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NASA NTRS2021

ICESat-2 Atmospheric Channel Description, Data Processing and First Results

The Advanced Topographic Laser Altimeter System (ATLAS) was launched aboard the Ice Cloud and land-Elevation Satellite-2 (ICESat-2) satellite in September 2018. ATLAS is a single wavelength (532 nm) lidar system designed to acquire high resolution measurements of the earth's surface while also obtaining atmospheric backscatter from molecules, clouds, and aerosols. Because ATLAS is optimized for altimetry, the atmospheric data acquired is unique in many respects and requires non-standard analysis techniques. For example, the high repetition rate laser limits the vertical extent of the profiles to just 14 km and causes atmospheric scattering from above 15 km to be added to the scattering in the lower 0–14 km profile. In addition, the limited vertical range of the acquired profiles renders it difficult to compute the magnitude of the solar background and hinders the application of standard calibration techniques. Despite these limitations, methods have been developed to successfully produce data products that have value to the atmospheric community for cloud and aerosol research and are currently available at the National Snow and Ice Data Center (NSIDC). In this paper we describe the ICESat-2 atmospheric channel and the methods used to process the ATLAS raw photon count data to obtain calibrated backscatter and higher level products such as layer heights and type, blowing snow, column optical depth and apparent surface reflectance.

Stephen P Palm↗
NASA NTRSDate not supplied

Leveraging Existing Satellite Precipitation Missions for AOS Applications Development

The Atmosphere Observing System (AOS) seeks to explore fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. AOS will provide key information to enhance the communities’ ability to improve weather and air quality forecasting today, seasonal to sub-seasonal changes in the near future, and societal challenges resulting from climate change in the decades to come. A fundamental component of the AOS mission is ensuring that applications are considered to the greatest extent possible in mission design.As a result, the Applications Impact Team (AIT) was implemented to address this objective.The overarching goal of the AIT is to help improve the capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data becomes available.To support these efforts, we leverage existing mission applications activities and initiatives, such as NASA’s GPM and TROPICS missions, to form a framework to enhance precipitation applications for AOS. Engaging with existing missions helps identify and understand data needs, gaps and opportunities for current and future stakeholders, determine what precipitation data products are of highest value and use, and helps connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS AIT activities and initiatives and highlight how existing satellite precipitation missions and their applications activities can play a critical role in AOS applications development during mission design.

Andrea Portier↗
NASA NTRSDate not supplied

The Benefit of NASA's Atmosphere Observing System (AOS) Mission Lidar and Polarimeter Observations for Health and Air Quality Applications

The Atmosphere Observing System (AOS) seeks to explore fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. AOS will provide key information to enhance the communities’ ability to improve weather and air quality forecasting today, seasonal to sub-seasonal changes in the near future, and societal challenges resulting from climate change in the decades to come. A fundamental component of the AOS mission is ensuring that health and air quality applications are considered to the greatest extent possible in mission design. As a result, the Applications Impact Team (AIT) was implemented to address this objective. The overarching goal of the AIT is to help improve the capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data becomes available. To support these efforts, we leverage existing and near future mission applications activities and initiatives, such as the NASA CALIPSO, MAIA, TEMPO, and PACE missions to form a framework to enhance health and air quality applications for AOS. The unique synergy between lidar and polarimeter instruments onboard the AOS constellation, as well as diurnally varying observations of aerosol profiles, will provide new opportunities to engage health and air quality stakeholders for forecasting, monitoring, and warning of hazardous events (e.g., wildfire smoke, volcanic ash) that impact human health. Engaging with existing missions helps identify and understand data needs, gaps and opportunities for current and future stakeholders, determine what aerosol data products are of highest value and use, and helps connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS aerosol observations relevant for health and air quality applications, AIT activities and initiatives and how existing aerosol satellite missions and their applications activities can play a critical role in AOS applications development during mission design.

Melanie Follette-Cook↗
DOE OSTI2014

Archiving Data from New Survey Technologies: Lessons Learned on Enabling Research with High-Precision Data While Preserving Participant Privacy: Preprint

