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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates

Abstract. We consider the problem of estimating the ensemble sizes required to characterize the forced component and the internal variability of a number of extreme metrics. While we exploit existing large ensembles, our perspective is that of a modeling center wanting to estimate a priori such sizes on the basis of an existing small ensemble (we assume the availability of only five members here). We therefore ask if such a small-size ensemble is sufficient to estimate accurately the population variance (i.e., the ensemble internal variability) and then apply a well-established formula that quantifies the expected error in the estimation of the population mean (i.e., the forced component) as a function of the sample size n, here taken to mean the ensemble size. We find that indeed we can anticipate errors in the estimation of the forced component for temperature and precipitation extremes as a function of n by plugging into the formula an estimate of the population variance derived on the basis of five members. For a range of spatial and temporal scales, forcing levels (we use simulations under Representative Concentration Pathway 8.5) and two models considered here as our proof of concept, it appears that an ensemble size of 20 or 25 members can provide estimates of the forced component for the extreme metrics considered that remain within small absolute and percentage errors. Additional members beyond 20 or 25 add only marginal precision to the estimate, and this remains true when statistical inference through extreme value analysis is used. We then ask about the ensemble size required to estimate the ensemble variance (a measure of internal variability) along the length of the simulation and – importantly – about the ensemble size required to detect significant changes in such variance along the simulation with increased external forcings. Using the F test, we find that estimates on the basis of only 5 or 10 ensemble members accurately represent the full ensemble variance even when the analysis is conducted at the grid-point scale. The detection of changes in the variance when comparing different times along the simulation, especially for the precipitation-based metrics, requires larger sizes but not larger than 15 or 20 members. While we recognize that there will always exist applications and metric definitions requiring larger statistical power and therefore ensemble sizes, our results suggest that for a wide range of analysis targets and scales an effective estimate of both forced component and internal variability can be achieved with sizes below 30 members. This invites consideration of the possibility of exploring additional sources of uncertainty, such as physics parameter settings, when designing ensemble simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Watersheds and stream networks viewed longitudinally: Example insights from novel spatial portrayals of watershed characteristics

Abstract Longitudinal depictions of watershed structure and characteristics, including topography, stream networks, wetlands, ground water levels, and land use, can provide watershed knowledge and understanding unavailable from standard plan view maps. Three case studies provide examples of knowledge gained by applying longitudinal views of stream networks, watershed hydrologic behavior, and land use distributions. Longitudinal views of mountain stream networks show extreme variability in the slope‐area relationships of low Strahler order streams, large discontinuities in drainage area (large parts of drainage area space are absent in networks), and large variations in network curvature. Longitudinal views of a groundwater‐dominated headwater watershed increase the inference available from limited groundwater observations and clearly reveal how groundwater connections affect the permanence of surface water features and the distribution of vadose zone storage in the landscape. Plotting land uses longitudinally illuminates and allows a quantitative analysis of how land uses are distributed relative to topographic position. Viewing watersheds and stream networks longitudinally can provide new insights into watershed forms and processes and motivate new questions and research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-386: Evaluation of EBT3 Film Response in Different Batches

Purpose: To investigate the uniformity of film response of EBT3 film of two different film batches. It has been reported that the response of the EBT film family is not homogenous between film batches. The later may have an impact in the dosimetry of small radiotherapy beams. Methods: A solid water phantom was used for dosimetric measurements. EBT3 film irradiation was performed with a 6 MV photon beam at 5 cm depth with a SAD of 100 cm. All irradiations were performed perpendicularly to the film plane covering the dose range 1 to 10 Gy. Three square field sizes were used to analyze the film response energy dependence: 10, 5 and 1 cm{sup 2}. Two batches of film EBT3 were used #A03181302 (B1) and #03031403 (B2). Film read out was carrying out with an Epson Perfection V750-Pro flatbed scanner in transmission mode with a spatial resolution of 72 dpi, with all post-processing and colour management options turned off, using 48 bits RGB colour depth. The scans were analyzed with the red channel. Results: The results shown that there were differences between the film response for each batch. The differences between batches for 1 Gy were 2%, 6% and 12% for 10, 5 and 1 cm2 square field sizes, respectively. The differences found for 10 Gy were 13%, 14% and 13% for 10, 5 and 1 cm{sup 2} square field sizes, respectively. It can be observed that the dependence with field size dismissed for higher doses. The later may be due to film response saturation at 10 Gy. Conclusion: The EBT3 film -as its predecessors-, it suffer for inter-batch variability in the film response. Further research is required to assess the possible impact in small beam dosimetry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

