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All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Mapping Impervious Surfaces Globally at 30m Resolution Using Global Land Survey Data

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and 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 a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (approx. 2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified archive of the National Geospatial Intelligence Agency (NGA). For each continental area several million training pixels are derived by analysts using image segmentation algorithms and tools and then aggregated to the 30m resolution of Landsat. Here we will discuss the production/testing of this massive data set for Europe, North and South America and Africa, including assessments of the 2010 surface reflectance data. This type of analysis is only possible because of the availability of long term 30m data sets from GLS and shows much promise for integration of Landsat 8 data in the future.

global land survey↗
NASA NTRS2004

Assimilation of Stratospheric Meteorological and Constituent Observations: A Review

This talk reviews the assimilation of meteorological and constituent observations of the stratosphere. The first efforts to assimilate observations into stratospheric models were during the early 1980s, and a number of research studies followed during the next decade. Since the launch of the Upper Atmospheric Research Satellite (UARS) in 1991, model-assimilated data sets of the stratospheric meteorological state have been routinely available. These assimilated data sets were critical in bringing together observations from the different instruments on UARS as well as linking UARS observations to measurements from other platforms. Using trajectory-mapping techniques, meteorological assimilation analyses are, now, widely used in the analysis of constituent observations and have increased the level of quantitative study of stratospheric chemistry and transport. During the 1990s the use of winds and temperatures from assimilated data sets became standard for offline chemistry and transport modeling. variability in middle latitudes. The transport experiments, however, reveal a set of shortcomings that become obvious as systematic errors are integrated over time. Generally, the tropics are not well represented, mixing between the tropics and middle latitudes is overestimated, and the residual circulation is not accurate. These shortcomings reveal underlying fundamental challenges related to bias and noise. Current studies using model simulation and data assimilation in controlled experimentation are highlighting the issues that must be addressed if assimilated data sets are to be convincingly used to study interannual variability and decadal change. observations. The primary focus has been on stratospheric ozone, but there are efforts that investigate a suite of reactive chemical constituents. Recent progress in ozone assimilation shows the potential of assimilation to contribute to the validation of ozone observations and, ultimately, the retrieval of ozone profiles from space-based radiance measurements. Assimilated data sets provide accurate analyses of synoptic and planetary Scale At the same time, stratospheric assimilation is evolving to include constituent

Rood, Richard B.↗
NASA NTRS1984

A general scientific information system to support the study of climate-related data

The development and use of NASA's Pilot Climate Data System (PCDS) are discussed. The PCDS is used as a focal point for managing and providing access to a large collection of actively used data for the Earth, ocean and atmospheric sciences. The PCDS provides uniform data catalogs, inventories, and access methods for selected NASA and non-NASA data sets. Scientific users can preview the data sets using graphical and statistical methods. The system has evolved from its original purpose as a climate data base management system in response to a national climate program, into an extensive package of capabilities to support many types of data sets from both spaceborne and surface based measurements with flexible data selection and analysis functions.

Treinish, L. A.↗
NASA NTRS1975

Design criteria for a multiple input land use system

A design is presented that proposes the use of digital image processing techniques to interface existing geocoded data sets and information management systems with thematic maps and remote sensed imagery. The basic premise is that geocoded data sets can be referenced to a raster scan that is equivalent to a grid cell data set, and that images taken of thematic maps or from remote sensing platforms can be converted to a raster scan. A major advantage of the raster format is that x, y coordinates are implicitly recognized by their position in the scan, and z values can be treated as Boolean layers in a three-dimensional data space. Such a system permits the rapid incorporation of data sets, rapid comparison of data sets, and adaptation to variable scales by resampling the raster scans.

Billingsley, F. C.↗
DOE OSTI2023

COMBLE Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility recently concluded its Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE), with its campaign emphasis on marine boundary-layer clouds and mixed-phase clouds during cold-air outbreaks. The COMBLE campaign featured the deployment of the first ARM Mobile Facility (AMF1) to northern Scandinavia (Andenes, Norway), including its standard complement of ARM cloud radars. In keeping with user demands stemming from the previous AMF Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, a post-campaign radar mentor effort was initiated for COMBLE. This activity was intended to improve the usability of the ARM cloud radar data sets in response to overall demands for calibrated, corrected data sets for downstream studies and retrieval applications. In addition to the terrain complexities previously important to CACTI data sets (e.g., clutter designation and/or removal), COMBLE presented new challenges to existing ARM radar mentor capabilities. These included the extension of existing methodologies (e.g., relative calibration adjustment [RCA] target techniques) to frozen environments and the potential issues with their applicability when considering mixed-phase precipitation conditions. As in the previous CACTI documentation (Hardin et al. 2020), the overall calibration and conditioning process in ARM nomenclature is referred to as generating a “b1” datastream. For the radars, these “b1” standards refer to a datastream that has been calibrated (and cross-calibrated), with effort to deliver the highest-quality (well-characterized) data possible. The “b1” radar mentor reporting (this current document) is intended to detail (i) the status/quality of the original “a1” (raw) data sets during the COMBLE AMF campaign, (ii) the corrections and calibrations that are applied to generate the b1 datastreams available on ARM’s Data Discovery, and (iii) the details of the applied methods, e.g., how radar offset/calibration numbers were determined.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