During the past 15 years, increasing numbers of organizations and planning agencies have begun collecting high-resolution Global Positioning System (GPS) travel data. Despite the significant effort and expense to collect it, privacy concerns often lead to underutilization of the data. To address this dilemma of providing data access while preserving privacy, the National Renewable Energy Laboratory, with support from the U.S. Department of Transportation and U.S. Department of Energy, established the Transportation Secure Data Center (TSDC). Lessons drawn from best-practice examples from other data centers have helped shape the structure and operating procedures for the TSDC, which functions under the philosophy of first and foremost preserving privacy, but doing so in a way that balances security with accessibility and usability of the data for legitimate research. This paper provides details about the TSDC approach toward achieving these goals, which has included creating a secure enclave with no external access for backing up and processing raw data, a publicly accessible website for downloading cleansed data, and a secure portal environment through which approved users can work with detailed spatial data using a variety of tools and reference information. This paper also describes lessons learned from operating the TSDC with respect to improvements in GPS data handling, processing, and user support, along with plans for continual enhancements to better support the needs of both data providers and users and to thus advance the research value derived from such valuable data.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Ambient Mass Spectrometry Rapid Analysis Methods for Trace Inorganics

The ability to rapidly detect and characterize the chemistry of trace quantities of inorganic species has multiple potential applications, including nuclear safeguards, nuclear forensics, and environmental monitoring. Some mass spectrometric methods currently exist, but they are costly and time-intensive, often destroying chemical information in the process of ionization. Ambient mass spectrometry is a relatively new analytical method in which samples are introduced to the mass spectrometer from atmospheric pressure, rather than from high vacuum. Ambient MS can operate with gentler ionization methods such as electrospray ionization (ESI) and paper-spray ionization (PSI), reducing fragmentation and preserving the chemical information of the analyte. This may be useful for determining the intended purpose of material in a sample. Strontium, part of nuclear fallout, is analyzed here to test these new analytical methods for viability. Electrospray ionization mass spectrometry functions by spraying the sample as a solution through a needle charged to a few kV. A nebulizing gas flows out along with the sample to create the spray before droplets enter a drying chamber with heated drying gas to remove the solvent molecules. From there bare analyte ions enter the mass spectrometer. This method has the advantage of relatively fast sample preparation and stable ionization. More stable ionization produces higher-quality data. Paper-spray ionization mass spectrometry operates by applying sample to a paper triangle. The paper triangle is then electrified in a metal clamp to a few kV before spray solvent is applied. The spray solvent transports analyte in the sample to the tip, where it is ionized and enters the mass spectrometer. One advantage of this method is reduced sample preparation - an analyst can even swipe a surface and cut a triangle directly from the swipe. The data analysis serves to rapidly process tens of samples all at once. The mass spectrometer outputs a file containing a few hundred spectra for each sample. The pipeline processes each one to identify peaks of interest. A full palette of data analysis metrics are generated, including plots of the raw data and plots of calculated values such as isotopic ratios. The pipeline filters the raw data to remove noise and background peaks, as well as peaks representing detector saturation. A heat map is generated to show the overall spectrum in mass-time- intensity space. Post-processing, we obtained the desired calibration curves, demonstrating that both ESI-MS and PSI-MS are viable methods for quantifying trace amounts of inorganics while retaining their chemical speciation information. ESI-MS demonstrated a linear response region of 100 ppb to 20 ppm, with a limit-of-detection of around 100 ppb. At top left is an example spectrum with the {sup 88}SrNO{sub 3} peak identified to show the retention of chemical speciation. PSI-MS showed a linear response region of around 1 ppb to 1 ppm, with a limit-of-detection of near 1 ppb. PSI-MS produced more erratic results than ESI-MS, likely due to the variability in ionization resulting from manual positioning of the paper triangle near the MS inlet. Future efforts will focus on improving the repeatability of PSI-MS as well as analyzing other species of interest such as cerium and uranium. Improvements will also be made to create more reliable data extraction and intelligent data filtering.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1979

Wetland flow resistance determination using Landsat data

In the past, one value of the roughness coefficient has frequently been used to represent the flow resistance characteristics of an entire natural wetland throughout the year. To improve the simulation of water flow through these natural vegetation communities, Landsat imagery and in situ flow measurements were combined to produce a more detailed representation of flow resistance. The vegetation in a typical marshland drainage basin in south Florida was classified into five categories using Landsat data. Flow measurements were then performed at characteristic sites in the basin. The measurements were taken at various depths during months of significant flow to examine the effect of seasonal growth. This information was then combined with the areal distribution of the vegetation as measured by satellite to more accurately simulate resistance to water flow in a natural marshland drainage basin.