C/2013 R1 (Lovejoy) at IR wavelengths and the variability of CO abundances among Oort Cloud comets

We report production rates, rotational temperatures, and related parameters for gases in C/2013 R1 (Lovejoy) using the Near InfraRed SPECtrometer at the Keck Observatory, on six UT dates spanning heliocentric distances (R{sub h} ) that decreased from 1.35 AU to 1.16 AU (pre-perihelion). We quantified nine gaseous species (H{sub 2}O, OH*, CO, CH{sub 4}, HCN, C{sub 2}H{sub 6}, CH{sub 3}OH, NH{sub 3}, and NH{sub 2}) and obtained upper limits for two others (C{sub 2}H{sub 2} and H{sub 2}CO). Compared with organics-normal comets, our results reveal highly enriched CO, (at most) slightly enriched CH{sub 3}OH, C{sub 2}H{sub 6}, and HCN, and CH{sub 4} consistent with {sup n}ormal{sup ,} yet depleted, NH{sub 3}, C{sub 2}H{sub 2}, and H{sub 2}CO. Rotational temperatures increased from ∼50 K to ∼70 K with decreasing R{sub h} , following a power law in R{sub h} of –2.0 ± 0.2, while the water production rate increased from 1.0 to 3.9 × 10{sup 28} molecules s{sup –1}, following a power law in R{sub h} of –4.7 ± 0.9. The ortho-para ratio for H{sub 2}O was 3.01 ± 0.49, corresponding to spin temperatures (T {sub spin}) ≥ 29 K (at the 1σ level). The observed spatial profiles for these emissions showed complex structures, possibly tied to nucleus rotation, although the cadence of our observations limits any definitive conclusions. The retrieved CO abundance in Lovejoy is more than twice the median value for comets in our IR survey, suggesting this comet is enriched in CO. We discuss the enriched value for CO in comet C/2013 R1 in terms of the variability of CO among Oort Cloud comets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Generic and robust method for automatic segmentation of PET images using an active contour model

Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies. Methods: MASAC, a method for automatic segmentation using an active contour model, incorporates the histogram fuzzy C-means clustering, and localized and textural information to constrain the active contour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based active contour algorithm (CAC) and Schaefer’s thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively. Results: For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (−8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work with good accuracy, resulting in a mean RE of −13.35% ± 11.87% and −11.15% ± 23.66%, a mean DSC of 0.89 ± 0.05 and 0.71 ± 0.09, and a mean CE of 19.19% ± 7.89% and 53.92% ± 12.65%, for PSs and CSs, respectively. Conclusions: The authors’ results demonstrate that the developed novel PET segmentation algorithm is applicable to various types of lesions in the authors’ study and is capable of producing accurate and consistent target volume delineations, potentially resulting in reduced intraobserver and interobserver variabilities observed when using manual delineation and improved accuracy in treatment planning and outcome evaluation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-14: A Comparison of a 2.5MV Imaging Beam to KV and 6MV Imaging Beams

