Results for “data quality analysis” — Page 50

NASA NTRS1985

Observations of low-degree P-mode oscillations in 1984

Analysis of Stanford differential velocity observations has been extended through the 1984 observing season. Excellent quality observations were obtained in 1984 on 38 days in a 49 day interval from June 20th through August 7th. The power spectrum of this data has been examined and improved frequency determinations have been made for p-modes of degree 2 through 5 and order 5 through 34. Of special interest are the modes of the lower orders, n ranging from 5 to 10, which have not been identified previously.

Henning, H. M.↗

NASA NTRS1986

Observations of low-degree p-mode oscillations in 1984

Analysis of Stanford differential velocity observations has been extended through the 1984 observing season. Excellent quality observations were obtained in 1984 on 38 days in a 49 day interval from June 20th through August 7th. The power spectrum of this data has been examined and improved frequency determinations have been made for p-modes of degree 2 through 5 and order 5 through 34. Of special interest are the modes of the lower orders, n ranging from 5 to 10, which have not been identified previously.

Henning, Harald M.↗

NASA NTRS1988

Parallel discrete-event simulation of FCFS stochastic queueing networks

Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

Nicol, David M.↗

NASA NTRS2001

Ab Initio and Improved Empirical Potentials for the Calculation of the Anharmonic Vibrational States and Intramolecular Mode Coupling of N-Methylacetamide

The second-order Moller-Plesset ab initio electronic structure method is used to compute points for the anharmonic mode-coupled potential energy surface of N-methylacetamide (NMA) in the trans(sub ct) configuration, including all degrees of freedom. The vibrational states and the spectroscopy are directly computed from this potential surface using the Correlation Corrected Vibrational Self-Consistent Field (CC-VSCF) method. The results are compared with CC-VSCF calculations using both the standard and improved empirical Amber-like force fields and available low temperature experimental matrix data. Analysis of our calculated spectroscopic results show that: (1) The excellent agreement between the ab initio CC-VSCF calculated frequencies and the experimental data suggest that the computed anharmonic potentials for N-methylacetamide are of a very high quality; (2) For most transitions, the vibrational frequencies obtained from the ab initio CC-VSCF method are superior to those obtained using the empirical CC-VSCF methods, when compared with experimental data. However, the improved empirical force field yields better agreement with the experimental frequencies as compared with a standard AMBER-type force field; (3) The empirical force field in particular overestimates anharmonic couplings for the amide-2 mode, the methyl asymmetric bending modes, the out-of-plane methyl bending modes, and the methyl distortions; (4) Disagreement between the ab initio and empirical anharmonic couplings is greater than the disagreement between the frequencies, and thus the anharmonic part of the empirical potential seems to be less accurate than the harmonic contribution;and (5) Both the empirical and ab initio CC-VSCF calculations predict a negligible anharmonic coupling between the amide-1 and other internal modes. The implication of this is that the intramolecular energy flow between the amide-1 and the other internal modes may be smaller than anticipated. These results may have important implications for the anharmonic force fields of peptides, for which N-methylacetamide is a model.

Gregurick, Susan K.↗

NASA NTRS2011

AIRS Impact on Analysis and Forecast of an Extreme Rainfall Event (Indus River Valley 2010) with a Global Data Assimilation and Forecast System

A set of data assimilation and forecast experiments are performed with the NASA Global data assimilation and forecast system GEOS-5, to compare the impact of different approaches towards assimilation of Advanced Infrared Spectrometer (AIRS) data on the precipitation analysis and forecast skill. The event chosen is an extreme rainfall episode which occurred in late July 11 2010 in Pakistan, causing massive floods along the Indus River Valley. Results show that the assimilation of quality-controlled AIRS temperature retrievals obtained under partly cloudy conditions produce better precipitation analyses, and substantially better 7-day forecasts, than assimilation of clear-sky radiances. The improvement of precipitation forecast skill up to 7 day is very significant in the tropics, and is caused by an improved representation, attributed to cloudy retrieval assimilation, of two contributing mechanisms: the low-level moisture advection, and the concentration of moisture over the area in the days preceding the precipitation peak.