Gervin, J. C.↗
NASA NTRS1994

Total ozone trends over the USA during 1979-1991 from Dobson spectrophotometer observations

Ozone trends for 1979-1991, determined from Dobson spectrophotometer observations made at eight stations in the United States, are augmented with trend data from four foreign cooperative stations operated by NOAA/CMDL. Results are based on provisional data archived routinely throughout the years at the World Ozone Data Center in Toronto, Canada, with calibration corrections applied to some of the data. Trends through 1990 exhibit values of minus 0.3 percent to minus 0.5 percent yr(exp -1) at mid-to-high latitudes in the northern hemisphere. With the addition of 1991 data, however, the trends become less negative, indicating that ozone increased in many parts of the world during 1991. Stations located within the plus or minus 20 deg N-S latitude band exhibit no ozone trends. Early 1992 data show decreased ozone values at some of the stations. At South Pole, Antarctica, October ozone values have remained low during the past 3 years.

Komhyr, Walter D.↗
NASA NTRS1981

A technique for improved assessment of flow resistance characteristics of natural wetlands using Landsat data

In the past, one value of the roughness coefficient has frequently been used to represent the flow resistance characteristics of the entire natural wetland throughout the year. To improve the simulation of water flow through these natural vegetation communities, Landsat imagery and in situ flow measurements could be combined to produce a more detailed representation of flow resistance. The vegetation in a typical marshland drainage basin in south Florida was classified into five major categories using Landsat data. Flow measurements were then performed at characteristic sites in the basin. The measurements were taken at various depths during months of significant flow to examine the effect of seasonal growth. This information can be compared with the areal extent of the vegetation measured by satellite to more accurately simulate resistance to water flow in natural marshland drainage basins.

Gervin, J. C.↗
DOE OSTI2022

Bayesian Optimization Framework for Imperfect Data or Models

Conventional Bayesian optimization methods implicitly assume that the data and model being optimized are “perfect.” This assumption leads to inaccurate posterior probability distribution functions (PDFs) when applied to “imperfect” data or models. The new Bayesian optimization framework presented in this report provides a way to parameterize the effect of imperfections usually encountered in a prior PDF of generalized data or a model on the posterior PDF. The effects of imperfections are parameterized by a set of constraints imposed on the posterior expectation values of deviations between the data and the model and on their covariance matrix elements. A particular set of values for these constraints conveys an evaluator’s best estimate of the effect of imperfections on the corresponding posterior expectation values. When a prior PDF of generalized data is assumed to be normal, an expression for a posterior PDF satisfying an arbitrary set of constraints is derived analytically for linear models. An analogous iterative algorithm is given for nonlinear models. The corresponding posterior PDF should be used to estimate any posterior expectation values in the presence of imperfections parameterized by that set of constraints. A posterior PDF of a conventional Bayesian optimization method is recovered analytically when all evaluator-specified constraints are set to zero (i.e., in the absence of any imperfections). The analytical expressions derived in this report for normal PDFs and linear models were verified numerically by a Metropolis–Hastings Monte Carlo method. The methods presented herein could be applied to any kind of data or models, including differential cross-section data or integral benchmark experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Landmark-embedded Gaussian process with applications for functional data modeling

In practice, we often need to infer the value of a target variable from functional observation data. A challenge in this task is that the relationship between the functional data and the target variable is very complex: the target variable not only influences the shape but also the location of the functional data. In addition, due to the uncertainties in the environment, the relationship is probabilistic, that is, for a given fixed target variable value, we still see variations in the shape and location of the functional data. To address this challenge, we present a landmark-embedded Gaussian process model that describes the relationship between the functional data and the target variable. A unique feature of the model is that landmark information is embedded in the Gaussian process model so that both the shape and location information of the functional data are considered simultaneously in a unified manner. Gibbs-Metropolis-Hasting algorithm is used for model parameters estimation and target variable inference. The performance of the proposed framework is evaluated by extensive numerical studies and a case study of nano-sensor calibration.

42 ENGINEERING↗
NASA NTRS1989

Low temperature measurement of the vapor pressures of planetary molecules

Interpretation of planetary observations and proper modeling of planetary atmospheres are critically upon accurate laboratory data for the chemical and physical properties of the constitutes of the atmospheres. It is important that these data are taken over the appropriate range of parameters such as temperature, pressure, and composition. Availability of accurate, laboratory data for vapor pressures and equilibrium constants of condensed species at low temperatures is essential for photochemical and cloud models of the atmospheres of the outer planets. In the absence of such data, modelers have no choice but to assume values based on an educated guess. In those cases where higher temperature data are available, a standard procedure is to extrapolate these points to the lower temperatures using the Clausius-Clapeyron equation. Last summer the vapor pressures of acetylene (C2H2) hydrogen cyanide (HCN), and cyanoacetylene (HC3N) was measured using two different methods. At the higher temperatures 1 torr and 10 torr capacitance manometers were used. To measure very low pressures, a technique was used which is based on the infrared absorption of thin film (TFIR). This summer the vapor pressure of acetylene was measured the TFIR method. The vapor pressure of hydrogen sulfide (H2S) was measured using capacitance manometers. Results for H2O agree with literature data over the common range of temperature. At the lower temperatures the data lie slightly below the values predicted by extrapolation of the Clausius-Clapeyron equation. Thin film infrared (TFIR) data for acetylene lie significantly below the values predicted by extrapolation. It is hoped to bridge the gap between the low end of the CM data and the upper end of the TFIR data in the future using a new spinning rotor gauge.

