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NASA NTRS2016

Time Series Explorer: Bayesian Blocks with Generalized Profiles and in Higher Dimensions

The Time Series Explorer (TSE) is a project aimed at provided new and advanced time series analysis algorithms in two forms: a tool kit and an automated pipeline applying selected tools in machine learning settings. I will present a sketch of TSE with emphasis on time-domain modeling in general and recent improvements of the Bayesian Block (BB) algorithm in particular. This includes generalizing the shape of the elementary blocks from the current constant-rate model to general shapes, such as two-sided exponentials. Related topics will include extension of BB to higher dimensions and a novel way to detect and characterize short time-scale bursts in time-tagged event data. The Fermi Gamma Ray Space Telescope light curve for the Crab Nebula will be used as an example for all of the algorithms discussed. This work is in collaboration with Tom Loredo.

Bayesian Block (BB) algorithm↗

NASA NTRS2019

MARGInS Model-Based Analysis of Realizable Goals in Systems

The high complexity of modern aircraft and spacecraft requires elaborate Verification and Validation (V&V) approaches to make sure that such complex systems work properly and reliably. MARGInS is a framework for the analysis, understanding, and prediction of the behavior of a complex, hybrid system. MARGInS contains a set of machine learning and statistical algorithms for multivariate clustering, treatment learning, critical factor determination, time-series analysis, event prediction, and safety-boundary detection and characterization. The framework supports system testing and can be configured to find novel features in test suites, determine classes of behavior, propose new experiments that can efficiently explore and characterize the boundaries between classes of system behavior, and to create visualizations and reports.

He, Yuning↗

NASA NTRS1985

A perspective on the evidence for periodic cometary impacts on earth

Recent suggestions of periodic cometary showers coincident with mass extinctions have prompted a review of the terrestrial cratering record. From the point of view of completeness of search and crater retention, the record used to argue for statistical periodicities is incomplete and may not be representative. Estimates of crater ages are of variable accuracy and precision and, in some cases, different dating methods yield discordant results. It is possible to define through time-series analysis a number of periodicities of different magnitude (about 29, 21, 18.5, and 13.5 m.y.) and phase, depending on which craters are considered the most representative sample of the record. Arguing against periodic cometary showers is the observation that estimates of the average cratering rate in recent time and observations on Apollo bodies are equivalent. In addition, siderophile element data from impact melt rocks suggest a variety of projectile types were responsible for relatively large terrestrial craters. Given these observations, it is concluded that statements regarding periodic cometray showers are not categorical and require evidence beyond arguments based on time-series analyses of an incomplete cratering record.

Grieve, R. A. F.↗

NASA NTRS2019

Global Validation of Columnar Water Vapor Derived from EOS MODIS-MAIAC Algorithm Against the Ground-Based AERONET Observations

The water vapor is a relevant greenhouse gas in the Earth's climate system, and satellite products become one of the most effective way to characterize and monitor the columnar water vapor (CWV) content at global scale. Recently, a new product (MCD19) was released as part of MODIS (Moderate Resolution Imaging Spectroradiometer) Collection 6 (C6). This operational product from the Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm includes a high 1-kilometer resolution CWV retrievals. This study presents the first global validation of MAIAC C6 CWV obtained from MODIS MCD19A2 product. This evaluation was performed using Aerosol Robotic Network (AERONET) observations at 265 sites (2000-2017). Overall, the results show a good agreement between MAIAC/AERONET CWV retrievals, with correlation coefficient higher than 0.95 and RMS (Root Mean Square) error lower than 0.250 centimeters. The binned error analysis revealed an underestimation (approximately 10 percent) of Aqua CWV retrievals with negative bias for CWV higher than 3.0 centimeters. In contrast, Terra CWV retrievals show a slope of regression close to unity and a low mean bias of 0.075 centimeters. While the accuracy is relatively similar between 1.0 and 5.0 centimeters for both sensor products, Terra dataset is more reliable for applications in humid tropical areas (less than 5.0 centimeters). The expected error was defined as plus or minus 15 percent, with less than 68 percent of retrievals falling within this envelope. However, the accuracy is regionally dependent, and lower error should be expected in some regions, such as South America and Oceania. Since MODIS instruments have exceeded their design lifetime, time series analysis was also presented for both sensor products. The temporal analysis revealed a systematic offset of global average between Terra and Aqua CWV records. We also found an upward trend (approximately 0.2 centimeters per decade) in Terra CWV retrievals, while Aqua CWV retrievals remain stable over time. The sensor degradation influences the ability to detect climate signals, and this study indicates the need for revisiting calibration of the MODIS bands 17-19, mainly for Terra instrument, to assure the quality of the MODIS water vapor product. Finally, this study presents a comprehensive validation analysis of MAIAC CWV over land, raising the understanding of its overall quality.