Reale, O.↗

NASA NTRS2007

Spatial Correlation and Coherence of Boundary Layer Winds Near Cape Canaveral Florida

The spatial correlation and coherence of winds over separation distances from 8.5 to 31 km based on central Florida data from November 1999 through August 2001 are presented. The winds at altitudes from 500 to 3000 m were measured using a network of five radar wind profilers. The goal was to determine the extent to which the profilers may be considered independent data sources. Quality controlled profiles were produced every 15 minutes for up to sixty gates, each representing 101 m in altitude over the range from 130 m to 6089 m. Five levels, each containing three consecutive gates, were selected for analysis. These levels covered the range from 433 to 3059 m. The results show that the profilers are independent for features having time scales of less than one hour in the winter or two hours in the summer. This does not depend significantly on height. Because the size of the network coincides with the "spectral gap" in the boundary layer, the result also does not depend on the spacing of the profilers within the network.

Merceret, Francis J.↗

NASA NTRS2014

Discovery of a Similar to 5 Day Characteristic Timescale in the Kepler Power Spectrum of Zw 229-15

We present time series analyses of the full Kepler dataset of Zw 229− 15. This Kepler light curve- with a baseline greater than three years, composed of virtually continuous, evenly sampled 30-minute measurements - is unprecedented in its quality and precision. We utilize two methods of power spectral analysis to investigate the optical variability and search for evidence of a bend frequency associated with a characteristic optical variability timescale. Each method yields similar results. The first interpolates across data gaps to use the standard Fourier periodogram. The second, using the CARMA-based time-domain modeling technique of Kelly et al., does not need evenly-sampled data. Both methods find excess power at high frequencies that may be due to Kepler instrumental effects. More importantly both also show strong bends (delta alpha is approx. 2) at timescales of approx. 5 days, a feature similar to those seen in the X-ray PSDs of AGN but never before in the optical. This observed approx. 5 day timescale may be associated with one of several physical processes potentially responsible for the variability. A plausible association could be made with light -crossing, dynamical or thermal timescales, depending on the assumed value of the accretion disk size and on unobserved disk parameters such as alpha and H¬R. This timescale is not consistent with the viscous timescale, which would be years in a approx. 10(exp7) solar mass AGN such as Zw 229− 15. However there must be a second bend on long (& 1 year) timescales, and that feature could be associated with the viscous timescale.

timescale↗

NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

NASA NTRSDate not supplied

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

NASA NTRS2024

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

NASA NTRS1983

An analysis of new techniqes for radiometric correction of LANDSAT-4 Thematic Mapper images

The utility of methods for generating TM RLUTS which can improve the quality of the resultant images was investigated. The TM-CCT-ADDS tape was changed to account for a different collection window for the calibration data. Several scenes of Terrebonne Bay, Louisiana and the Grand Bahamas were analyzed to evaluate the radiometric corrections operationally applied to the image data and to investigate several techniques for reducing striping in the images. Printer plots for the TM shutter data were produced and detector statistics were compiled and plotted. These statistics included various combinations of the average shutter counts for each scan before and after DC restore for forward and reverse scans. Results show that striping is caused by the detectors becoming saturated when they view a bright cloud and depress the DC restore level.

Kogut, J.↗

NASA NTRS1989

Analysis of coordinated observations of a giant stellar flare

Multi-wavelength observations of a giant flare on the star AD Leo were obtained with the 2.1 m and 0.9 m telescopes at McDonald Observatory and the International Ultraviolet Explorer satellite. The quality, spectral coverage, and time resolution of the data represented a major improvement over any published stellar flare data. Two theoretical, quantitative flare models were developed. Combining the models, the chromospheric emission model predictions in the hydrogen Balmer lines, Da II K, Mg II h + k and the optical continuum were compared to the observations, with the result that much of the gradual phase flare emission could be produced by the x ray and conductive heated atmospheres. The models lend insight into the impulsive phase flare emission, but do not reproduce it. Soft x ray and conductive heating of the chromosphere is a natural consequence of the coronal temperatures that have been observed during the gradual phase of flares on the sun and on M dwarf stars. The improved flare observations and quantitative flare models presented here show that these heating mechanisms can produce atmospheres whose emission matches many of the observed stellar flare features.

Lambert, David L.↗

NASA NTRS2018

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.

remote sensing data↗

NASA NTRS2009

International Space Station Air Quality Assessed According to Toxicologically-Grouped Compounds

Scores of compounds are found in the International Space Station (ISS) atmospheric samples that are returned to the Johnson Space Center Toxicology Laboratory for analysis. Spacecraft Maximum Allowable Concentrations (SMACs) are set with the view that each compound is present as if there were no other compounds present. In order to apply SMACs to the interpretation of the analytical data, the toxicologist must employ some method of combining the potential effects of the aggregate of compounds found in the atmospheric samples. The simplest approach is to assume that each quantifiable compound has the potential for some effect in proportion to the applicable SMAC, and then add all the proportions. This simple paradigm disregards the fact that most compounds have potential to adversely affect only a few physiological systems, and their effects would be independent rather than additive. An improved approach to dealing with exposure to mixtures is to add the proportions only for compounds that adversely affect the same physiological system. For example, toxicants that cause respiratory irritation are separated from those that cause neurotoxicity or cardio-toxicity. Herein we analyze ISS air quality data according to toxicological groups with a view that this could be used for understanding any crew symptoms occurring at the time of the sample. In addition, this approach could be useful in post-flight longitudinal surveys where the flight surgeon may need to identify post-flight, follow-up medical studies because of on-orbit exposures that target specific physiological systems.

