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NASA NTRS1990

Loop current eddy shedding estimated using Geosat altimeter data

A method for extracting periodic signals from altimeter data is applied in the Gulf of Mexico using data from the first two years of the Geosat Exact Repeat Mission. The least squares fitting of selected frequencies of sine and cosine functions to the time series of sea surface height at each point of the Geosat ground track is used to estimate the dominant frequency in the gulf for this time period. Optimal interpolation of the sine and cosine coefficients at the dominant frequency to a uniformly spaced grid allows reconstruction of the time series in the gulf and shows eddies shedding from the Loop Current with a period of approximately 10.5 months, consistent with shedding periods determined from numerical models and analysis of satellite infrared data. This technique is a novel method for investigation of periodic signals in Geosat altimetry and is not severely affected by the data outages present in the time series.

Jacobs, Gregg A.↗

NASA NTRS1995

MSATT: Mars Surface and Atmosphere Through Time

The papers published here are based on a workshop entitled "Mars: Past, Present, and Future: Results from the MSATT Program." MSATT (Mars Surface and Atmosphere Through Time) was the last of the Mars data analysis programs and functioned mainly through a series of focused workshops, the final one being held at the Lunar and Planetary Institute in Houston, Texas on November 15-17, 1993. The program began and ended with workshops that brought the entire MSATT community together. Here you will find papers that address the geology, mineralogy, and meteorology of Mars in an effort to assess how the surface and atmosphere of this fascinating planet have evolved over time. Could early Mars have been warmed by a brighter young sun instead of a massive greenhouse effect? Were glaciers and hydrological cycles part of Mars' relatively recent past, or was aeolian activity responsible for the putative glacial features? Do the SNCs come from a single source region, or is more than one site involved? And what really are the properties of Martian soils and what do they tell us about the weathering environment? Clearly, these are difficult questions, but progress toward answers can be found in this issue. Also contained in this issue are a mix of theoretical and observational papers that deal with the general circulation of the current atmosphere, the factors that drive it (dust properties), and the role it plays in controlling the current climate system.

Source record↗

DOE OSTI2022

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗

NASA NTRS1995

Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment. Statistics obtained using analysis windows, which are translated to span the LWP dataset, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data are transformed onto an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band and has a mean frequency that is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iteratively redistributing LWP at each scale using the value of the local mean. This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the 'variance coupled model,' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two- parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of these models.

Gollmer, Steven M.↗

NASA NTRS1984

Analogs in the wintertime 500 mb height field

Lorenz (1969) has considered the possibility that an atmospheric circulation pattern might recur, taking into account the definition of a pair of analogous flows or 'analogs'. The present investigation is concerned with a search of time series of Northern Hemisphere wintertime geopotential heights for possible analogs. Attention is given to data and analysis procedure, analog quality, and error growth rates. The obtained results imply that the found analogs are not a useful tool for forecasting the evolution of the midlatitude flow on time scales of several days. It is pointed out, however, that the negative results should not be extended to other applications of analog forecasting.

Gutzler, D. S.↗

NASA NTRS1989

Autoregressive modeling for the spectral analysis of oceanographic data

Over the last decade there has been a dramatic increase in the number and volume of data sets useful for oceanographic studies. Many of these data sets consist of long temporal or spatial series derived from satellites and large-scale oceanographic experiments. These data sets are, however, often 'gappy' in space, irregular in time, and always of finite length. The conventional Fourier transform (FT) approach to the spectral analysis is thus often inapplicable, or where applicable, it provides questionable results. Here, through comparative analysis with the FT for different oceanographic data sets, the possibilities offered by autoregressive (AR) modeling to perform spectral analysis of gappy, finite-length series, are discussed. The applications demonstrate that as the length of the time series becomes shorter, the resolving power of the AR approach as compared with that of the FT improves. For the longest data sets examined here, 98 points, the AR method performed only slightly better than the FT, but for the very short ones, 17 points, the AR method showed a dramatic improvement over the FT. The application of the AR method to a gappy time series, although a secondary concern of this manuscript, further underlines the value of this approach.

Gangopadhyay, Avijit↗

NASA NTRS1993

Analysis of the effects of mean local node-crossing time on the evolution of Sun-synchronous orbits

An investigation of the effect of mean local node-crossing time on the evolution of Sun-synchronous orbits was undertaken during Phase-A orbit analysis for the National Oceanic and Atmospheric Administration (NOAA) O,P,Q environmental spacecraft. That analysis added to the growing body of evidence that individual Sun-synchronous missions, at differing node-crossing times, experience nodal drift rates that can differ in both magnitude and direction. A Sun-synchronous orbit is obtained by means of a nodal drift rate approximating the 0.9856-degree-per-day apparent precession of the position of the mean Sun. This drift rate is achieved through the interaction of the orbital semimajor axis and inclination in Earth's geopotential field. Influencing perturbations include atmospheric drag and, most important, the effects of solar gravitation on inclination. The present analysis examines a series of Sun-synchronous orbits with mean local node-crossing times at 1-hour intervals from 6 a.m. to 6 p.m. It considers the fixed geometry of each orbital plane with respect to both the Sun and the diurnal atmospheric bulge, then analyzes the influence of these features upon the evolution of the semimajor axix and inclination and thus upon the rate of the nodal drift in the course of 1 year.