MAIAC↗

NASA NTRS2004

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Srivastava, Ashok↗

NASA NTRS2012

Using NASA's Giovanni System to Simulate Time-Series Stations in the Outflow Region of California's Eel River

Oceanographic time-series stations provide vital data for the monitoring of oceanic processes, particularly those associated with trends over time and interannual variability. There are likely numerous locations where the establishment of a time-series station would be desirable, but for reasons of funding or logistics, such establishment may not be feasible. An alternative to an operational time-series station is monitoring of sites via remote sensing. In this study, the NASA Giovanni data system is employed to simulate the establishment of two time-series stations near the outflow region of California s Eel River, which carries a high sediment load. Previous time-series analysis of this location (Acker et al. 2009) indicated that remotely-sensed chl a exhibits a statistically significant increasing trend during summer (low flow) months, but no apparent trend during winter (high flow) months. Examination of several newly-available ocean data parameters in Giovanni, including 8-day resolution data, demonstrates the differences in ocean parameter trends at the two locations compared to regionally-averaged time-series. The hypothesis that the increased summer chl a values are related to increasing SST is evaluated, and the signature of the Eel River plume is defined with ocean optical parameters.

Acker, James G.↗

NASA NTRS2005

Regression Analysis of Long-term Profile Ozone Data Set from BUV Instruments

We have produced a profile merged ozone data set (MOD) based on the SBUV/SBUV2 series of nadir-viewing satellite backscatter instruments, covering the period from November 1978 - December 2003. In 2004, data from the Nimbus 7 SBUV and NOAA 9,11, and 16 SBUV/2 instruments were reprocessed using the Version 8 (V8) algorithm and most recent calibrations. More recently, data from the Nimbus 4 BUV instrument, which operated from 1970 - 1977, were also reprocessed using the V8 algorithm. As part of the V8 profile calibration, the Nimbus 7 and NOAA 9 (1993-1997 only) instrument calibrations have been adjusted to match the NOAA 11 calibration, which was established from comparisons with SSBUV shuttle flight data. Given the level of agreement between the data sets, we simply average the ozone values during periods of instrument overlap to produce the MOD profile data set. We use statistical time-series analysis of the MOD profile data set (1978-2003) to estimate the change in profile ozone due to changing stratospheric chlorine levels. The Nimbus 4 BUV data offer an opportunity to test the physical properties of our statistical model. We extrapolate our statistical model fit backwards in time and compare to the Nimbus 4 data. We compare the statistics of the residuals from the fit for the Nimbus 4 period to those obtained from the 1978-2003 period over which the statistical model coefficients were estimated.

Frith, Stacey↗

NASA NTRS2017

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗

NASA NTRS2004

The Validation of Version 8 Ozone Profiles: Is SBUV Ready for Prime Time?

