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NASA NTRS1993

Airborne eddy correlation gas flux measurements - Design criteria for optical techniques

Although several methods exist for the determination of the flux of an atmospheric species, the airborne eddy correlation method has the advantage of providing direct flux measurements that are representative of regional spatial domains. The design criteria pertinent to the construction of chemical instrumentation suitable for use in airborne eddy correlation flux measurements are discussed. A brief overview of the advantages and limitations of the current instrumentation used to obtain flux measurements for CO, CH4, O3, CO2, and water vapor are given. The intended height of the measurement within the convective boundary layer is also shown to be an important design criteria. The sensitivity, or resolution, which is required in the measurement of a scalar species to obtain an adequate species flux measurement is discussed. The relationship between the species flux resolution and the more commonly stated instrumental resolution is developed and it is shown that the standard error of the flux estimate is a complicated function of the atmospheric variability and the averaging time that is used. The use of the recently proposed intermittent sampling method to determine the species flux is examined. The application of this technique may provide an opportunity to expand the suite of trace gases for which direct flux measurements are possible.

Ritter, John A.↗

NASA NTRS1994

HST FOS spectroscopy of M87: Evidence for a disk of ionized gas around a massive black hole

Using the Faint Object Spectrograph (FOS) on the Hubble Space Telescope (HST) to observe the central region of M87, we have obtained spectra covering approximately 4600-6800 A at a spectral dispersion approximately 4.4 A per resolution element through the .26 sec diameter entrance aperture. One spectrum was obtained centered on the nucleus of M87 and two centered 0.25 sec off the nucleus at position angles of 21 deg and 201 deg, thus sampling the anticipated major axis of the disklike structure (described in a companion Letter) expected to lie approximately perpendicular to the axis of the M87 jet. Pointing errors for these observations are estimated to be less than 0.02 sec. Radial velocities of the ionized gas in the two positions 0.25 sec on either side of the nucleus are measured to be approx. equals +/- 500 km/s relative to the M87 systemic velocity. These observations plus emission-line spectra obtained at two additional locations near the nucleus show the ionized gas to be in Keplerian rotation about a mass M = (2.4 +/- 0.7) x 10(exp 9) solar mass within the inner 0.25 sec of M87. Our results provide strong evidence for the presence of a supermassive nuclear black hole in M87.

Harms, Richard J.↗

NASA NTRS1998

Evaluation of the 29-km Eta Model: Objective Verification at Three Selected Stations - Part 1

This paper describes an objective verification of the National Centers for Environmental Prediction (NCEP) 29-km eta model from May 1996 through January 1998. The evaluation was designed to assess the model's surface and upper-air point forecast accuracy at three selected locations during separate warm (May - August) and cool (October - January) season periods. In order to enhance sample sizes available for statistical calculations, the objective verification includes two consecutive warm and cool season periods. Systematic model deficiencies comprise the larger portion of the total error in most of the surface forecast variables that were evaluated. The error characteristics for both surface and upper-air forecasts vary widely by parameter, season, and station location. At upper levels, a few characteristic biases are identified. Overall however, the upper-level errors are more nonsystematic in nature and could be explained partly by observational measurement uncertainty. With a few exceptions, the upper-air results also indicate that 24-h model error growth is not statistically significant. In February and August 1997, NCEP implemented upgrades to the eta model's physical parameterizations that were designed to change some of the model's error characteristics near the surface. The results shown in this paper indicate that these upgrades led to identifiable and statistically significant changes in forecast accuracy for selected surface parameters. While some of the changes were expected, others were not consistent with the intent of the model updates and further emphasize the need for ongoing sensitivity studies and localized statistical verification efforts. Objective verification of point forecasts is a stringent measure of model performance, but when used alone, is not enough to quantify the overall value that model guidance may add to the forecast process. Therefore, results from a subjective verification of the meso-eta model over the Florida peninsula are discussed in the companion paper by Manobianco and Nutter. Overall verification results presented here and in part two should establish a reasonable benchmark from which model users and developers may pursue the ongoing eta model verification strategies in the future.

