Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “time resolution data”

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

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

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Coherence lengths of upstream ULF waves - Dual ISEE observations

We have used high time resolution simultaneous magnetic field data from the dual ISEE spacecraft to study the coherence lengths of upstream ULF waves. We examine the cross-correlation between ISEE 1 and 2 observations for different spacecraft separations and determine the coherence lengths for upstream 30-second waves, 3-second waves, and one-Hz waves. We find that the observed coherence lengths are consistent with those estimated from the bandwidth of the spectral peak and that these lengths vary markedly from less than 100 km to over 1 R(E). In order to study all these wave phenomena, a multiple spacecraft mission such as the upcoming ESA Cluster mission would need to be capable of assuming a wide variety of possible separations.

Le, G.↗
NASA NTRS2003

Search for 1-10 Hz Modulations in Coronal Emission with SECIS During the August 11, 1999 Eclipse

Results of the search of the periodic changes of the 530.3 nm line intensity emitted by selected structures of the solar corona in the frequency range 1-10 Hz are presented. A set of 12728 images of the section of the solar corona extending from near the north pole to the south-west were taken simultaneously in the 530.3 nm ('green') line and white-light with the Solar Eclipse Coronal Imaging System (SECIS) during the 143-seconds-long totality of the 1999 August 11 solar eclipse observed in Shabla, Bulgaria. The time resolution of the collected data is better than 0.05-s and the pixel size is approximately 4 arcsecs. Using classical Fourier spectral analysis tools, we investigated temporal changes of the local 530.3 nm coronal line brightness in the frequency range 1-10 Hz of thousands of points within the field of view. The various photometric and instrumental effects have been extensively considered. We did not find any indisputable, statistically significant evidence of periodicities in any of the investigated points (at significance level alpha = 0.05 or better).

Rudawy, P.↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRS1989

Observations of winter polynyas and fractures using NOAA AVHRR TIR images and Nimbus-7 SMMR sea ice concentration charts

The validity of the daily sea ice concentration charts obtained from Nimbus-7 SMMR data is tested against thermal IR NOAA AVHRR-4 images with a 1.1 x 1.1 km resolution. Polynyas and fractures recorded in both data sets are compared for the same times over the same areas. Although the coarser resolution of SMMR data leads to a loss of detail, it is found that the ice concentration charts provide valuable data on openings in the ice. The SMMR data on the location, orientation, and size of polynyas and fractures are shown to be in good agreement with the AVHRR data. Also, the results suggest that the location and orientation of plynyas and fractures are related to the direction of surface winds.

Dey, B.↗
NASA NTRS2008

Combined Impedance Probe and Langmuir Probe Studies of the Low-Latitude E Region

The EQUIS-2 sounding rocket and radar campaign, launched from Kwajalein Atoll in 2004, included a mission to study low-latitude irregularities and electrodynamics, led by NASA GSFC. This mission included two instrumented rockets launched into the nighttime E region (apogee near 120 km), which included comprehensive electrodynamics and neutral density instrumentation. These rockets carried the first of a new generation of impedance probes, that utilize a wide-band drive signal to simultaneously measure the impedance of an antenna in a plasma as a function of frequency from 7 kEIz to 4 MHz. at a rapid cadence. This technique promises to permit true plasma spectroscopy, and resulted in the identification of multiple plasma resonances and accurate measurements of the plasma density, even in the low density nighttime E region. We present analyses of the technique and resulting spectra, and show how these data may be combined with fixed-bias Langmuir Probe data to infer the temperature structure of the E region as well as providing accurate absolute calibrations for the very high time resolution fixed-bias probe data. The data is shown to agree well with data from ionosonde, the ALTAIR radar, and the Peruvian beacon experiment.