James, John T.↗

NASA NTRS2010

International Space Station Air Quality Assessed According to Toxicologically-Grouped Compounds

Scores of compounds are found in the International Space Station (ISS) atmospheric samples that are returned to the Johnson Space Center Toxicology Laboratory for analysis. Spacecraft Maximum Allowable Concentrations (SMACs) are set with the view that each compound is present as if there were no other compounds present. In order to apply SMACs to the interpretation of the analytical data, the toxicologist must employ some method of combining the potential effects of the aggregate of compounds found in the atmospheric samples. The simplest approach is to assume that each quantifiable compound has the potential for some effect in proportion to the applicable SMAC, and then add all the proportions. This simple paradigm disregards the fact that most compounds have potential to adversely affect only a few physiological systems, and their effects would be independent rather than additive. An improved approach to dealing with exposure to mixtures is to add the proportions only for compounds that adversely affect the same physiological system. For example, toxicants that cause respiratory irritation are separated from those that cause neurotoxicity or cardio-toxicity. Herein we analyze ISS air quality data according to toxicological groups with a view that this could be used for understanding any crew symptoms occurring at the time of the sample acquisition. In addition, this approach could be useful in post-flight longitudinal surveys where the flight surgeon may need to identify post-flight, follow-up medical studies because of on-orbit exposures that target specific physiological systems.

James, John T.↗

NASA NTRS1991

Geodynamics branch data base for main magnetic field analysis

The data sets used in geomagnetic field modeling at GSFC are described. Data are measured and obtained from a variety of information and sources. For clarity, data sets from different sources are categorized and processed separately. The data base is composed of magnetic observatory data, surface data, high quality aeromagnetic, high quality total intensity marine data, satellite data, and repeat data. These individual data categories are described in detail in a series of notebooks in the Geodynamics Branch, GSFC. This catalog reviews the original data sets, the processing history, and the final data sets available for each individual category of the data base and is to be used as a reference manual for the notebooks. Each data type used in geomagnetic field modeling has varying levels of complexity requiring specialized processing routines for satellite and observatory data and two general routines for processing aeromagnetic, marine, land survey, and repeat data.

Langel, Robert A.↗

NASA NTRS1978

The ATLAS integrated structural analysis and design software system

The ATLAS system provides an extensive set of integrated technical computer-program modules for the analysis and design of general structural configurations, as well as capabilities that are particularly suited for the aeroelastic design of flight vehicles. The system is based on the stiffness formulation of the finite element structural analysis method and can be executed in batch and interactive computing environments on CDC 6600/CYBER computers. Problem-definition input data are written in an engineering-oriented language using a free field format. Input-data default values, generation options, and data quality checks provided by the preprocessors minimize the amount of data and flowtime for problem definition/verfication. Postprocessors allow selected input and calculated data to be extracted, manipulated, and displayed via on-line and off-line prints or plots for monitoring and verifying problem solutions. The sequence and mode of execution of selected program modules are controlled by a common user-oriented language.

Dreisbach, R. L.↗

NASA NTRS1981

Measurement of HO2 and other trace gases in the stratosphere using a high resolution far infrared spectrometer at 28 Km

A progress report and data analyses from the December 1980 flight are presented. The following areas are covered: (1) computer analysis of the flight spectra to obtain phase corrected, normalized sums of spectra for retrieval of atmospheric profiles; (2) study of atmospheric HF, HCl, and H2O; (3) stratospheric H2O2 and HOCl; (4) laboratory spectroscopy of HOCl; and (5) design study of a new balloon gondola. The majority of the flight data were taken in the low background mode, i.e., one input to the spectrometer looking at the sky and the other looking at a LN2 temperature blackbody. An analysis of HF stratospheric measurements was undertaken in conjunction with the HF analysis. High quality spectra showing the HOCl q-branches under optically thin conditions were also obtained.

Traub, W. A.↗