Nutter, Paul A.↗

NASA NTRS2000

Plant chlorophyll content meter

A plant chlorophyll content meter is described which collects light reflected from a target plant and separates the collected light into two different wavelength bands. These wavelength bands, or channels, are described as having center wavelengths of 700 nm and 840 nm. The light collected in these two channels are processed using photo detectors and amplifiers. An analog to digital converter is described which provides a digital representation of the level of light collected by the lens and falling within the two channels. A controller provided in the meter device compares the level of light reflected from a target plant with a level of light detected from a light source, such as light reflected by a target having 100% reflectance, or transmitted through a diffusion receptor. The percent of reflection in the two separate wavelength bands from a target plant are compared to provide a ratio which indicates a relative level of plant physiological stress. A method of compensating for electronic drift is described where a sample is taken when a collection lens is covered to prevent light from entering the device. This compensation method allows for a more accurate reading by reducing error contributions due to electronic drift from environmental conditions at the location where a hand-held unit is used.

Spiering, Bruce A.↗

NASA NTRS2013

Creating a Satellite-Based Record of Tropospheric Ozone

The TES retrieval algorithm has been applied to IASI radiances. We compare the retrieved ozone profiles with ozone sonde profiles for mid-latitudes for the year 2008. We find a positive bias in the IASI ozone profiles in the UTLS region of up to 22 %. The spatial coverage of the IASI instrument allows sampling of effectively the same air mass with several IASI scenes simultaneously. Comparisons of the root-mean-square of an ensemble of IASI profiles to theoretical errors indicate that the measurement noise and the interference of temperature and water vapour on the retrieval together mostly explain the empirically derived random errors. The total degrees of freedom for signal of the retrieval for ozone are 3.1 +/- 0.2 and the tropospheric degrees of freedom are 1.0 +/- 0.2 for the described cases. IASI ozone profiles agree within the error bars with coincident ozone profiles derived from a TES stare sequence for the ozone sonde station at Bratt's Lake (50.2 deg N, 104.7 deg W).

pollutant↗

NASA NTRS2015

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate Which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(sub burn) = delta C(sub tot) added to the fire plume, where C(sub tot) approximately equals (CO2 + CO). Mixed-effects regression can estimate pre-fire background values of Ctot (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta epsilon lambda tau alpha−x(sub i)/(C(sub burn))i,j., MERET and "consensus" require more than two emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (bscat, babs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics.

fires↗

NASA NTRS2016

Techniques for Estimating Emissions Factors from Forest Burning: ARCTAS and SEAC4RS Airborne Measurements Indicate which Fires Produce Ozone

Previous studies of emission factors from biomass burning are prone to large errors since they ignore the interplay of mixing and varying pre-fire background CO2 levels. Such complications severely affected our studies of 446 forest fire plume samples measured in the Western US by the science teams of NASA's SEAC4RS and ARCTAS airborne missions. Consequently we propose a Mixed Effects Regression Emission Technique (MERET) to check techniques like the Normalized Emission Ratio Method (NERM), where use of sequential observations cannot disentangle emissions and mixing. We also evaluate a simpler "consensus" technique. All techniques relate emissions to fuel burned using C(burn) = delta C(tot) added to the fire plume, where C(tot) approximately equals (CO2 = CO). Mixed-effects regression can estimate pre-fire background values of C(tot) (indexed by observation j) simultaneously with emissions factors indexed by individual species i, delta, epsilon lambda tau alpha-x(sub I)/C(sub burn))I,j. MERET and "consensus" require more than emissions indicators. Our studies excluded samples where exogenous CO or CH4 might have been fed into a fire plume, mimicking emission. We sought to let the data on 13 gases and particulate properties suggest clusters of variables and plume types, using non-negative matrix factorization (NMF). While samples were mixtures, the NMF unmixing suggested purer burn types. Particulate properties (b scant, b abs, SSA, AAE) and gas-phase emissions were interrelated. Finally, we sought a simple categorization useful for modeling ozone production in plumes. Two kinds of fires produced high ozone: those with large fuel nitrogen as evidenced by remnant CH3CN in the plumes, and also those from very intense large burns. Fire types with optimal ratios of delta-NOy/delta- HCHO associate with the highest additional ozone per unit Cburn, Perhaps these plumes exhibit limited NOx binding to reactive organics. Perhaps these plumes exhibit limited NOx binding to reactive organics

ozone↗

NASA NTRS2017

Value of Sample Return and High Precision Analyses: Need for A Resource of Compelling Stories, Metaphors and Examples for Public Speakers