Jordan, P.↗

DOE OSTI2022

Origin of multifractality in solar wind turbulence: the role of current sheets

ABSTRACT In this work, a multifractal framework is proposed to investigate the effects of current sheets in solar wind turbulence. By using multifractal detrended fluctuation analysis coupled with surrogate methods and volatility, two solar wind magnetic field time series are investigated, one with current sheets and one without current sheets. Despite the lack of extreme-events intermittent bursts in the current sheet-free series, both series are shown to be strongly multifractal, although the current sheet-free series displays an almost linear behaviour for the scaling exponent of structure functions. Long-range correlations are shown to be the main source of multifractality for the series without current sheets, while a combination of heavy-tail distribution and non-linear correlations is responsible for multifractality in the series with current sheets. The multifractality in both time series is formally shown to be associated with an energy-cascade process using the p-model.

Gomes, Leonardo F.↗

DOE OSTI2021

Climate Extremes and Variability Surrounding Chesapeake Bay: Past, Present, and Future

Measures of extreme climate variability around Chesapeake Bay have changed over the past century (1895–2014), resulting in the need to establish new baselines for understanding future change. Here, observed climate variability is compared with Coupled Model Intercomparison Project fifth assessment climate models to evaluate ensemble model skill in this region. Observed trends include annual and seasonal declines in the percentage of cold days. Similarly, increases in the annual and seasonal percentages of warm days occurred in all seasons of the North Chesapeake (>38.2°N) but were only significant in spring and summer in the South (<38.2°N) demonstrating regional differences even at local scales. Precipitation intensity increased over the past century. Models using emissions scenarios RCP4.5 and 8.5 project these trends will continue, though they have little skill in precipitation extremes. Pacific and Atlantic climate modes are generally more correlated with climate extremes than mean temperature and precipitation suggesting potential predictability in the synoptic patterns underlying the extremes. However, they also drive the need for time series at least 60-years long for establishing climate trends. This local analysis differs from regional, state level, and local 2.5° × 3.75° grid analyses, highlighting the importance of local climate assessments that consider topographic and regional weather patterns.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1977

A new source of lunar electromagnetic induction - Forcing by the diamagnetic cavity

Analysis of the power spectral densities (PSD's) of eight 50-hour time series from Apollo 12 lunar surface magnetometer (LSM) and isochronous Explorer 35 Ames magnetometer data points to the existence of a new source of electromagnetic induction in the interior of the moon which is independent of the transverse electric mode. This source is hypothesized to arise from extension of the cavity diamagnetic field into the moon in analogy with the fringing field of a solenoid.

Sonett, C. P.↗

NASA NTRS1983

An analysis of periodicities in the 1470 to 1974 Beijing precipitation record

An analyis of a time series consisting of an annual index of dryness/wetness for the years 1470 to 1974 in Beijing, China is presented. Its power spectrum shows that dominant cycles occur with long periods of the order of 80 years. Cycles with periods of 11 and 22 years are weak or non-existent, but a significant signal at 18.7 years (which is also the period of a component of the lunar tide generating force) is detected. The long term variations in Beijing precipitation appear to lag long term (Gleissberg) variations in solar activity by nearly 75 years. A pattern which spans nearly 150 years in the Beijing record is found to be repeated with notable similarity.

Hameed, S.↗

NASA NTRS1987

SPAN: Ocean science

The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links space and Earth science research and data analysis computers. It provides a common working environment for sharing computer resources, sharing computer peripherals, solving proprietary problems, and providing the potential for significant time and cost savings for correlative data analysis. This is one of a series of discipline-specific SPAN documents which are intended to complement the SPAN primer and SPAN Management documents. Their purpose is to provide the discipline scientists with a comprehensive set of documents to assist in the use of SPAN for discipline specific scientific research.

Thomas, Valerie L.↗

NASA NTRS1991

Oceanographic data analysis with NASA's SEAPAK software

The paper presents a case study of the interannual variability of vertical Ekman transport (upwelling) observed in the North Atlantic during the CZCS data collection period in order to illustrate SEAPAK's ancillary data handling functions. The study begins at the entire basin-scale for the North Atlantic and proceeds to a regional scale where much of the observed upwelling variability occurs. The analysis utilizes a variety of output types, including images, horizontal contour plots, time series, cross sections, and vertical profiles, produced on the VAX directly or by commercially available PC software packages. The SEAPAK software can be used just as effectively for global or basin-scale studies as for regional studies.

