 14 yr are studied to demonstrate the photogrammetric differential-rectification technique applied to radar images and to examine changes that occurred in the area over time. Five of the images are rectified by using ground control points and a digital height model taken from a map. Residual coordinate errors in ground control are reduced from several hundred meters in all cases to + or - 19 to 70 m. The contents of the radar images are compared with a Landsat image and with aerial photographs. Effects of radar system parameters on radar images are briefly reviewed.

Leberl, F.↗

NASA NTRS1986

A direct time series comparison between the La Jolla and Belfast radiocarbon records

For many years it has been widely assumed that the variations in the level of atmospheric carbon-14 were due to statistical fluctuations arising from experimental error. This is understandable since the signal/noise ratio is very low and the time sequences representing the variations are strongly stochastic. Interlaboratory comparisons show that baseline variations in the absolute value of the carbon-14 concentration do exist. However, assuming linearity, the delta 14C values are independent of these. The importance of assessing the quantitive reality of the delta 14C values is based upon their expression of the interplanetary cosmic ray source function, because in the range of 100 to 1000 year periods, there appears to be no evidence that the Earth's magnetic field is the source modulating function. Therefore the modulation is either due to changes in the solar atmosphere propagated out into the solar wind, or extra-heliospheric pressure effects, but these appear to be unlikely for the periods noted here. The recent availability of the new high quality Belfast time sequence of delta 14C now permits a simple mutual assessment of the several sequences which are available. Since the La Jolla record has been a standard for many years , these two were chosen for a simple comparison. Although differences exist, the close agreement between these two sequences, one carried out on White mountain Bristlecone pines, and the other done using Irish peat bog wood, is striking. This correlation between the two strongly reinforces the statistical view that the delta 14C record is that of real interplanetary modulation of the cosmic ray source leading to the generation of atmospheric 14C.

Sonett, C. P.↗

NASA NTRS1982

Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data

Detection of a periodic signal hidden in noise is frequently a goal in astronomical data analysis. This paper does not introduce a new detection technique, but instead studies the reliability and efficiency of detection with the most commonly used technique, the periodogram, in the case where the observation times are unevenly spaced. This choice was made because, of the methods in current use, it appears to have the simplest statistical behavior. A modification of the classical definition of the periodogram is necessary in order to retain the simple statistical behavior of the evenly spaced case. With this modification, periodogram analysis and least-squares fitting of sine waves to the data are exactly equivalent. Certain difficulties with the use of the periodogram are less important than commonly believed in the case of detection of strictly periodic signals. In addition, the standard method for mitigating these difficulties (tapering) can be used just as well if the sampling is uneven. An analysis of the statistical significance of signal detections is presented, with examples

Scargle, J. D.↗

NASA NTRS2010

An Examination of the Hadley Sea-Surface Temperature Time Series for the Nino 3.4 Region

The Hadley sea-surface temperature (HadSST) dataset is investigated for the interval 1871-2008. The purpose of this investigation is to determine the degree of success in identifying and characterizing El Nino (EN) southern (ENSO) extreme events, both EN and La Nina (LN) events. Comparisons are made against both the Southern Oscillation Index for the same time interval and with published values of the Oceanic Nino Index for the interval since 1950. Some 60 ENSO extreme events are identified in the HadSST dataset, consisting of 33 EN and 27 LN events. Also, preferential associations are found to exist between the duration of ENSO extreme events and their maximum anomalous excursion temperatures and between the recurrence rate for an EN event and the duration of the last known EN event. Because the present ongoing EN is a strong event, it should persist 11 months or longer, inferring that the next EN event should not be expected until June 2012 or later. Furthermore, the decadal sum of EN-related months is found to have increased somewhat steadily since the decade of 1920-1929, suggesting that the present decade (2010-2019) possibly will see about 3-4 EN events, totaling about 37 +/- 3 EN-related months (i.e., months that meet the definition for the occurrence of an EN event).

Wilson, Robert M.↗

NASA NTRS1996

Variance Analysis of Unevenly Spaced Time Series Data

We have investigated the effect of uneven data spacing on the computation of delta (sub chi)(gamma). Evenly spaced simulated data sets were generated for noise processes ranging from white phase modulation (PM) to random walk frequency modulation (FM). Delta(sub chi)(gamma) was then calculated for each noise type. Data were subsequently removed from each simulated data set using typical two-way satellite time and frequency transfer (TWSTFT) data patterns to create two unevenly spaced sets with average intervals of 2.8 and 3.6 days. Delta(sub chi)(gamma) was then calculated for each sparse data set using two different approaches. First the missing data points were replaced by linear interpolation and delta (sub chi)(gamma) calculated from this now full data set. The second approach ignored the fact that the data were unevenly spaced and calculated delta(sub chi)(gamma) as if the data were equally spaced with average spacing of 2.8 or 3.6 days. Both approaches have advantages and disadvantages, and techniques are presented for correcting errors caused by uneven data spacing in typical TWSTFT data sets.