There is widespread agreement among planetary scientists that much of what we know about the workings of the solar system comes from accurate, high precision measurements on returned samples. Precision is a function of the number of atoms the instrumentation is able to count. Accuracy depends on the calibration or standardization technique. For Genesis, the solar wind sample return mission, acquiring enough atoms to ensure precise SW measurements and then accurately quantifying those measurements were steps known to be non‐trivial pre‐flight. The difficulty of precise and accurate measurements on returned samples, and why they cannot be made remotely, is not communicated well to the public. In part, this is be-cause "high precision" is abstract and error bars are not very exciting topics. This paper explores ideas for collecting and compiling compelling metaphors and colorful examples as a resource for planetary science public speakers.

Allton, J. H.↗

NASA NTRSDate not supplied

Spectrally Dependent Radiometric Measurement Errors Due to Ccd Serial Pixel-to-Pixel Readout Interference in the Ocean Color Instrument of the NASA PACE Mission

The Ocean Color Instrument on NASA’s PACE mission is a 322 887 nm hyperspectral imager with 1 km x 1 km nadir spatial resolution and 5 nm spectral resolution utilizing charge-coupled devices (CCDs) operating in Time Delay Integration (TDI) mode where each TDI column represents a different wavelength in 0.625 nm increments. After TDI, the charge is moved into serial output pixels and read out. The spatial resolution requires an 8.5 MHz readout rate. This only allows 59 ns for the CCD reset and video to be asserted and settled before sampling. The response exhibits serial pixel-to-pixel readout interference due to the lack of full settling. Each serial pixel value has a dependence on the value of the preceding pixel value. This leads to a spectrally dependent radiometric measurement error of up to 0.3 %. We explain the operation of the detection system, the behavior of the interference, and show the resulting measurement error based on data from both ground testing and on-orbit characterization.

Remote Sensing↗

NASA NTRS2024

Spectrally Dependent Radiometric Measurement Errors Due to CCD Serial Pixel-to-Pixel Readout Interference in the Ocean Color Instrument of the NASA PACE Mission

Remote Sensing↗

NASA NTRS1980

Software reliability: A comparison of results obtained from established software reliability models

Two models of the software error detection process are compared, the Jelinski-Moranda model and a Bayes inference model. Simulation techniques are used to generate software related system failure data which is analyzed by both models. Point estimates and confidence limits are compared. It is demonstrated that uncertainty may be considerable for reasonable samples sizes and should be considered in any application of these techniques. The Jelinski-Moranda model is sensitive to the failure of data to follow internal assumptions of the model, often not providing any point estimates, a factor which may limit its usefulness in many real world situations. The Bayes model is shown to respond to the introduction of additional errors in the software correction process, a condition where error counting models such as the Jelinski-Moranda generally fail to converge.

Horn, M. H.↗

NASA NTRS1983

Effects of autocorrelation upon LANDSAT classification accuracy

Richmond, Virginia and Denver, Colorado were study sites in an effort to determine the effect of autocorrelation on the accuracy of a parallelopiped classifier of LANDSAT digital data. The autocorrelation was assumed to decay to insignificant levels when sampled at distances of at least ten pixels. Spectral themes developed using blocks of adjacent pixels, and using groups of pixels spaced at least 10 pixels apart were used. Effects of geometric distortions were minimized by using only pixels from the interiors of land cover sections. Accuracy was evaluated for three classes; agriculture, residential and "all other"; both type 1 and type 2 errors were evaluated by means of overall classification accuracy. All classes give comparable results. Accuracy is approximately the same in both techniques; however, the variance in accuracy is significantly higher using the themes developed from autocorrelated data. The vectors of mean spectral response were nearly identical regardless of sampling method used. The estimated variances were much larger when using autocorrelated pixels.