Rowland, D. E.↗
NASA NTRS2011

High-Performance Wireless Telemetry

Prior technology for machinery data acquisition used slip rings, FM radio communication, or non-real-time digital communication. Slip rings are often noisy, require much space that may not be available, and require access to the shaft, which may not be possible. FM radio is not accurate or stable, and is limited in the number of channels, often with channel crosstalk, and intermittent as the shaft rotates. Non-real-time digital communication is very popular, but complex, with long development time, and objections from users who need continuous waveforms from many channels. This innovation extends the amount of information conveyed from a rotating machine to a data acquisition system while keeping the development time short and keeping the rotating electronics simple, compact, stable, and rugged. The data are all real time. The product of the number of channels, times the bit resolution, times the update rate, gives a data rate higher than available by older methods. The telemetry system consists of a data-receiving rack that supplies magnetically coupled power to a rotating instrument amplifier ring in the machine being monitored. The ring digitizes the data and magnetically couples the data back to the rack, where it is made available. The transformer is generally a ring positioned around the axis of rotation with one side of the transformer free to rotate and the other side held stationary. The windings are laid in the ring; this gives the data immunity to any rotation that may occur. A medium-frequency sine-wave power source in a rack supplies power through a cable to a rotating ring transformer that passes the power on to a rotating set of electronics. The electronics power a set of up to 40 sensors and provides instrument amplifiers for the sensors. The outputs from the amplifiers are filtered and multiplexed into a serial ADC. The output from the ADC is connected to another rotating ring transformer that conveys the serial data from the rotating section to the stationary section. From there, a cable conveys the serial data to the remote rack, where it is reconditioned to logic level specifications, de-serialized, and converted back to analog. In the rotating electronics are code generators to indicate the beginning of files for data synchronization.

Griebeler, Elmer↗
NASA NTRS2017

Interactive Visualization of High-Dimensional Petascale Ocean Data

We describe an application for interactive visualization of 5 petabytes of time-varying multivariate data from a high-resolution global ocean circulation model. The input data are 10311 hourly (ocean time) time steps of various 2D and 3D fields from a 22-billion point 1/48- degree “lat-lon cap” configuration of the MIT General Circulation Model (MITgcm). We map the global horizontal model domain onto our 128-screen (8x16) tiled display wall to produce a canonical tiling with approximately one MITgcm grid point per display pixel, and using this tiling we encode the entire time series for multiple native and computed scalar quantities at a collection of ocean depths. We reduce disk bandwidth requirements by converting the model’s floating point data to 16-bit fixed point values, and compressing those values with a lossless video encoder, which together allow synchronized playback at 24 time steps per second across all 128 displays. The application allows dynamic assignment of any two encoded tiles to any display, and has multiple interfaces for quickly specifying various orderly arrangements of tiles. All subsequent rendering is done on the fly, with run time control of colormaps, transfer functions, histogram equalization, and labeling. The two data streams on each screen can be rendered independently and combined in various ways, including blending, differencing, horizontal/ vertical wipes, and checkerboarding. The two data streams on any screen can optionally be displayed as a scatterplot in their joint attribute space. All scatterplots and map-view plots from the same x/y location and depth are linked so they all show the current brushable selection. Ocean scientists have used the system, and have found previously unidentified features in the data.

Interactive↗
NASA NTRS2018

Fusion of Multiple Low-Resolution NASA Airborne Snow Observatory (ASO) Lidar Data for Forest Vegetation Structure Characterization

Airborne lidar provides timely updated maps for monitoring forest change at high resolution but it has been little used for that purpose due to the scarcity of long-term time-series over a common area. The NASA Jet Propulsion Laboratory Airborne Snow Observatory (ASO) is a landscape-level monitoring system that provides ongoing multi-year remote sensing measurements over mountainous ecosystems to primary quantify snow volume and dynamics. It collects low-resolution lidar data (~1.5 pt/m2) with a nominal weekly frequency up to 12 times a year with measurements that span 2013-2017 over 12 mountain watersheds across the western US that currently face ecological threads. In this work, we present a method to automatically register ASO weekly low-resolution lidar point clouds in order to calculate spatially consistent datasets (~12 pt/m2) adapted to fine scale forestry studies. We test the method using 12 lidar datasets acquired over the Tuolumne River Basin (Sierra Nevada, California) in the spring and summer of 2014. On average, the ASO lidar system provides accurate measurements in terms of geolocation (0.38m and 0.12m for the horizontal and vertical dimension, respectively) but some datasets are biased up to 1.38m and 0.53m, respectively. Our registration method successfully corrected for systematic bias improving the 3D geometry of forest point clouds.