Ozone profile data are now available from a series of BUV instruments - SBUV on Nimbus 7 and SBW/2 instruments on NOAA 9, NOAA 11, and NOAA 16. The data have been processed through the new version 8 algorithm, which is designed to be more accurate and, more importantly, to reduce the influence of the a priori on ozone trends. As a part of the version 8 reprocessing we have attempted to apply a consistent calibration to the individual instruments so that their data records can be used together in a time series analysis. Validation consists of examining not only the mean difference from external datasets (i.e trends) but also consistency in the interannual variability of the data. Here we validate the v8 BUV data through comparison with ECC sondes, lidar and microwave measurements, and with SAGE II and HALOE satellite data records. We find that individual profiles generally agree with external data sets within +/-10% between 30 hPa and 1 hPa (approx. 24 - 50 km) and frequently agree within +/-5%. The interannual variability of the BUV ozone time series agrees well with that of SAGE II . On the average, different B W instruments usually agree within +/-5% with each other, though the relative error increases near the ends of the Nimbus 7 and NOAA 16 data records as a result of instrument problems. The combined v8 BUV data sets cover the 1979-2003 time period giving daily global coverage of the ozone vertical distribution to better accuracy than has ever been possible before.

McPeters, R. D.↗

NASA NTRS2018

PYSAT: Python Satellite Data Analysis Toolkit

A common problem in space science data analysis is combining complementary data sources that are provided and analyzed in different formats and programming languages. The Python Satellite Data Analysis Toolkit (pysat) addresses this issue by providing an open source toolkit that implements the general process of space science data analysis, from beginning to end, in an instrumentindependent manner. This toolkit uses an Instrument object that enables systematic analysis of science data from a variety of platforms within a single interface. Basic functions such as downloading, loading, and cleaning are included for all supported instruments. Common analysis routines are also included, which are instrument and data source independent. A nanokernel is used to provide instrument independence, it is attached to the Instrument object and mediates the systematic and arbitrary modification of loaded data. Pysat uses the nanokernel to improve the rigor of time series analysis, support onthefly orbit determination, and cleanly span file breaks. Pysat's functions and higherlevel scientific analysis features are validated through the use of unit testing. Further adoption by the community provides a set of scientific results produced by a common core, constituting a distributed heritage that supports the validity of the underlying processing and scientific output. These features are used to demonstrate consistency between derived electron density profiles and measured ion drifts, particularly downward ion drifts in the afternoon hours during extreme solar minimum. Pysat builds upon open source Python software that is freely available and encourages communitydriven development.

Stoneback, R.A.↗

NASA NTRS1995

Heart rate and respiratory rhythm dynamics on ascent to high altitude

OBJECTIVE--To investigate the alterations in autonomic control of heart rate at high altitude and to test the hypothesis that hypoxaemic stress during exposure to high altitude induces non-linear, periodic heart rate oscillations, similar to those seen in heart failure and the sleep apnoea syndrome. SUBJECTS--11 healthy subjects aged 24-64. MAIN OUTCOME MEASURES--24 hour ambulatory electrocardiogram records obtained at baseline (1524 m) and at 4700 m. Simultaneous heart rate and respiratory dynamics during 2.5 hours of sleep by fast Fourier transform analysis of beat to beat heart rate and of an electrocardiographically derived respiration signal. RESULTS--All subjects had resting hypoxaemia at high altitude, with an average oxyhaemoglobin saturation of 81% (5%). There was no significant change in mean heart rate, but low frequency (0.01-0.05 Hz) spectral power was increased (P < 0.01) at high altitude. Time series analysis showed a complex range of non-linear sinus rhythm dynamics. Striking low frequency (0.04-0.06 Hz) heart rate oscillations were observed during sleep in eight subjects at high altitude. Analysis of the electrocardiographically derived respiration signal indicated that these heart rate oscillations correlated with low frequency respiratory oscillations. CONCLUSIONS--These data suggest (a) that increased low frequency power during high altitude exposure is not simply attributable to increased sympathetic modulation of heart rate, but relates to distinctive cardiopulmonary oscillations at approximately 0.05 Hz and (b) that the emergence of periodic heart rate oscillations at high altitude is consistent with an unstable cardiopulmonary control system that may develop on acute exposure to hypoxaemic stress.