Hackman, Christine↗

NASA NTRS2017

Single Object & Time Series Spectroscopy with JWST NIRCam

JWST will enable high signal-to-noise spectroscopic observations of the atmospheres of transiting planets with high sensitivity at wavelengths that are inaccessible with HST or other existing facilities. We plan to exploit this by measuring abundances, chemical compositions, cloud properties, and temperature-pressure parameters of a set of mostly warm (T 600 - 1200 K) and low mass (14 -200 Earth mass) planets in our guaranteed time program. These planets are expected to have significant molecular absorptions of H2O, CH4, CO2, CO, and other molecules that are key for determining these parameters and illuminating how and where the planets formed. We describe how we will use the NIRCam grisms to observe slitless transmission and emission spectra of these planets over 2.4 - 5.0 microns wavelength and how well these observations can measure our desired parameters. This will include how we set integration times, exposure parameters, and obtain simultaneous shorter wavelength images to track telescope pointing and stellar variability. We will illustrate this with specific examples showing model spectra, simulated observations, expected information retrieval results, completed Astronomer's Proposal Tools observing templates, target visibility, and other considerations.

NIRCam↗

NASA NTRS2023

A Machine Learning-Based Approach to Time-Series Wave Identification in the Solar Wind

The Wind spacecraft has yielded several decades of high-resolution magnetic field data, a large fraction of which displays small-scale structures. In particular, the solar wind is full of wavelike fluctuations that appear in both the field magnitude and its components. The nature of these fluctuations can be tied to the properties of other structures in the solar wind, such as shocks, that have implications for the time evolution of the solar wind. As such, having a large collection of wave events would facilitate further study of the effects that these fluctuations have on solar wind evolution. Given the large volume of magnetic field data available, machine learning is the most practical approach to classifying the myriad small-scale structures observed. To this end, a subset of Wind data is labeled and used as a training set for a multi-branch 1D convolutional neural network aimed at classifying circularly polarized wave modes. Using this algorithm, a preliminary statistical study of one year of data is performed, yielding about 300,000 wave intervals out of about 5,000,000 solar wind intervals. The wave intervals come about more often in the fast solar wind and at higher temperatures, and the number of waves per day is highly periodic. This machine learning-based approach to wave detection has the potential to be a powerful, inexpensive way to catalog waves throughout decades of spacecraft data.

Samuel Fordin↗

NASA NTRS1992

Late quaternary time series of Arabian Sea productivity: Global and regional signals

Modern annual floral and faunal production in the northwest Arabian Sea derives primarily from upwelling induced by strong southwest winds during June, July, and August. Indian Ocean summer monsoon winds are, in turn, driven by differential heating between the Asian continent and the Indian ocean to the south. This differential heating produces a strong pressure gradient resulting in southwest monsoon winds and both coastal and divergent upwelling off the Arabian Peninsula. Over geologic time scales (10(exp 4) to 10(exp 6) years), monsoon wind strength is sensitive to changes in boundary conditions which influence this pressure gradient. Important boundary conditions include the seasonal distribution of solar radiation, global ice volume, Indian Ocean sea surface temperature, and the elevation and albedo of the Asian continent. To the extent that these factors influence monsoon wind strength, they also influence upwelling and productivity. In addition, however, productivity associated with upwelling can be decoupled from the strength of the summer monsoon winds via ocean mechanisms which serve to inhibit or enhance the nutrient supply in the intermediate waters of the Indian Ocean, the source for upwelled waters in the Arabian Sea. To differentiate productivity associated with wind-induced upwelling from that associated with other components of the system such as nutrient sequestering in glacial-age deep waters, we employ a strategy which monitors independent components of the oceanic and atmospheric subsystems. Using sediment records from the Owen Ridge, northwest Arabian Sea, we monitor the strength of upwelling and productivity using two independent indicators, percent G. bulloides and opal accumulation. We monitor the strength of southwest monsoon winds by measuring the grain-size of lithogenic dust particles blown into the Arabian Sea from the surrounding deserts of the Somali and Arabian Peninsulas. Our current hypothesis is that the variability associated with the 41 kyr power in the G. bulloides and opal accumulation records derive from nutrient availability in the intermediate waters which are upwelled via monsoon winds. This hypothesis is testable by comparison with Cd records of intermediate and deep waters of the Atlantic and Indian Ocean.