An Update on Ozone Profile Trends for the Period 2000 to 2016

Ozone profile trends over the period 2000 to 2016 from several merged satellite ozone data sets and from ground-based data measured by four techniques at stations of the Network for the Detection of Atmospheric Composition Change indicate significant ozone increases in the upper stratosphere, between 35 and 48 kilometers altitude (5 and 1 hectopascals). Near 2 hectopascals (42 kilometers), ozone has been increasing by about 1.5 percent per decade in the tropics (20 degrees S to 20 degrees N), and by 2 to 2.5 percent per decade in the 35 to 60 degree latitude bands of both hemispheres. At levels below 35 kilometers (5 hectopascals), 2000 to 2016 ozone trends are smaller and not statistically significant. The observed trend profiles are consistent with expectations from chemistry climate model simulations. This study confirms positive trends of upper stratospheric ozone already reported, e.g., in the WMO/UNEP (World Meteorological Organization/United Nations Environmental Programme) Ozone Assessment 2014 or by Harris et al. (2015). Compared to those studies, three to four additional years of observations, updated and improved data sets with reduced drift, and the fact that nearly all individual data sets indicate ozone increase in the upper stratosphere, all give enhanced confidence. Uncertainties have been reduced, for example for the trend near 2 hectopascals in the 35 to 60 degree latitude bands from about plus or minus 5 percent (2 sigma) in Harris et al. (2015) to less than plus or minus 2 percent (2 sigma). Nevertheless, a thorough analysis of possible drifts and differences between various data sources is still required, as is a detailed attribution of the observed increases to declining ozone-depleting substances and to stratospheric cooling. Ongoing quality observations from multiple independent platforms are key for verifying that recovery of the ozone layer continues as expected.

chemistry climate model simulations↗
NASA NTRS2003

Direct Manipulation in Virtual Reality

Virtual Reality interfaces offer several advantages for scientific visualization such as the ability to perceive three-dimensional data structures in a natural way. The focus of this chapter is direct manipulation, the ability for a user in virtual reality to control objects in the virtual environment in a direct and natural way, much as objects are manipulated in the real world. Direct manipulation provides many advantages for the exploration of complex, multi-dimensional data sets, by allowing the investigator the ability to intuitively explore the data environment. Because direct manipulation is essentially a control interface, it is better suited for the exploration and analysis of a data set than for the publishing or communication of features found in that data set. Thus direct manipulation is most relevant to the analysis of complex data that fills a volume of three-dimensional space, such as a fluid flow data set. Direct manipulation allows the intuitive exploration of that data, which facilitates the discovery of data features that would be difficult to find using more conventional visualization methods. Using a direct manipulation interface in virtual reality, an investigator can, for example, move a data probe about in space, watching the results and getting a sense of how the data varies within its spatial volume.

Bryson, Steve↗
NASA NTRSDate not supplied

Surface Radiation Budget

The Surface Radiation Budget (SRB) data sets contain global 3-hourly, daily and monthly averages of surface longwave and shortwave radiative properties, cloud amount, and meteorological properties computed using models. The main input data for these models include cloud information, top-of-atmosphere radiances and profiles of atmospheric water vapor and temperature. Some of the input data include Earth Radiation Budget Energy (ERBE) top-of-atmosphere clear-sky albedo and International Satellite Cloud Climatology Project (ISCCP) radiances and cloud amount. SRB parameters derived for the renewable energy community are also available from the Surface meteorology and Solar Energy (SSE) data set. Other SRB data are available from Clouds and the Earth's Radiant Energy System (CERES) and Multi-angle Imaging SpectroRadiometer (MISR). [Mission Objectives] The objective of the SRB Project is to produce and archive a global data set of shortwave (SW) and longwave (LW) surface and top of the atmosphere parameters. The data generated in the SRB project may be used in conjunction with other data sets to facilitate the development of renewable energy resources and increase understanding of radiative properties within the meteorological community. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