Craig, R. G.↗

DOE OSTI2018

Evaluation of trace elements in U.S. coals using the USGS COALQUAL database version 3.0. Part I: Rare earth elements and yttrium (REY)

Coal is a potential source of valuable elements such as rare earth elements and yttrium (REY). In this work, REY concentrations in U.S. domestic coals were evaluated using data from the USGS COALQUAL Database Version 3.0. The database contains a total of 7657 non-weathered, full-bed coal samples. The number of samples containing REY data points varies among elements. Assessment of data quality indicates that some of the REY data are semi-quantitative and should be used with caution. Different analytical instruments and methods with varying accuracies and precisions are thought to be the main sources of errors. Inclusion of qualified data also accounts for the sawtooth pattern of the UCC-normalized REY distribution. A new set of Q factor values was thus proposed to adjust qualified data. Consequently, mean concentrations of REY in U.S. coals were obtained with a total REY concentration of 65.5 ppm on a moisture-free whole coal basis. Further evaluation of REY in 5378 selected coal samples indicates that about 9–13% of the samples fall into the combined category of promising and highly promising coals for REY, according to the classification of Dai et al. (2017). Taking sampling bias into consideration, we further found that bituminous coal, particularly from the central Appalachian region, has the highest probability of being a source for beneficial recovery of REY. More specifically, bituminous coal from eastern Kentucky is likely to be the best option. Lastly, we conclude that U.S. domestic coal is a promising, alternative source for beneficial recovery of REY to meet the U.S. REY demand for economic growth.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2017

Surrogate Models for TREAT Transient Calculations

The Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is currently preparing for resumption of operation after more than 20 years in a long-term standby state. In parallel with preparation for operations and a new transient testing program, the DOENE Advanced Modeling and Simulation program (NEAMS) has been supporting the development of three-dimensional transient multi-physics modeling capabilities within the reactor physics application MAMMOTH. Recently, the MAMMOTH reactor physics team has begun development of uncertainty and sensitivity analysis for the TREAT core. This research will be used to support the analysis of reactor operation and experiment planning. Traditional approaches, i.e., Monte Carlo simulations, for such tasks require a large number of model evaluations under both steady state and transient conditions. However, exhaustive sets of sampling runs are simply not practical for TREAT since evaluations of each model can take a substantial amount of time. A solution to this problem is to build a surrogate model employing a smaller number of model evaluations. The surrogate model is designed to provide an accurate and fast approximation to the detailed TREAT model. In this manner, the surrogate model can be used in place of the TREAT transient model for uncertainty and sensitivity analysis at a fraction of the computational cost. The high dimensional model representation (HDMR) method is employed here for approximating the responses of interest in terms of functions of lower dimensions. This method has been implemented in RAVEN and all TREAT transient calculations are performed using the multiphysics code MAMMOTH. In addition, a code interface has also been developed in order to couple RAVEN with MAMMOTH. The surrogate model is then tested and compared for TREAT startup testing program Transient Test no. 15 core, and its accuracy is measured by its ability to estimate the mean, coefficient of variance, skewness, excess kurtosis and probability density function of the outputs of Transient Test no. 15 model, as well as root mean square error metric.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water

Simulations of carbon dioxide (CO 2 ) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO 2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. Here, we show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Simulations of the pairwise kinematic Sunyaev-Zel'dovich signal