Clemens, Steven C.↗

NASA NTRS1994

A numerical analysis of shipboard and coastal zone color scanner time series of new production within Gulf Stream cyclonic eddies in the South Atlantic Bight

Eddy-induced upwelling occurs along the western edge of the Gulf Stream between Cape Canaveral, Florida, and Cape Hatteras, North Carolina, in the South Atlantic Bight (SAB). Coastal zone color scanner images of 1-km resolution spanning the period April 13-21, 1979, were processed to examine these eddy features in relation to concurrent shipboard and current/temperature measurements at moored arrays. A quasi-one-dimensional (z), time dependent biological model, using only nitrate as a nutrient source, has been combined with a three-dimensional physical model in an attempt to replicate the observed phytoplankton field at the northward edge of an eddy. The model is applicable only to the SAB south of the Charleston Bump, at approximately 31.5 deg N, since no feature analogous to the bump exists in the model bathymetry. The modeled chlorophyll, nitrate, and primary production fields of the euphotic zone are very similar to those obtained from the satellite and shipboard data at the leading edges of the observed eddies south of the Charleston Bump. The horizontal and vertical simulated fluxes of nitrate and chlorophyll show that only approximately 10% of the upwelled nitrate is utilized by the phytoplankton of the modeled grid box on the northern edge of the cyclone, while approximately 75% is lost horizontally, with the remainder still in the euphotic zone after the 10-day period of the model. Loss of chlorophyll due to sinking is very small in this strong upwelling region of the cyclone. The model is relatively insensitive to variations in the sinking parameterization and the external nitrate and chlorophyll fields but is very sensitive to a reduction of the maximum potential growth rate to half that measured. Given the success of this model in simulating the new production of the selcted upwelling region, other upwelling regions for which measurements or successful models of physical and biological quantities and rates exist could be modeled similarly.

Pribble, J. Raymond↗

NASA NTRSDate not supplied

Creating a Deformation Time Series Utilizing InSAR to Assess Hazards and Detect Volcanic Unrest in Clear Lake Volcanic Field, California

According to the U.S Geological Survey, the Clear Lake Volcanic Field (CLVF) in northern California is at a high threat potential for volcanic hazards. Eruptions leading to increased seismic activity could result in silicic domes, cinder cones, and flows that would be dangerous to the residential areas near the volcanic field. Remotely sensed Earth observations can reveal volcanic processes in the subsurface, which are essential to the timely monitoring of potential volcanic activity. In particular, Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Digital Elevation Model (DEM) data capture relative surface deformation at unprecedented high spatial and temporal resolutions. Leveraging C-SAR and DEMs, we conducted interferometric analysis from January 2016 to December 2023. Our results demonstrate 1) the mean surface displacement velocity of the Clear Lake Volcanic field is measured to undergo 5 to 10-centimeter scale deformation and shows a strong correlation with the surrounding faults, 2) apparent seasonal differences in rates of surface change, and 3) seismic activity associated with the geyser geothermal field has a strong correlation with cumulative surface displacement, with active fault zones having 2 to 5 cm of additional displacement. Results indicate that deformation is linked to deep pressure sources causing stresses on the surficial environment that should be considered in hazard mitigation. This study provides a baseline of historic deformation, aiding hazard analysts in communication efforts and streamlining decision-making for potential risks to region residents.

Ivan Tochimani-Hernandez↗

NASA NTRS2011

Solar Cycle Fine Structure and Surface Rotation from Ca II K-Line Time Series Data

Analysis of three and a half decades of data from the NSO/AFRL/Sac Peak K-line monitoring program yields evidence for four components to the variation: (a) the solar cycle, with considerable fine structure and a quasi-periodicity of 122.4 days; (b) a stochastic process, faster than (a) and largely independent of it, (c) a quasi-periodic signal due to rotational modulation, and of course (d) observational errors (shown to be quite small). Correlation and power spectrum analyses elucidate periodic and aperiodic variation of these chromospheric parameters. Time-frequency analysis is especially useful for extracting information about differential rotation, and in particular elucidates the connection between its behavior and fine structure of the solar cycle on approximately one-year time scales. These results further suggest that similar analyses will be useful at detecting and characterizing differential rotation in stars from stellar light-curves such as those being produced at NASA's Kepler observatory.

Scargle, Jeff↗

NASA NTRS2008

Effective Interpolation of Incomplete Satellite-Derived Leaf-Area Index Time Series for the Continental United States

Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Jasinski, Michael F.↗

NASA NTRS1992

Time series observations of O stars. I - IUE observations of variability in the stellar wind of Zeta Puppis

Stellar wind variability in Zeta Pup (O4 I(n)f) is described based on 31 high-resolution IUE observations secured over 5 1/2 days in 1989 April. Extensive changes are evident in the absorption regions of Si IV 1393.76, 1402.77A and N IV 1718.55A P Cygni profiles. Both lines exhibit similar patterns of variability, which are characterized by the development and subsequent blueward migration, of discrete absorption components. The formation of four discrete features is identified over about 2.2 days of intensive observations, with a recurrence time of about 15 hr. The time scales, velocities, and accelerations of the progressive absorption enhancements are determined. These changes are accompanied by fluctuations of up to about 200 km/s in the maximum observed blue edge velocities in saturated C IV and N V P Cygni profiles.

Prinja, R. K.↗

NASA NTRS2001

A New Method for Nonlinear and Nonstationary Time Series Analysis: The Empirical Mode Decomposition Method

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical nonlinear system models are used to illustrate the roles played by the nonlinear and nonstationary effects in the energy-frequency-time distribution.

Huang, Norden E.↗

NASA NTRS1999

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Huang, Norden E.↗