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NASA NTRS2018

The Convergence of Analysis Produced by Overlapping Assimilation Streams

When conducting a reanalysis for a long period, it is common to do so using multiple, parallel computational schemes. A period of overlap is included to foster continuity between successive streams. At the GMAO, the overlap period is one year. By the end of that period, the time mean anlysis for corresponding overlapped months are almost identical, as desired. The variances of differences at corresponding analysis times within each month, however, do not converge to zero. Instead their monthly variances converge to values that are a significant fraction of the the estimated variances of analysis errors. This occurs although the overlapping streams use the same observations, assimilation model, and assimilation algorithm, differing only in the background applied information applied at the beginning of the overlap period.

Errico, Ronald M.↗
NASA NTRS2018

Development of Gridded Innovations and Observations Supplement to MERRA-2

Atmospheric reanalysis have become an important source of data for weather and climate research, owing to the continuity of the data, but especially because of the multitude of observational data included (radiosondes, commercial aircraft, retrieved data products and radiances). However, the presence of assimilated observations can vary based on numerous factors, and so it is difficult or impossible for a researcher to say with any degree of certainty how many and what type of observations contributed to the reanalysis data they are using at any give point in time or space, or their contribution to the eventual analyzed fields. For example, quality control, transmission interruptions, and station outages can occasionally affect data availability. While orbital paths are known, drift in certain instruments, cloud clearing, and the large number of available instruments makes it challenging to know which satellite is observing any region at any point in the diurnal cycle. Furthermore, there is information from the statistics generated by the data assimilation that can help understand the model and the quality of the reanalysis. Typically, the assimilated observations and their innovations are saved in observation-space data formats and are not easily made available to reanalysis users.Here, we present an early version of a data set has been developed to make the MERRA-2 assimilated observations available for rapid and general use, by simplifying the data format. The observations are binned to a grid similar as MERRA-2 and saved as netCDF. This data collection includes the mean and number of observations in the bin as well as its variance. The data will also include the innovations from the data assimilation, the forecast departure and the analysis increment, as well as bias correction (for satellite radiances). In this paper, we present the data format (called MERRA-2 Gridded Innovations and Observations or GIO) and its strengths and limitations with some initial testing and validation of the methodology.

Bosilovich, Michael G.↗
DOE OSTI2023

A temporal analysis and response to nitrate availability of 3D root system architecture in diverse pennycress (Thlaspi arvense L.) accessions

Introduction Roots have a central role in plant resource capture and are the interface between the plant and the soil that affect multiple ecosystem processes. Field pennycress ( Thlaspi arvense L.) is a diploid annual cover crop species that has potential utility for reducing soil erosion and nutrient losses; and has rich seeds (30-35% oil) amenable to biofuel production and as a protein animal feed. The objective of this research was to (1) precisely characterize root system architecture and development, (2) understand plastic responses of pennycress roots to nitrate nutrition, (3) and determine genotypic variance available in root development and nitrate plasticity. Methods Using a root imaging and analysis pipeline, the 4D architecture of the pennycress root system was characterized under four nitrate regimes, ranging from zero to high nitrate concentrations. These measurements were taken at four time points (days 5, 9, 13, and 17 after sowing). Results Significant nitrate condition response and genotype interactions were identified for many root traits, with the greatest impact observed on lateral root traits. In trace nitrate conditions, a greater lateral root count, length, density, and a steeper lateral root angle was observed compared to high nitrate conditions. Additionally, genotype-by-nitrate condition interaction was observed for root width, width:depth ratio, mean lateral root length, and lateral root density. Discussion These findings illustrate root trait variance among pennycress accessions. These traits could serve as targets for breeding programs aimed at developing improved cover crops that are responsive to nitrate, leading to enhanced productivity, resilience, and ecosystem service.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Taylor approximation variance reduction for approximation errors in PDE-constrained Bayesian inverse problems