Stackhouse, Paul W.↗
NASA NTRS2016

An Assessment of New Satellite Data Products for the Development of a Long-Term Global Solar Resource at 10-100 km

A project representing an effort to reprocess the NASA based solar resource data sets is reviewed. The effort represented a collaboration between NASA, NOAA, NREL and the SUNY-Albany and aimed to deliver a 10 km resolution, 3-hourly data set spanning from 1983 through near-present. Part of the project was to transition project capability to NREL for annual processing to extend data set. Due to delays in the key input project called ISCCP, we evaluate only Beta versions of this data set and also introduce the potential use of another NASA Langley based cloud data set for the CERES project. The CERES project uses these cloud properties to compute global top-of-atmosphere and surface fluxes at the 1x1 degree resolution. Here, we also briefly discuss these data sets in potential usage for solar resource benchmarking.

Stackhouse, Paul W., Jr.↗
DOE OSTI2021

Phase-weighted slant stacking for surface wave dispersion measurement

SUMMARY Surface wave retrieval from ambient noise records using seismic interferometry techniques has been widely used for multiscale shear wave velocity (Vs) imaging. One key step during Vs imaging is the generation of dispersion spectra and the extraction of a reliable dispersion curve from the retrieved surface waves. However, the sparse array geometry usually affects the ability for high-frequency (>1 Hz) seismic signals’ acquisition. Dispersion measurements are degraded by array response due to sparse sampling and often present smeared dispersion spectra with sidelobe artefacts. Previous studies usually focus on interferograms’ domain (e.g. cross-correlation function) and attempt to enhance coherent signals before dispersion measurement. We propose an alternative technique to explicitly deblur dispersion spectra through use of a phase-weighted slant-stacking algorithm. Numerical examples demonstrate the strength of the proposed technique to attenuate array responses as well as incoherent noise. Three different field examples prove the flexibility and superiority of the proposed technique: the first data set consists of ambient noise records acquired using a nodal seismometer array; the second data set utilizes distributed acoustic sensing (DAS) and a marine fibre-optic cable to acquire a similar ambient noise data set; the last data set is a vibrator-based active-source surface wave data. The enhanced dispersion measurements provide cleaner and higher-resolution spectra without distortions which will assist both human interpreters as well as ML algorithms in efficiently picking curves for subsequent Vs inversion.

58 GEOSCIENCES↗
NASA NTRS2010

Peak Wind Tool for General Forecasting

The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded again by six years, from October 1996 to April 2002, by interpolating 1000-ft sounding data to 100-ft increments. The Phase II developmental data set included observations for the cool season months of October 1996 to February 2007. The AMU calculated 68 candidate predictors from the XMR soundings, to include 19 stability parameters, 48 wind speed parameters and one wind shear parameter. Each day in the data set was stratified by synoptic weather pattern, low-level wind direction, precipitation and Richardson Number, for a total of 60 stratification methods. Linear regression equations, using the 68 predictors and 60 stratification methods, were created for the tool's three forecast parameters: the highest peak wind speed of the day (PWSD), 5-minute average speed at the same time (A WSD), and timing of the PWSD. For PWSD and A WSD, 30 Phase II methods were selected for evaluation in the verification data set. For timing of the PWSD, 12 Phase\I methods were selected for evaluation. The verification data set contained observations for the cool season months of March 2007 to April 2009. The data set was used to compare the Phase I and II forecast methods to climatology, model forecast winds and wind advisories issued by the 45 WS. The model forecast winds were derived from the 0000 and 1200 UTC runs of the 12-km North American Mesoscale (MesoNAM) model. The forecast methods that performed the best in the verification data set were selected for the Phase II version of the tool. For PWSD and A WSD, linear regression equations based on MesoNAM forecasts performed significantly better than the Phase I and II methods. For timing of the PWSD, none of the methods performed significantly bener than climatology. The AMU then developed the Microsoft Excel and MIDDS GUls. The GUIs display the forecasts for PWSD, AWSD and the probability the PWSD will meet or exceed 25 kt, 35 kt and 50 kt. Since none of the prediction methods for timing of the PWSD performed significantly better thanlimatology, the tool no longer displays this predictand. The Excel and MIDDS GUIs display forecasts for Day-I to Day-3 and Day-I to Day-5, respectively. The Excel GUI uses MesoNAM forecasts as input, while the MIDDS GUI uses input from the MesoNAM and Global Forecast System model. Based on feedback from the 45 WS, the AMU added the daily average wind speed from 30 ft to 60 ft to the tool, which is one of the parameters in the 24-Hour and Weekly Planning Forecasts issued by the 45 WS. In addition, the AMU expanded the MIDDS GUI to include forecasts out to Day-7.