Painter, Thomas H.↗
NASA NTRS2012

Generating Ground Reference Data for a Global Impervious Surface Survey

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Tilton, James C.↗
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 NTRS1983

MAGSAT investigation of crustal magnetic anomalies in the eastern Indian Ocean

Crustal magnetic anomalies in a region of the eastern Indian Ocean were studied using data from NASA's MAGSAT mission. The investigation region (0 deg to 50 deg South, 75 to 125 deg East) contains several important tectonic features, including the Broken Ridge, Java Trench, Ninetyeast Ridge, and Southeast Indian Ridge. A large positive magnetic anomaly is associated with the Broken Ridge and smaller positive anomalies correlate with the Ninetyeast Ridge and western Australia. Individual profiles of scalar data (computed from vector components) were considered to determine the overall data quality and resolution capability. A set of MAGSAT ""Quiet-Time'' data was used to compute an equivalent source crustal magnetic anomaly map of the study region. Maps of crustal magnetization and magnetic susceptibility were computed from the equivalent source dipoles. Gravity data were used to help interpretation, and a map of the ratio of magnetization to density contrasts was computed using Poisson's relation. The results are consistent with the hypothesis of induced magnetization of a crustal layer having varying thickness and composition.

Sailor, R. V.↗
NASA NTRS1995

Catalog of solar wind events identified from observations by ISTP spacecraft

The ISTP Science Planning and Operations Facility (SPOF), in collaboration with ISTP investigators, is developing a catalog of solar wind events and features. The catalog is primarily based on plasma and magnetic field observations from the WIND and IMP-8 spacecraft. Interplanetary events that may trigger magnetospheric activity are included as well as features of interest for using the solar wind as a plasma laboratory. Catalog coverage begins on September 8, 1992, the start of ISTP science data collection. The catalog is based on Key Parameter data sets (preliminary summary data at approximately 1 min time resolution produced quickly for survey purposes) and as such has limited citability in formal scientific work. Its primary intent is to serve as a reference for identifying candidate periods for further study, such as may be the focus of coordinated data analysis efforts during ISTP and/or IACG Science Campaigns. To facilitate access by members of the ISTP and wider space physics communities, the catalog will be available on the World Wide Web. The contents of the catalog will be described, and samples of catalog information will be presented.

Peredo, M.↗
NASA NTRS1991

Limits on the radius and a possible atmosphere of Charon from its 1980 stellar occultation

Walker's (1980) stellar occultation data for Charon are presently fit by a model which encompasses the possibility of differential refraction by an atmosphere, followed by a sudden occultation behind Charon's limb. The 601.5-km Charon radius lower limit thus obtained may serve as a constraint in models of the mutual event data; while the model fits considered support a Charonian atmosphere of indeterminate composition, time resolution is insufficient for certainty and the data may be interpretable as indications of either a slight extinction near Charon or an entirely unidentified and unassociated effect.

Elliot, J. L.↗
NASA NTRS1985

Magnetospheric impulse response for many levels of geomagnetic activity

The temporal relationship between the solar wind and magnetospheric activity has been studied using 34 intervals of high time resolution IMP 8 solar wind data and the corresponding AL auroral activity index. The median values of the AL index for each interval were utilized to rank the intervals according to geomagnetic activity level. The linear prediction filtering technique was then applied to model magnetospheric response as measured by the AL index to the solar wind input function VB(s). The linear prediction filtering routine produces a filter of time-lagged response coefficients which estimates the most general linear relationship between the chosen input and output parameters of the magnetospheric system. It is found that the filters are composed of two response pulses speaking at time lags of 20 and 60 min. The amplitude of the 60-min pulse is the larger for moderate activity levels, while the 20-min pulse is the larger for strong activity levels. A possible interpretation is that the 20-min pulse represents magnetospheric activity driven directly by solar wind coupling and that the 60-min pulse represents magnetospheric activity driven by the release of energy previously stored in the magnetotail. If this interpretation is correct, the linear filtering results suggest that both the driven and the unloading models of magnetospheric response are important facets of a more comprehensive response model.