In numerous applications, surrogate models are used as a replacement for accurate parameter-to-observable mappings when solving large-scale inverse problems governed by partial differential equations (PDEs). The surrogate model may be a computationally cheaper alternative to the accurate parameter-to-observable mappings and/or may ignore additional unknowns or sources of uncertainty. The Bayesian approximation error (BAE) approach provides a means to account for the induced uncertainties and approximation errors, i.e. the errors between the accurate parameter-to-observable mapping and the surrogate. The statistics of these errors are, however, in general unknown a priori, and are thus calculated using Monte Carlo sampling. Although the sampling is typically carried out offline, i.e. before considering the data, the process can still represent a computational bottleneck. In this work, we develop a scalable computational approach for reducing the costs associated with the sampling stage of the BAE approach. Specifically, we consider the Taylor expansion of the accurate and surrogate forward models with respect to the uncertain parameter fields either as a control variate for variance reduction or as a means to directly and efficiently approximate the mean and covariance of the approximation errors. We propose efficient methods for evaluating the expressions for the mean and covariance of the Taylor approximations based on linear(-ized) PDE solves. Furthermore, the proposed approach is independent of the dimension of the uncertain parameter, depending instead on the intrinsic dimension of the data, ensuring scalability to high-dimensional problems. The potential benefits of the proposed approach are demonstrated for two high-dimensional inverse problems governed by PDE examples, namely for the estimation of a distributed Robin boundary coefficient in a linear diffusion problem, and for a coefficient estimation problem governed by a nonlinear diffusion problem.

Bayesian approximation error↗
NASA NTRS1983

On the role of the seasonal cycle

The definition of the seasonal cycle as the projection of an atmospheric time series onto a suitably defined subset of orthogonal basis functions guarantees that any atmospheric covariance may be expressed as the sum of a seasonal cycle part and a transient part (where transient refers to departures from the seasonal cycle rather than the time mean). Results are presented for the seasonal cycle contribution to the zonally averaged fluxes of momentum and heat, and for the zonally averaged height variance, in data for: the winter season, the winter season with the Fourier basis set appropriate for the seven-year time series, and the seven-year mean. The Fourier basis set calculation indicates that the interannual variability of the momentum flux is dominated by the interactions between the seasonal cycle and the meteorologically low frequency flow.

Straus, D. M.↗
DOE OSTI2019

Turbulent transport and mixing in the multimode narrowband Richtmyer-Meshkov instability

The mean momentum and heavy mass fraction, turbulent kinetic energy, and heavy mass fraction variance fields, as well as the budgets of their transport equations are examined several times during the evolution of a narrowband Richtmyer-Meshkov instability initiated by a Mach 1.84 shock traversing a perturbed interface separating gases with a density ratio of 3. The results are computed using the “quarter scale” data from four algorithms presented in the θ-group study of Thornber et al. [“Late-time growth rate, mixing, and anisotropy in the multimode narrowband Richtmyer-Meshkov instability: The θ-group collaboration,” Phys. Fluids 29, 105107 (2017)]. The present study is inspired by a previous similar study of Rayleigh-Taylor instability and mixing using direct numerical simulation data by Schilling and Mueschke [“Analysis of turbulent transport and mixing in transitional Rayleigh-Taylor unstable flow using direct numerical simulation data,” Phys. Fluids 22, 105102 (2010)]. In addition to comparing the predictions of the data from four implicit large-eddy simulation codes, the budgets are used to quantify the relative importance of the terms in the transport equations, and the balance of the terms is employed to infer the numerical dissipation. Furthermore, terms arising from the compressibility of the flow are examined, in particular the pressure-dilatation. The results are useful for validation of large-eddy simulation and Reynolds-averaged modeling of Richtmyer-Meshkov instability.