Firestone, James K.↗

NASA NTRS2000

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses, and the validation of the results.

Schieldge, John↗

NASA NTRS2014

Analyzing the Impacts of Natural Environments on Launch and Landing Availability for NASA's Exploration Systems Development Programs

The National Aeronautics and Space Administration (NASA) is developing new capabilities for human and scientific exploration beyond Earth orbit. Natural environments information is an important asset for NASA's development of the next generation space transportation system as part of the Exploration Systems Development (ESD) Programs, which includes the Space Launch System (SLS) and Multi-Purpose Crew Vehicle (MPCV) Programs. Natural terrestrial environment conditions - such as wind, lightning and sea states - can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing to landing and recovery operations, including all potential abort scenarios. Space vehicles are particularly sensitive to these environments during the launch/ascent and the entry/landing phases of mission operations. The Marshall Space Flight Center (MSFC) Natural Environments Branch provides engineering design support for NASA space vehicle projects and programs by providing design engineers and mission planners with natural environments definitions as well as performing custom analyses to help characterize the impacts the natural environment may have on vehicle performance. One such analysis involves assessing the impact of natural environments to operational availability. Climatological time series of operational surface weather observations are used to calculate probabilities of meeting/exceeding various sets of hypothetical vehicle-specific parametric constraint thresholds. Outputs are tabulated by month and hour of day to show both seasonal and diurnal variation. This paper will discuss how climate analyses are performed by the MSFC Natural Environments Branch to support the ESD Launch Availability (LA) Technical Performance Measure (TPM), the SLS Launch Availability due to Natural Environments TPM, and several MPCV (Orion) launch and landing availability analyses - including the 2014 Orion Exploration Flight Test 1 (EFT-1) mission.

Altino, Karen M.↗

NASA NTRS2014

Analyzing the Impacts of Natural Environments on Launch and Landing Availability for NASA's Eploration Systems Development Programs

NASA is developing new capabilities for human and scientific exploration beyond Earth orbit. Natural environments information is an important asset for NASA's development of the next generation space transportation system as part of the Exploration Systems Development Program, which includes the Space Launch System (SLS) and MultiPurpose Crew Vehicle (MPCV) Programs. Natural terrestrial environment conditions - such as wind, lightning and sea states - can affect vehicle safety and performance during multiple mission phases ranging from prelaunch ground processing to landing and recovery operations, including all potential abort scenarios. Space vehicles are particularly sensitive to these environments during the launch/ascent and the entry/landing phases of mission operations. The Marshall Space Flight Center (MSFC) Natural Environments Branch provides engineering design support for NASA space vehicle projects and programs by providing design engineers and mission planners with natural environments definitions as well as performing custom analyses to help characterize the impacts the natural environment may have on vehicle performance. One such analysis involves assessing the impact of natural environments to operational availability. Climatological time series of operational surface weather observations are used to calculate probabilities of meeting or exceeding various sets of hypothetical vehicle-specific parametric constraint thresholds.

Altino, Karen M.↗

NASA NTRS2015

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

wavelet analysis↗

NASA NTRS2019

Can We Use the QA4ECV Black-sky Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) using AVHRR Surface Reflectance to Assess Terrestrial Global Change?

NOAA platforms provide the longest period of terrestrial observation since the 1980s. The progress in calibration, atmospheric corrections and physically based land retrieval offers the opportunity to reprocess these data for extending terrestrial product time series. Within the Quality Assurance for Essential Climate Variables (QA4ECV) project, the black-sky Joint Research Centre (JRC)-fraction of absorbed photosynthetically active radiation (FAPAR) algorithm was developed for the AVHRR sensors on-board NOAA-07 to -16 using the Land Surface Reflectance Climate Data Record. The retrieval algorithm was based on the radiative transfer theory, and uncertainties were included in the products. We proposed a time and spatial composite for providing both 10-day and monthly products at 0.05º × 0.05º. Quality control and validation were achieved through benchmarking against third-party products, including Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) datasets produced with the same retrieval algorithm. Past ground-based measurements, providing a proxy of FAPAR, showed good agreement of seasonality values over short homogeneous canopies and mixed vegetation. The average difference between SeaWiFS and QA4ECV monthly products over 2002–2005 is about 0.075 with a standard deviation of 0.091. We proposed a monthly linear bias correction that reduced these statistics to 0.02 and 0.001. The complete harmonized long-term time series was then used to address its fitness for the purpose of analysis of global terrestrial change.

AVHRR↗