Kraus, George F.↗
NASA NTRS2013

Potassium Isotopic Compositions of NIST Potassium Standards and 40Ar/39Ar Mineral Standards

Knowledge of the isotopic ratios of standards, spikes, and reference materials is fundamental to the accuracy of many geochronological methods. For example, the 238U/235U ratio relevant to U-Pb geochronology was recently re-determined [1] and shown to differ significantly from the previously accepted value employed during age determinations. These underlying values are fundamental to accurate age calculations in many isotopic systems, and uncertainty in these values can represent a significant (and often unrecognized) portion of the uncertainty budget for determined ages. The potassium isotopic composition of mineral standards, or neutron flux monitors, is a critical, but often overlooked component in the calculation of K-Ar and 40Ar/39Ar ages. It is currently assumed that all terrestrial materials have abundances indistinguishable from that of NIST SRM 985 [2]; this is apparently a reasonable assumption at the 0.25per mille level (1σ) [3]. The 40Ar/39Ar method further relies on the assumption that standards and samples (including primary and secondary standards) have indistinguishable 40K/39K values. We will present data establishing the potassium isotopic compositions of NIST isotopic K SRM 985, elemental K SRM 999b, and 40Ar/39Ar biotite mineral standard GA1550 (sample MD-2). Stable isotopic compositions (41K/39K) were measured by the peak shoulder method with high resolution MC-ICP-MS (Thermo Scientific NEPTUNE Plus), using the accepted value of NIST isotopic SRM 985 [2] for fractionation [4] corrections [5]. 40K abundances were measured by TIMS (Thermo Scientific TRITON), using 41K/39K values from ICP-MS measurements (or, for SRM 985, values from [2]) for internal fractionation corrections. Collectively these data represent an important step towards a metrologically traceable calibration of 40K concentrations in primary 40Ar/39Ar mineral standards and improve uncertainties by ca. an order of magnitude in the potassium isotopic compositions of standards.

Morgan, Leah↗
NASA NTRS2017

Suomi NPP VIIRS Solar Diffuser Screen Transmittance Model and Its Applications

The visible infrared imaging radiometer suite on the Suomi National Polar-orbiting Partnership satellite calibrates its reflective solar bands through observations of a sunlit solar diffuser (SD) panel. Sunlight passes through a perforated plate, referred to as the SD screen, before reaching the SD. It is critical to know whether the SD screen transmittance measured prelaunch is accurate. Several factors such as misalignments of the SD panel and the measurement apparatus could lead to errors in the measured transmittance and thus adversely impact on-orbit calibration quality through the SD. We develop a mathematical model to describe the transmittance as a function of the angles that incident light makes with the SD screen, and apply the model to fit the prelaunch measured transmittance. The results reveal that the model does not reproduce the measured transmittance unless the size of the apertures in the SD screen is quite different from the design value. We attribute the difference to the orientation alignment errors for the SD panel and the measurement apparatus. We model the alignment errors and apply our transmittance model to fit the prelaunch transmittance to retrieve the "true" transmittance. To use this model correctly, we also examine the finite source size effect on the transmittance. Furthermore, we compare the product of the retrieved "true" transmittance and the prelaunch SD bidirectional reflectance distribution function (BRDF) value to the value derived from on-orbit data to determine whether the prelaunch SD BRDF value is relatively accurate. The model is significant in that it can evaluate whether the SD screen transmittance measured prelaunch is accurate and help retrieve the true transmittance from the transmittance with measurement errors, consequently resulting in a more accurate sensor data product by the same amount.

sensors↗
NASA NTRS1972

The formation and analysis of a 5 deg equal area block terrestrial gravity field

A set of 23,355 1 degree x 1 degree mean free air anomalies were used to predict a set of 5 degree equal area anomalies and their standard errors. Using the 1 degree data incorporating geophysically predicted values of ACIC, 1283 5 degree blocks were computed. Excluding the geophysically predicted anomalies 1249 blocks were computed. The 1 degree data were also used to compute covariance functions and the equatorial gravity and flattening implied by this data. The predicted anomalies were supplemented by model anomalies to form a complete 1654 global anomaly field. These data were used in a weighted least squares to determine potential coefficients to degree 15, and in a summation type formulation to determine potential coefficients to degree 25. These potential coefficients sets are compared to recent satellite determinations.