42 ENGINEERING↗
DOE OSTI2021

Statistical uncertainties of the v n { 2 k } harmonics from Q cumulants

Analytic formulas to calculate statistical uncertainties of v n { 2 k } harmonics extracted from the Q cumulants are presented. The Q cumulants are multivariate polynomial functions of the weighted means of 2m-particle azimuthal correlations, $\langle\langle 2 m \rangle\rangle$. Variances and covariances of the $\langle\langle 2 m \rangle\rangle$ are included in the analytic formulas of the uncertainties that can be calculated simultaneously with the calculations of the v n { 2 k } harmonics. The calculations are performed using a simple toy model, which roughly simulates elliptic flow azimuthal anisotropy with magnitudes around 0.05. The results are compared with the results obtained by the many data subsets, and by the bootstrapping method. The first one is a common way of estimation of the statistical uncertainties of the v n { 2 k } harmonics in a real experiment. In order to increase precision in the measurement of the v n { 2 k } harmonics, a large number of 15 000 subsets and the same number of the resampling in the bootstrap method is used. Unlike the other ways of the analytic calculation of the v n { 2 k } statistical uncertainties, our proposal that includes the use of squared weights in the calculation of both the variances and covariances, gives the best agreement with the results obtained from the subsets and bootstrap method. Additionally, a recurrence equation between Q cumulants of any order is also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1986

The use of multidate multichannel radiance data in urban feature analysis

Two images were obtained from thematic mappers on Landsats 4 and 5 over the Washington, DC area during November 1982 and March 1984. Selected training areas containing different types of urban land use were examined,one area consisting entirely of forest. Mean digital radiance values for each bandpass in each image were examined, and variances, standard deviations, and covariances between bandpasses were calculated. It has been found that two bandpasses caused forested areas to stand out from other land use types, especially for the November 1982 image. In order to evaluate quantitatively the possible utility of the principal components analysis in selected feature extraction, the eigenvectors were evaluated for principal axes rotations which rendered each selected land use type most separable from all other land use types. The evaluated eigenvectors were plotted as a function of land use type, whose order was decided by considering anticipated shadow component and by examining the relative loadings indicative of vegetation for each of the principal components for the different features considered. The analysis was performed for each seven-band image separately and for the two combined images. It was found that by combining the two images, more dramatic land use type separation could be obtained.

Duggin, M. J.↗
NASA NTRS1990

Accounting for crustal magnetization in models of the core magnetic field

The problem of determining the magnetic field originating in the earth's core in the presence of remanent and induced magnetization is considered. The effect of remanent magnetization in the crust on satellite measurements of the core magnetic field is investigated. The crust as a zero-mean stationary Gaussian random process is modelled using an idea proposed by Parker (1988). It is shown that the matrix of second-order statistics is proportional to the Gram matrix, which depends only on the inner-products of the appropriate Green's functions, and that at a typical satellite altitude of 400 km the data are correlated out to an angular separation of approximately 15 deg. Accurate and efficient means of calculating the matrix elements are given. It is shown that the variance of measurements of the radial component of a magnetic field due to the crust is expected to be approximately twice that in horizontal components.

Jackson, Andrew↗
NASA NTRS1995

Error modeling for differential GPS

Differential Global Positioning System (DGPS) positioning is used to accurately locate a GPS receiver based upon the well-known position of a reference site. In utilizing this technique, several error sources contribute to position inaccuracy. This thesis investigates the error in DGPS operation and attempts to develop a statistical model for the behavior of this error. The model for DGPS error is developed using GPS data collected by Draper Laboratory. The Marquardt method for nonlinear curve-fitting is used to find the parameters of a first order Markov process that models the average errors from the collected data. The results show that a first order Markov process can be used to model the DGPS error as a function of baseline distance and time delay. The model's time correlation constant is 3847.1 seconds (1.07 hours) for the mean square error. The distance correlation constant is 122.8 kilometers. The total process variance for the DGPS model is 3.73 sq meters.