Purpose: To compare image quality metrics and dose of TrueBeam V2.0’s 2.5MV imaging beam and kV and 6MV images. Methods: To evaluate the MV image quality, the Standard Imaging QC-3 and Varian Las Vegas (LV) phantoms were imaged using the ‘quality’ and ‘low dose’ modes and then processed using RIT113 V6.3. The LEEDS phantom was used to evaluate the kV image quality. The signal to noise ratio (SNR) was also evaluated in patient images using Matlab. In addition, dose per image was evaluated at a depth of 5cm using solid water for a 28.6 cm × 28.6 cm field size, which is representative of the largest jaw settings at an SID of 150cm. Results: The 2.5MV images had lower dose than the 6 MV images and a contrast to noise ratio (CNR) about 1.4 times higher, when evaluated using the QC-3. When energy was held constant but dose varied, the different modes, ‘low dose’ and ‘quality’, showed less than an 8% difference in CNR. The ‘quality’ modes demonstrated better spatial resolution than the ‘low dose’; however, even with the ‘low dose’ all line pairs were distinct except for the 0.75lp/mm on the 2.5MV. The LV phantom was used to measure low contrast detectability and showed similar results to the QC-3. Several patient images all confirmed that SNR were highest in kV images followed by 2.5MV and then 6MV. Qualitatively, for anatomical areas with large variability in thickness, like lateral head and necks, 2.5MV images show more anatomy, such as shoulder position, than kV images. Conclusions: The kV images clearly provide the best image metrics per unit dose. The 2.5MV beam showed excellent contrast at a lower dose than 6MV and may be superior to kV for difficult to image areas that include large changes in anatomical thickness. P Balter: Varian, Sun Nuclear, Philips, CPRIT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Direct Measure of Electrode Spatial Heterogeneity: Influence of Processing Conditions on Anode Architecture and Performance

The spatial (in)homogeneity of aqueous processed silicon electrodes using standard poly(acrylic acid)-based binders and slurry preparation conditions is demonstrated in this work. X-ray nanotomography shows segregation of materials into submicron-thick layers depending on the mixing method and starting binder molecular weights. Using a dispersant, or in situ production of dispersant from the cleavage of the binder into smaller molecular weight species, increases the resulting lateral homogeneity while drastically decreasing the vertical homogeneity as a result of sedimentation and separation due to gravitational forces. This data explains some of the variability in the literature with respect to silicon electrode performance and demonstrates two potential ways to improve slurry-based electrode fabrications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Modeling mechanical behavior of an additively manufactured metal structure with local texture variations: a study on model form error

Here, the repetitive rapid solidification that occurs in metal additive manufacturing (AM) processes creates microstructures distinctly different from wrought materials. Local variability in AM microstructures (either by design or unintentional) raises questions as to how AM structures should be modeled at the part-scale to minimize modeling error. The key goal of this work is to demonstrate a posteriori error estimation applied to an AM part. It is assumed that the actual microstructure is unknown and an approximate, spatially uniform material model is used. Error bounds are calculated for many reference models based on AM microstructures with elongated grain morphology and localized or global fiber textures during a post-processing step. The current findings promote confidence that a posteriori model form error estimation could be used effectively in mechanical performance simulations of AM parts to quickly obtain quantitative error metrics between an approximate model result and many microstructure-based reference models. The a posteriori error estimation introduces significant time savings compared to computing the full reference model solutions. Tight bounds on model form error are obtained when texture variations in the reference models occur on large length scales. For materials with property variation at small length scales, multi-scale error estimation techniques are needed to properly account for the many interfaces present between areas with different properties.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Edge flame structure in a turbulent lifted flame: A direct numerical simulation study

This paper presents here a statistical analysis of edge flames in a turbulent lifted flame using direct numerical simulation (DNS). To investigate the dynamics of edge flames, a theoretical framework describing the edge-flame propagation velocity as a function of propagation velocities of mixture-fraction and product-mass fraction iso-surfaces at the flame base is used. The correlations between these propagation velocities and several other variables are then studied, including iso-surface curvatures, iso-surface orientations, strain rates, scalar dissipation rate and gradients of product mass fraction. The contribution of these parameters to the overall behaviour of the edge flame is also investigated using conditional averaging on two-dimensional spatial locations at the flame base. The analysis reveals that the tangential and normal strain rates in addition to the curvatures and scalar dissipation rates have significant contributions to the overall behaviour of the edge flame. The elliptical motion of the flame base described in our earlier study is extended to provide a clearer picture of how these various parameters affect the large fluctuations of edge-flame velocity observed at the flame base.