The pairwise kinematic Sunyaev–Zel’dovich (kSZ) signal from galaxy clusters is a probe of their line of sight momenta, and thus a potentially valuable source of cosmological information. In addition to the momenta, the amplitude of the measured signal depends on the properties of the intracluster gas and observational limitations such as errors in determining cluster centers and redshifts. In this work, we simulate the pairwise kSZ signal of clusters at z<1, using the output from a cosmological N-body simulation and including the properties of the intracluster gas via a model that can be varied in post-processing. We find that modifications to the gas profile due to star formation and feedback reduce the pairwise kSZ amplitude of clusters by ∼50%, relative to the naive “gas traces mass” assumption. We demonstrate that miscentering can reduce the overall amplitude of the pairwise kSZ signal by up to 10%, while redshift errors can lead to an almost complete suppression of the signal at small separations. We confirm that a high-significance detection is expected from the combination of data from current generation, high-resolution cosmic microwave background experiments, such as the South Pole Telescope, and cluster samples from optical photometric surveys, such as the Dark Energy Survey. Furthermore, we forecast that future experiments such as Advanced ACTPol in conjunction with data from the Dark Energy Spectroscopic Instrument will yield detection significances of at least 20σ, and up to 57σ in an optimistic scenario. Our simulated maps are publicly available at http://www.hep.anl.gov/cosmology/ksz.html.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2012

Cross-calibration of Imaging Sensors using Model-based, SI-traceable Predictions of At-sensor Radiance

Many inter-consistency efforts force empirical agreement between sensors viewing a source nearly coincident in time and geometry that ensures consistency between sensors rather than obtain an SI-traceable calibration with documented error budgets. The method described here provides interconsistency via absolute radiometric calibration with defensible error budget avoiding systematic errors through prediction of at-sensor radiance for a site viewed by multiple sensors but not necessarily viewed at coincident times. The method predicts spectral radiance over a given surface site for arbitrary view and illumination angles and for any date dominated by clear-sky conditions. The foundation is a model-based, SI-traceable prediction of at-sensor radiance over selected sites based on physical understanding of the surface and atmosphere. The calibration of the ground site will include spatial, spectral, and sunview geometric effects based on satellite and ground-based data. The result is an interconsistency of hyperspectral and multispectral sensors spanning spatial resolutions from meters to kilometers all relative to the surface site rather than a single sensor. The source-centric philosophy of calibrating the site inherently accounts for footprint size mismatch, spectral band mismatch, and temporal and spatial sampling effects. The method for characterizing the test site allows its use for SI-traceable calibration of any sensor that can view the calibrated test site. Interconsistency is obtained through the traceability and error budget rather than coincident views. Such an approach to inter-consistency provides better understanding of biases between sensors as well producing more accurate results with documented SI-traceability that reduces the need for overlapping data sets.

Thome, Kurtis↗

DOE OSTI2016

SU-F-J-193: Efficient Dose Extinction Method for Water Equivalent Path Length (WEPL) of Real Tissue Samples for Validation of CT HU to Stopping Power Conversion

Purpose: For proton therapy, an accurate model of CT HU to relative stopping power (RSP) conversion is essential. In current practice, validation of these models relies solely on measurements of tissue substitutes with standard compositions. Validation based on real tissue samples would be much more direct and can address variations between patients. This study intends to develop an efficient and accurate system based on the concept of dose extinction to measure WEPL and retrieve RSP in biological tissue in large number of types. Methods: A broad AP proton beam delivering a spread out Bragg peak (SOBP) is used to irradiate the samples with a Matrixx detector positioned immediately below. A water tank was placed on top of the samples, with the water level controllable in sub-millimeter by a remotely controlled dosing pump. While gradually lowering the water level with beam on, the transmission dose was recorded at 1 frame/sec. The WEPL were determined as the difference between the known beam range of the delivered SOBP (80%) and the water level corresponding to 80% of measured dose profiles in time. A Gammex 467 phantom was used to test the system and various types of biological tissue was measured. Results: RSP for all Gammex inserts, expect the one made with lung-450 material (<2% error), were determined within ±0.5% error. Depends on the WEPL of investigated phantom, a measurement takes around 10 min, which can be accelerated by a faster pump. Conclusion: Based on the concept of dose extinction, a system was explored to measure WEPL efficiently and accurately for a large number of samples. This allows the validation of CT HU to stopping power conversions based on large number of samples and real tissues. It also allows the assessment of beam uncertainties due to variations over patients, which issue has never been sufficiently studied before.

60 APPLIED LIFE SCIENCES↗