Blerman, Gregory S.↗
NASA NTRS1995

Coronal electron stream and Langmuir wave detection inside a propagation channel at 4.3 AU

Observations of an energetic interplanetary electron event associated with the production of Langmuir waves, both of which are identified at 4.3 AU by instruments on the Ulysses spacecraft, are presented in this paper. This electron event propagates inside a well-defined magnetic structure. The existence of this structure is firmly established by joint particle and plasma observations made by Ulysses instruments. Its local estimated radial width is of the order of 2.3 x 10(exp 7) km (0.15 AU). The electron beam is associated with a type III burst observed from Earth at high frequencies and at low frequencies from Ulysses in association with Langmuir waves detected inside the structure. The consistency of local (Ulysses) and remote (Earth) observations in terms of temporal and geometrical considerations establishes that the structure is anchored in the solar corona near the solar active region responisble for the observed type III emission and gives an accurate determination of the injection time for the observed electron beam. Propagation analysis of the electron event is presented. In order to quantify the magnetic field properties, a variance analysis has been performed and is presented in this paper. The analysis establishes that inside the structure the amount of magnetic energy involved in the fluctuations is less than 4% of the total magnetic energy; the minimal variance direction is well defined and in coincidence with the direction of the mean magnetic field. This configuration may produce conditions favorable for scatter free streaming of energetic electrons and/or Langmuir wave production. The results presented show that the magnetic field might play a role in stabilizing the coronal-origin plasma structures and then preserving them to large, approximately 4 AU, distances in the heliosphere.

Buttighoffer, A.↗
NASA NTRS1996

Planetary Boundary Layer Simulation Using TASS

Boundary conditions to an existing large-eddy simulation model have been changed in order to simulate turbulence in the atmospheric boundary layer. Several options are now available, including the use of a surface energy balance. In addition, we compare convective boundary layer simulations with the Wangara and Minnesota field experiments as well as with other model results. We find excellent agreement of modelled mean profiles of wind and temperature with observations and good agreement for velocity variances. Neutral boundary simulation results are compared with theory and with previously used models. Agreement with theory is reasonable, while agreement with previous models is excellent.

Schowalter, David G.↗
NASA NTRS2008

Baroreflex Sensitivity Decreases During 90-Day Bed Rest

Baroreflex sensitivity (BRS) decreases during spaceflight and simulated spaceflight (head down bed rest [BR]). However, previous studies have only examined BRS in response to a limited blood pressure (BP) range or to a single sudden change in BP. PURPOSE: The purpose of this study was to examine BRS during 90 days of 6deg head-down tilt BR over a broad range of BP perturbations. METHODS: Nineteen normal volunteers (12M, 7F) were tested one day before BR, and then near BR days 30, 60 and 90. BP was pharmacologically altered by continuous infusions of phenylephrine (PE) and sodium nitroprusside (SNP). Electrocardiogram and continuous BP were collected during 10 min of normal saline (NS), followed by increasing concentrations of PE (10 min each of 0.4, 0.8 and 1.6 micro-g/kg/min). After a 20 min break, NS was infused again for 10 min, followed by increasing concentrations of SNP (10 min each of 0.4, 0.8, 1.2 micro-g/kg/min). Baroreceptor sensitivity was measured as the slope of a sequence of 3 or more beats in which the systolic BP and following R-R interval (RR) both increased or decreased. Spectral heart rate variability (HRV) and mean RR were analyzed using data from only the NS infusions. Two-way repeated-measures analysis of variance was performed to examine the effects of BR and gender. RESULTS: RR decreased (p<0.001) from pre- BR across BR days. High frequency in normalized units, a measure of parasympathetic activity, decreased with BR (p=0.027) and was lower (p=0.046) in men (0.39+/-0.02, mean+/-SEM) than women (0.48+/-0.02). The spontaneous baroreflex slope, our measure of BRS, increased with PE and decreased with SNP across BR (p<0.001). The percentage decrease in BRS from pre- to post-BR appeared to be larger in women (43.6+/-7.0%) than in men (31.3+/-3.9%, p=0.06). CONCLUSION: Parasympathetic activity and baroreflex sensitivity decrease during 90 days of BR, and BRS tends to diminish more in women than in men.