Non-NASA Center↗

NASA NTRS1995

The IUE Mega Campaign. Modulated Structure in the Wind of HD 64760 (B0.5 Ib)

We highlight systematic variability in the stellar wind of the early B type supergiant, HD 64760, whose UV line profiles were monitored for almost 16 days in 1995 January as part of the IUE 'MEGA Campaign.' The extensive coverage reveals a pattern of rapidly evolving discrete optical depth changes which typically migrate from approx. - 200 km/s to approx. -1500 km/s in less than 12 hr. These features coexist with more slowly evolving structures lasting several days. Time-series analysis of the Si(IV), Si(III), and N(V) profile variations presents a clear 1.2 day periodicity, which is a quarter of the estimated maximum rotation period of HD 64760. The line profile changes are consistent with an interpretation in terms of a set of corotating wind features which occult the stellar disk at least 3 times during the observing run. These data are combined with UV observations collected in 1993 March to argue in favor of rotationally modulated wind variations in HD 64760. The basic result of very regular, large-scale optical depth variations points to a 'clock' whose origin is on the stellar surface, rather than a mechanism that is entirely intrinsic to the stellar wind.

Prinja, Raman K.↗

NASA NTRS2022

Helheim Glacier Ice Velocity Variability Responds to Runoff and Terminus Position, but at Different Timescales

The Greenland Ice Sheet discharges ice to the ocean through hundreds of outlet glaciers. Recent acceleration of Greenland outlet glaciers has been linked to both oceanic and atmospheric drivers. Here, we leverage temporally dense observations, regional climate model output, and newly developed time series analysis tools to assess the most important forcings causing ice flow variability at one of the largest Greenland outlet glaciers, Helheim Glacier, from 2009 to 2017. We find that ice speed correlates most strongly with catchment-integrated runoff at seasonal to interannual scales, while multi-annual flow variability correlates most strongly with multi-annual terminus variability. The disparate time scales and the influence of subglacial topography on Helheim Glacier’s dynamics highlight different regimes that can inform modeling and forecasting of its future. Notably, our results suggest that the recent terminus history observed at Helheim is a response to, rather than the cause of, upstream changes.

Cryospheric science↗

NASA NTRS2016

Assessing Spontaneous Combustion Instability with Recurrence Quantification Analysis

Spontaneous instabilities can pose a significant challenge to verification of combustion stability, and characterizing its onset is an important avenue of improvement for stability assessments of liquid propellant rocket engines. Recurrence Quantification Analysis (RQA) is used here to explore nonlinear combustion dynamics that might give insight into instability. Multiple types of patterns representative of different dynamical states are identified within fluctuating chamber pressure data, and markers for impending instability are found. A class of metrics which describe these patterns is also calculated. RQA metrics are compared with and interpreted against another metric from nonlinear time series analysis, the Hurst exponent, to help better distinguish between stable and unstable operation.

Eberhart, Chad J.↗

NASA NTRS1996

Transneuronal pathways to the vestibulocerebellum

The alpha-herpes virus (pseudorabies, PRV) was used to observe central nervous system (CNS) pathways associated with the vestibulocerebellar system. Retrograde transneuronal migration of alpha-herpes virions from specific lobules of the gerbil and rat vestibulo-cerebellar cortex was detected immunohistochemically. Using a time series analysis, progression of infection along polyneuronal cerebellar afferent pathways was examined. Pressure injections of > 20 nanoliters of a 10(8) plaque forming units (pfu) per ml solution of virus were sufficient to initiate an infectious locus which resulted in labeled neurons in the inferior olivary subnuclei, vestibular nuclei, and their afferent cell groups in a progressive temporal fashion and in growing complexity with increasing incubation time. We show that climbing fibers and some other cerebellar afferent fibers transported the virus retrogradely from the cerebellum within 24 hours. One to three days after cerebellar infection discrete cell groups were labeled and appropriate laterality within crossed projections was preserved. Subsequent nuclei labeled with PRV after infection of the flocculus/paraflocculus, or nodulus/uvula, included the following: vestibular (e.g., z) and inferior olivary nuclei (e.g., dorsal cap), accessory oculomotor (e.g., Darkschewitsch n.) and accessory optic related nuclei, (e.g., the nucleus of the optic tract, and the medial terminal nucleus); noradrenergic, raphe, and reticular cell groups (e.g., locus coeruleus, dorsal raphe, raphe pontis, and the lateral reticular tract); other vestibulocerebellum sites, the periaqueductal gray, substantia nigra, hippocampus, thalamus and hypothalamus, amygdala, septal nuclei, and the frontal, cingulate, entorhinal, perirhinal, and insular cortices. However, there were differences in the resulting labeling between infection in either region. Double-labeling experiments revealed that vestibular efferent neurons are located adjacent to, but are not included among, flocculus-projecting supragenual neurons. PRV transport from the vestibular labyrinth and cervical muscles also resulted in CNS infections. Virus propagation in situ provides specific connectivity information based on the functional transport across synapses. The findings support and extend anatomical data regarding vestibulo-olivo-cerebellar pathways.