Bargatze, L. F.↗
NASA NTRS2008

The 2008 Super Tuesday Tornado Outbreak: Synthetic Dual Doppler Analysis of Contrasting Tornadic Storm Types

During the Super Tuesday Tornado Outbreak on 5-6 February, a significant number of storms passed within about 40 km of WSR-88D radars. This distance, combined with the significant motion vector (from the southwest at 20-25 m per second) of relatively steady storms, is amenable to a synthetic dual Doppler analysis during the times when the storms passed the WSR-88D locations. Nine storms will be analyzed using the SDD technique. The following table provides their general characteristics and nearest approach to the 88D radars. For this data set, storm structure ranges from isolated supercell to QLCS. Each storm will be analyzed for a 40-60 min period during passage by the WSR-88D radar to determine general storm properties. Analysis of high-resolution single Doppler data around the time of passage (plus or minus 30 min), combined with 1-2 SDD analyses, will be used to examine the kinematic structure of low-level circulations (e.g., mesocyclone, downdraft) and the relation to the parent storm. This analysis may provide insights on the fundamental differences between cyclonic circulations in supercell storms and those within QCLS's.

Knupp, Kevin R.↗
NASA NTRS2006

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Ross, Kenton W.↗
NASA NTRS2018

Compensation of Oxygen Transmittance Effects for Proximal Sensing Retrieval of Canopy-Leaving Sun-Induced Chlorophyll Fluorescence

Estimates of Sun-Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O2) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal-sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (1) the sensor height above the vegetated canopy; (2) the SIF retrieval technique used, e.g., Fraunhofer Line Discriminator (FLD) family or Spectral Fitting Methods (SFM); and (3) the instrument's spectral resolution. We demonstrate that for proximal-sensing scenarios compensating for atmospheric effects by simply introducing the O2 transmittance function into the FLD or SFM formulations improves SIF estimations. However, these simplistic corrections still lead to inaccurate SIF estimations due to the multiplication of spectrally convolved atmospheric transfer functions with absorption features. Consequently, a more rigorous oxygen compensation strategy is proposed and assessed by following a classic airborne atmospheric correction scheme adapted to proximal sensing. This approach allows compensating for the O2 absorption effects and, at the same time, convolving the high spectral resolution data according to the corresponding Instrumental Spectral Response Function (ISRF) through the use of an atmospheric radiative transfer model. Finally, due to the key role of O2 absorption on the evaluated proximal-sensing SIF retrieval strategies, its dependency on surface pressure (p) and air temperature (T) was also assessed. we combined simulated spectral data with p and T measurements obtained for a one-year period in the Hyytiala Forestry Field Station in Finland. Of importance hereby is that seasonal dynamics in terms of T and p, if not appropriately considered as part of the retrieval strategy, can result in erroneous SIF seasonal trends that mimic those of known dynamics for temperature-dependent physiological responses of vegetation.

"sun–induced chlorophyll fluorescence (SIF); pro↗
NASA NTRS1994

Searches for millisecond pulsations in low-mass X-ray binaries, 2

Coherent millisecond X-ray pulsations are expected from low-mass X-ray binaries (LMXBs), but remain undetected. Using the single-parameter Quadratic Coherence Recovery Technique (QCRT) to correct for unknown binary orbit motion, we have performed Fourier transform searches for coherent oscillations in all long, continuous segments of data obtained at 1 ms time resolution during Ginga observations of LMXB. We have searched the six known Z sources (GX 5-1, Cyg X-2, Sco X-1, GX 17+2, GX 340+0, and GX 349+2), seven of the 14 known atoll sources (GX 3+1. GX 9+1, GX 9+9, 1728-33. 1820-30, 1636-53 and 1608-52), the 'peculiar' source Cir X-1, and the high-mass binary Cyg X-3. We find no evidence for coherent pulsations in any of these sources, with 99% confidence limits on the pulsed fraction between 0.3% and 5.0% at frequencies below the Nyquist frequency of 512 Hz. A key assumption made in determining upper limits in previous searches is shown to be incorrect. We provide a recipe for correctly setting upper limits and detection thresholds. Finally we discuss and apply two strategies to improve sensitivity by utilizing multiple, independent, continuous segments of data with comparable count rates.

Vaughan, B. A.↗