Stenger, M. B.↗
NASA NTRS2016

Comparison of Turbulent Thermal Diffusivity and Scalar Variance Models

In this study, several variable turbulent Prandtl number formulations are examined for boundary layers, pipe flow, and axisymmetric jets. The model formulations include simple algebraic relations between the thermal diffusivity and turbulent viscosity as well as more complex models that solve transport equations for the thermal variance and its dissipation rate. Results are compared with available data for wall heat transfer and profile measurements of mean temperature, the root-mean-square (RMS) fluctuating temperature, turbulent heat flux and turbulent Prandtl number. For wall-bounded problems, the algebraic models are found to best predict the rise in turbulent Prandtl number near the wall as well as the log-layer temperature profile, while the thermal variance models provide a good representation of the RMS temperature fluctuations. In jet flows, the algebraic models provide no benefit over a constant turbulent Prandtl number approach. Application of the thermal variance models finds that some significantly overpredict the temperature variance in the plume and most underpredict the thermal growth rate of the jet. The models yield very similar fluctuating temperature intensities in jets from straight pipes and smooth contraction nozzles, in contrast to data that indicate the latter should have noticeably higher values. For the particular low subsonic heated jet cases examined, changes in the turbulent Prandtl number had no effect on the centerline velocity decay.

computational fluid dynamics↗
DOE OSTI2019

IAEA Coordinated Research Project on HTGR Physics, Thermal Hydraulics, and Depletion Uncertainty Analysis: PHISICS/RELAP5-3D Results for the Phase III Coupled Core Exercises

This report details the Parallel and Highly Innovative Simulation for INL Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the neutronics stand-alone core exercises defined for Phase II of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase II models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the propagation of cross-section uncertainties from the lattice to the core calculation (core) phase of the prismatic 350 megawatt (MW) General Atomics (GA) Modular HTGR (MHTGR). The Phase II neutronics exercises consist of two sub-cases (II-2a and II-2b) specified for the fresh and mixed core loading of the MHTGR-350 prismatic high-temperature reactor design. Exercises II-2a and II-2b are performed without temperature feedback using isothermal temperature profiles. For the nominal lattice physics (i.e., best-estimate) model, a series of fresh and depleted single block and super cell SCALE/KENO and SCALE/NEWT models were developed at Idaho National Laboratory (INL) to assess the impact of spectral effects on the few-group cross sections. A combination of these lattice cells were used in a super cell calculation to construct 8-group cross-section libraries for use in the INL-developed PHISICS/RELAP5-3D code suite. The block-level homogenized libraries were assigned to the 220 fuel zones utilized in the MHTGR-350 PHISICS core model, according to the fresh and mixed fresh/depleted core loading pattern. In order to evaluate the effect of uncertainty propagation, several sets consisting of 1,000 perturbed NEWT lattice and PHISICS/RELAP5-3D core calculations were performed using the SCALE 6.2 ENDF/B-VII.1 cross-section co-variance data and the stochastic sampling module Sampler in SCALE 6.2.0. The Figures of Merit (FOM) investigated include the mean and standard deviation uncertainty values obtained for the eigenvalues, control rod worth values, block-averaged power profiles, power axial offsets, and isothermal temperature feedback coefficients. A sensitivity study on the main nuclide reaction contributors to the FOM uncertainties has not yet been performed since the SCALE/PHISICS/RAVEN coupling with ENDF/B-VII co-variance data is still being developed. It was found that uncertainties in the cross sections lead to uncertainties in the local power values of up to 1.5%. The variances between the fresh and mixed/depleted core models are not as large as the axial variations between the top and bottom within each core model. The core eigenvalue uncertainty is approximately 0.5%, which is significant in comparison to typical eigenvalue difference targets (less than ~0.1% for LWRs). The power peaking and axial offset uncertainties are smaller (0.10% – 0.15%) and probably below the level of significance in typical core design metrics. The use of an 8-group energy structure slightly under-estimates some of the uncertainties, but in absolute terms, the uncertainty results are reasonably close to the 26-group results. The 26- and 8-group mean and nominal results differ by a larger degree, and if it can be afforded in terms of calculation resources, the 26-group structure should be used for HTGR calculations. The 8-group structure can, however, still be useful for reasonably accurate uncertainty assessments of transient cases where computational time is important. It was furthermore found that the use of a super cell during the cross-section generation process for better representation of the spectral environment at the core periphery did not lead to significant changes in the core eigenvalues, axial offset, and power peaking uncertainties. The impact of the super cell cross sections on the nominal and mean eigenvalues is, however, important enough (0.6% – 1.1% lower) to justify the use of these super cells for HTGR core simulation to represent the softer spectral environment in the core peripheral regions for nominal best-estimate calculations. The use of super cells for HTGR uncertainty studies is, therefore, not strictly necessary, but the improvements in nominal results could justify their use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Using ground-based lidar data to investigate the water–vapor budget in the daytime atmospheric boundary layer