NASA Discipline Neuroscience↗

NASA NTRS2018

Vegetation Change Detection in Southern California Solar Energy Developments

Change detection from satellite sensor vegetation indices (VIs) presents an opportunity to monitor trends and disturbances at the regional scale for southern California's Mojave and Lower Colorado Deserts. Renewable energy sites are being constructed in this region on public lands under the Bureau of Land Management (BLM). We have developed a framework for VI change detection over the past two decades, with initial focus on three sites, Joshua Tree National Park, Mojave National Preserve, and a proximal group of Development Focus Areas (DFAs), for comparison between protected and development-targeted lands. Three Terra MODIS VIs (normalized difference [NDVI], enhanced [EVI], soil-adjusted [SAVI]) were evaluated in the Breaks for Additive Season and Trend (BFAST) setting for the regional MODIS 250-m resolution grid to estimate significant time series shifts (breakpoints) from February 2000 to May 2018. All three VIs tended to detect the maximum number of breakpoints at a grid location, but cross-correlations with precipitation and comparison with timing of wildfire burns near the study sites for breakpoint density (proportion of area with a breakpoint) showed that NDVI had the strongest response to these major disturbances, supporting its use for subsequent analysis. Time series of NDVI breakpoint change densities for individual solar energy sites did not have a consistent vegetation response following construction. Bootstrapping showed that the DFAs had significantly larger kurtosis and variance in the positive NDVI breakpoint distribution than did the protected sites, but there was no significant difference in the negative distribution for all three sites. The inconsistent post-construction NDVI signal and the large number of breakpoints overall suggested that the largest changes in vegetation cover density were tied to seasonal precipitation amounts. The distributional results indicated that existing site-specific conditions were the main control on VI responses, given the history of human disturbances in the DFAs. Although the results do not support persistent VI disturbances resulting from recent solar energy development, continued monitoring and examination of other ecological variables and surface temperatures will be vital to the long-term protection of this desert environment.

Potter, Christopher S.↗

NASA NTRS1989

Probing solar system objects at infrared wavelengths

The instruments, techniques, and analysis methods employed in IR observations of solar-system objects are discussed and illustrated with sample data. Particular attention is given to (1) high-resolution (Doppler-limited) spectra of H2O in Comet Halley and Comet Wilson (1986l), obtained with the NASA Kuiper Airborne Observatory in 1985-1986, and (2) scanning observations of Jovian thermal emission, obtained with the NASA IRTF in 1987 and subjected to detailed time-series analysis to investigate atmospheric motion. The data are presented in spectra, energy-level diagrams, maps, and graphs and briefly characterized.

Mumma, M. J.↗

NASA NTRS1991

Detection of target distance in the presence of an interfering reflection using a frequency-stepped double side-band suppressed carrier microwave radar system

A technique for detecting the distance to a highly reflective target in the presence of an interesting reflection using a frequency-stepped double-sideband suppressed carrier (DSBSC) microwave-millimeter-wave radar system is analytically derived. The main result of the analysis shows that the measured group delays produced by the DSBSC system possess a periodicity inversely proportional to the difference between the time delays to the target and interferer, independent of the signal-to-interference ratio (SIR). Simulation results are presented in the context of electron plasma density range estimation using a block diagram communications CAD tool. A unique and accurate plasma model is introduced. A high-resolution spectral estimation technique based on an autoregressive time series analysis is applied to the measured group delays, and it is shown that accurate target distance estimates may be obtained, independent of SIR.

Ybarra, Gary A.↗