Barrett, Joe H., III↗
NASA NTRS2001

A Comparison of HALOE V19 with SAGE II V6.00 Ozone Observations using Trajectory Mapping

We apply trajectory mapping to an eight-year intercomparison of ozone observations from HALOE (V19) and SAGE II (V6.00) for the months March, May, June, September, October, and December from the period December 1991 - October 1999. Our results, which represent the most extensive such intercomparison of these two data sets to date, suggest a root-mean -square difference between the two data sets of greater than 15% below 22 km and of 4 - 12% throughout most of the rest of the stratosphere. In addition, we find a bias with HALOE ozone low relative to SAGE II by 5 - 20% below 22 km between 40degS and 40degN. Biases throughout most of the rest of the stratosphere are nearly nonexistent. Finally, our analysis suggests almost no drift in the bias between the data sets is observed over the period of study. In the course of our study, we also determine that the employment of the Wang-Cunnold criteria is still recommended with the V6.00 SAGE II ozone data. Results with the new versions of the data sets show significant improvement over previous versions, particularly in the elimination of mid-stratospheric biases and the elimination of the previously observed drifts in the biases between the data sets in the lower stratosphere. Since HALOE V19 and V18 ozone are very similar, these changes can likely be attributed to improvements in the SAGE II retrieval.

Morris, Gary A.↗
NASA NTRS2000

Test Cases for the Benchmark Active Controls: Spoiler and Control Surface Oscillations and Flutter

As a portion of the Benchmark Models Program at NASA Langley, a simple generic model was developed for active controls research and was called BACT for Benchmark Active Controls Technology model. This model was based on the previously-tested Benchmark Models rectangular wing with the NACA 0012 airfoil section that was mounted on the Pitch and Plunge Apparatus (PAPA) for flutter testing. The BACT model had an upper surface spoiler, a lower surface spoiler, and a trailing edge control surface for use in flutter suppression and dynamic response excitation. Previous experience with flutter suppression indicated a need for measured control surface aerodynamics for accurate control law design. Three different types of flutter instability boundaries had also been determined for the NACA 0012/PAPA model, a classical flutter boundary, a transonic stall flutter boundary at angle of attack, and a plunge instability near M = 0.9. Therefore an extensive set of steady and control surface oscillation data was generated spanning the range of the three types of instabilities. This information was subsequently used to design control laws to suppress each flutter instability. There have been three tests of the BACT model. The objective of the first test, TDT Test 485, was to generate a data set of steady and unsteady control surface effectiveness data, and to determine the open loop dynamic characteristics of the control systems including the actuators. Unsteady pressures, loads, and transfer functions were measured. The other two tests, TDT Test 502 and TDT Test 5 18, were primarily oriented towards active controls research, but some data supplementary to the first test were obtained. Dynamic response of the flexible system to control surface excitation and open loop flutter characteristics were determined during Test 502. Loads were not measured during the last two tests. During these tests, a database of over 3000 data sets was obtained. A reasonably extensive subset of the data sets from the first two tests have been chosen for Test Cases for computational comparisons concentrating on static conditions and cases with harmonically oscillating control surfaces. Several flutter Test Cases from both tests have also been included. Some aerodynamic comparisons with the BACT data have been made using computational fluid dynamics codes at the Navier-Stokes level (and in the accompanying chapter SC). Some mechanical and active control studies have been presented. In this report several Test Cases are selected to illustrate trends for a variety of different conditions with emphasis on transonic flow effects. Cases for static angles of attack, static trailing-edge and upper-surface spoiler deflections are included for a range of conditions near those for the oscillation cases. Cases for trailing-edge control and upper-surface spoiler oscillations for a range of Mach numbers, angle of attack, and static control deflections are included. Cases for all three types of flutter instability are selected. In addition some cases are included for dynamic response measurements during forced oscillations of the controls on the flexible mount. An overview of the model and tests is given, and the standard formulary for these data is listed. Some sample data and sample results of calculations are presented. Only the static pressures and the first harmonic real and imaginary parts of the pressures are included in the data for the Test Cases, but digitized time histories have been archived. The data for the Test Cases are also available as separate electronic files.

Bennett, Robert M.↗