42 ENGINEERING↗
DOE OSTI2022

Spatial Trends and Drivers of Bedload and Suspended Sediment Fluxes in Global Rivers

Abstract Bedload is notoriously challenging to measure and model; its dynamics, therefore, remains largely unknown in most fluvial systems worldwide. We present results from a global scale bedload flux model as part of the WBMsed modeling framework that well predict the distribution of water discharge, suspended sediment and bedload. The sensitivity of bedload predictions to river slope, particle size, discharge, river width, and suspended sediment were analyzed, showing the model to be most responsive to spatial dynamics in river discharge and slope. The relationship between bedload and total sediment flux is analyzed globally, and for representative longitudinal river profiles (Amazon, Mississippi, and Lena Rivers). The results show that while the proportion of bedload decreases from headwaters to the coasts, there is considerable variability between basins and along river corridors. The topographic and hydrological longitudinal profiles of rivers are shown to be the key drivers of bedload trends, with fluctuations in slope controlling its more local dynamics. Estimates of water and sediment fluxes to global oceans from 2,067 largest river outlets (draining 67% of the global continental area) are provided. Estimated water discharge at 30,579 km 3 /y corresponds well to past estimates; however, sediment flux is higher. Total global particulate load of 17.8 Gt/y is delivered to global oceans, 14.8 Gt/y as washload, 1.1 Gt/y as bedload, and 2.6 Gt/y as suspended bed material. The largest 25 rivers are predicted to transport more than half of the total sediment flux to global oceans.

Cohen, Sagy↗
DOE OSTI2022

Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

Abstract Using a large suite of Green's function perturbation experiments, we construct the emergent dynamical operator for surface temperature and extract the most excitable mode. The leading mode turns out to be the most dominant mode excited by the climate forcing of doubling CO 2 , alone capturing 56% of the total spatial variances of the surface temperature response. The pattern of the leading mode is partly organized by the atmospheric annular modes in both hemispheres, and further modulated by the feedbacks from ocean circulations. Though derived from a single model, the leading mode can capture the spatio‐temporal variabilities of the global mean surface temperature over the past century in both the CMIP6 model simulations and observations. Moreover, the leading mode is most efficiently excited by radiative forcings from the midlatitude bands centered around 45°N and 25°S, where most human activities take place, suggesting the potency of human influence on the climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Convolutional Neural Networks Trained on Internal Variability Predict Forced Response of TOA Radiation by Learning the Pattern Effect

Abstract Predicting forced, long‐term radiative feedbacks from internal climate variability has been a decades‐long quest in climate science. We train a convolutional neural network (CNN) to predict annual‐ and global‐mean top of the atmosphere radiation anomalies from time‐varying maps of near‐surface temperature in climate models. Trained on internal variability alone, the nonlinear CNN can predict radiation under strong climate change, outperforms a regularized linear regression approach, and works within and across different climate models. We show with explainable artificial intelligence methods that the CNN draws predictive skill from physically meaningful regions but at much smaller spatial scales than currently assumed.

Rugenstein, Maria [Colorado State University Fort ↗
DOE OSTI2020

Climate-Related Trends of Within-Storm Intensities Using Dimensionless Temporal-Storm Distributions