Rapp, R. H.↗
NASA NTRS1977

Different ages of lunar light plains

The crater populations of 18 lunar light plains (Cayley plains) show a variation in relative ages by a factor of about 4 in crater frequency in regions in the surroundings of the Orientale and Imbrium basin, and by a factor of greater than 25 for more distant sites. Thus the idea of a moon-wide synchronism in the emplacement of the lunar light plains with the formation of the basins Imbrium or Orientale cannot be supported. Some light plains are younger than the youngest basin Orientale. Since these plains cannot have been emplaced by any other basin-forming event and local impact-derived origin can certainly be excluded, an endogenic (magmatic) origin is proposed for these plains. Age determination data (D sub L values) by Soderblom and Lebofsky (1972) and Soderblom and Boyce (1972) are shown to be correlated with own cumulative crater frequency data (N) for surfaces younger than about 3.8 b.y. It is found that D sub L is proportional to the 0.6 power of N. For ages greater than 3.8 b.y., the D sub L data by those authors, especially their light plains data, are incompatible with the present crater frequency data.

Neukum, G.↗
NASA NTRS1983

Status of the geopotential

Satellite laser ranging, satellite altimetry, and improved measurements of surface gravitational anomalies have broadened the data base on intermediate and short wavelength regions of the earth gravity field. The global data set served to develop new geopotential models with a resolution in spherical harmonics out to degree 180. The resolution was made possible using Seasat altimetry data containing 56,761 values of 1 x 1 deg gravity anomalies. Satellite-to-satellite tracking techniques involving the Geos-3 and Apollo spacecraft data for the sea surface temperature have yielded accurate intermediate wavelength gravity variations which correlate well with residual depth anomalies. Oceanic gravity anomalies have been computed directly from satellite altimetry or through statistical estimation using oceanic geoid heights. The data sets for gravimetric geoids have been compared with altimetric surfaces to identify areas which were of interest for geophysical investigation. Future data sets could become available from a proposed satellite-to-satellite Doppler tracking system (Gravsat) launched by NASA.

Lerch, F. J.↗
DOE OSTI2012

Establishing a Secure Data Center with Remote Access: Preprint

Access to existing travel data is critical for many analysis efforts that lack the time or resources to support detailed data collection. High-resolution data sets provide particular value, but also present a challenge for preserving the anonymity of the original survey participants. To address this dilemma of providing data access while preserving privacy, the National Renewable EnergyLaboratory and the U.S. Department of Transportation have launched the Transportation Secure Data Center (TSDC). TSDC data sets include those from regional travel surveys and studies that increasingly use global positioning system devices. Data provided by different collecting agencies varies with respect to formatting, elements included and level of processing conducted in support of theoriginal purpose. The TSDC relies on a number of geospatial and other analysis tools to ensure data quality and to generate useful information outputs. TSDC users can access the processed data in two different ways. The first is by downloading summary results and second-by-second vehicle speed profiles (with latitude/longitude information removed) from a publicly-accessible website. The secondmethod involves applying for a remote connection account to a controlled-access environment where spatial analysis can be conducted, but raw data cannot be removed. The TSDC website is http://www.nrel.gov/vehiclesandfuels/secure_transportation_data.html.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Diagnostics of Data-Driven Models: Uncertainty Quantification of PM7 Semi-Empirical Quantum Chemical Method

Abstract We report an evaluation of a semi-empirical quantum chemical method PM7 from the perspective of uncertainty quantification. Specifically, we apply Bound-to-Bound Data Collaboration, an uncertainty quantification framework, to characterize (a) variability of PM7 model parameter values consistent with the uncertainty in the training data and (b) uncertainty propagation from the training data to the model predictions. Experimental heats of formation of a homologous series of linear alkanes are used as the property of interest. The training data are chemically accurate , i.e., they have very low uncertainty by the standards of computational chemistry. The analysis does not find evidence of PM7 consistency with the entire data set considered as no single set of parameter values is found that captures the experimental uncertainties of all training data. A set of parameter values for PM7 was able to capture the training data within ±1 kcal/mol, but not to the smaller level of uncertainty in the reported data. Nevertheless, PM7 was found to be consistent for subsets of the training data. In such cases, uncertainty propagation from the chemically accurate training data to the predicted values preserves error within bounds of chemical accuracy if predictions are made for the molecules of comparable size. Otherwise, the error grows linearly with the relative size of the molecules.

42 ENGINEERING↗