The moisture advection term in the water–vapor budget equation is investigated with a combination of a vertically-staring water–vapor lidar and Doppler lidar systems. These instruments make it possible to get the mean profile of moisture tendency and the latent heat flux (LHF) divergence. We use data of the Land–Atmosphere Feedback Experiment (LAFE) at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site, Oklahoma, USA, collected on 30 August 2017 between 15 and 24 UTC, which corresponds to 09 to 18 LT. The lidars provide turbulence resolving profiles of moisture and vertical wind fluctuations. The LHF profile is derived from the covariance of these moisture and vertical wind fluctuations. The mean boundary layer height z i is determined from the peak of the moisture variance. The results demonstrate that the combination of two remote sensing instruments can be applied for determining the dominant water–vapor budget terms, namely moisture tendency, latent heat flux divergence and moisture advection.

Advection↗
DOE OSTI2024

A New Coupled Biogeochemical Modeling Approach Provides Accurate Predictions of Methane and Carbon Dioxide Fluxes Across Diverse Tidal Wetlands

Abstract Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO 2 ) and methane (CH 4 ) in tidal wetlands are highly uncertain. While several biogeochemical models can operate in tidal wetlands, they have yet to be parameterized and validated against high‐frequency, ecosystem‐scale CO 2 and CH 4 flux measurements across diverse sites. We paired the Cohort Marsh Equilibrium Model (CMEM) with a version of the PEPRMT model called PEPRMT‐Tidal, which considers the effects of water table height, sulfate, and nitrate availability on CO 2 and CH 4 emissions. Using a model‐data fusion approach, we parameterized the model with three sites and validated it with two independent sites, with representation from the three marine coasts of North America. Gross primary productivity (GPP) and ecosystem respiration (R eco ) modules explained, on average, 73% of the variation in CO 2 exchange with low model error (normalized root mean square error (nRMSE) <1). The CH 4 module also explained the majority of variance in CH 4 emissions in validation sites ( R 2 = 0.54; nRMSE = 1.15). The PEPRMT‐Tidal‐CMEM model coupling is a key advance toward constraining estimates of greenhouse gas emissions across diverse North American tidal wetlands. Further analyses of model error and case studies during changing salinity conditions guide future modeling efforts regarding four main processes: (a) the influence of salinity and nitrate on GPP, (b) the influence of laterally transported dissolved inorganic C on R eco , (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH 4 emissions, and (d) CH 4 responses to non‐periodic changes in salinity.

54 ENVIRONMENTAL SCIENCES↗