Huff curves are probabilistic time distributions of rainfall expressed as dimensionless cumulative percentages of storm depth and duration. Previous studies have documented development factors, spatial robustness, and the utility of Huff curves in practical applications. However, the effects of trending rainfall on Huff curve intensity patterns have not yet been studied. As such, the goal of this paper is to fill this gap by studying Huff curve patterns in a watershed with demonstrated increasing trends of temperature and precipitation, with the intention that it can be generalized to other areas in the US and the world. To achieve this goal, the high temporal resolution precipitation data collected from a high spatial density, 72-year precipitation-gauge network on the 4.25-km 2 North Appalachian Experimental Watershed in east-central Ohio were used. Seasonal storm pattern trends from 1939 to 2010 were investigated using dimensionless depth (with the frequency of 50%, $d_{50}$) and the curve variability $(V = d_{80} - d_{20})$ at three dimensionless within-storms time periods (three verticals). The Spearman rank correlation procedure (correlation coefficient, ρ and significance probability, p) was used to statistically determine trends over time using 8 periods of 4-season sets of Huff curves over the 72 years. Two averages of ρ and p were computed: (1) by averaging the individual ρ and p obtained from 10 gauges (AvgI); and (2) by grouped averaging of all individual gauge values of $d_{50}$ and V and then computing ρ and p (AvgG). The test results of individual gauges showed that 4 cases for $d_{50}$ and 23 cases for V were significant for all seasons and verticals (total of 120 cases for each variable). The test results of AvgI for $d_{50}$ and V and AvgG for $d_{50}$ showed no significant trends in all seasons and verticals. Only the AvgG for V led to a significant trend for V in spring and fall at different times within storm patterns. The data do not provide sufficient evidence at the p=0.05 significance level to reject the null hypothesis of unchanging position of the dimensionless depth of the 50% Huff curves for individual or averages for all seasons and verticals. Also, there is insufficient evidence to reject the null hypothesis of unchanging variability, V, using the average ρ of individual gauges (AvgI for V) for all seasons and verticals. AvgG results showed a significant trend in V; however, this analysis may be affected by the nonindependence of storm data. The results suggest that it is likely that there is little if any effect of trending climate over approximately 70 years on Huff curve patterns. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Also, individual rain gauge data may not be representative of trends even over small areas, and seasonal differences were noticeable as found in other studies. Recommendations are provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Remote sensing of cytotype and its consequences for canopy damage in quaking aspen

Abstract Mapping geographic mosaics of genetic variation and their consequences via genotype x environment interactions at large extents and high resolution has been limited by the scalability of DNA sequencing. Here, we address this challenge for cytotype (chromosome copy number) variation in quaking aspen, a drought‐impacted foundation tree species. We integrate airborne imaging spectroscopy data with ground‐based DNA sequencing data and canopy damage data in 391 km 2 of southwestern Colorado. We show that (1) aspen cover and cytotype can be remotely sensed at 1 m spatial resolution, (2) the geographic mosaic of cytotypes is heterogeneous and interdigitated, (3) triploids have higher leaf nitrogen, canopy water content, and carbon isotope shifts (δ 13 C) than diploids, and (4) canopy damage varies among cytotypes and depends on interactions with topography, canopy height, and trait variables. Triploids are at higher risk in hotter and drier conditions.

Blonder, Benjamin↗
DOE OSTI2015

Isolating causal pathways between flow and fish in the regulated river hierarchy

Unregulated river systems are organized in a hierarchy in which large-scale factors (i.e., landscape and segment scales) influence local habitats (i.e., reach, meso-, and microhabitat scales), and both differentially exert selective pressures on biota. Dams, however, create discontinua in these processes and change the hierarchical structure. We examined the relative roles of hydrology and other instream factors, within a hierarchical landscape context, in organizing fish communities in regulated and unregulated tributaries to the Upper Tennessee River, USA. We also used multivariate regression trees to identify factors that partition fish assemblages based on trait similarities, irrespective of spatial scale. Then, we used classical path analysis and structural equation modeling to evaluate the most plausible hierarchical causal structure of specific trait-based community components, given the data. Both statistical approaches suggested that river regulation affects stream fishes through a variety of reach-scale variables, not always through hydrology itself. Though we observed different changes in flow, temperature, and biotic responses according to regulation types, the most predominant path in which dam regulation affected biota was via temperature alterations. Diversion dams had the strongest effects on fish assemblages. Diversion dams reduced flow magnitudes, leading to declines in fish richness but increased temperatures, leading to lower abundances in equilibrium species and nest guarders. Peaking and run-of-river dams increased flow variability, leading to lower abundances in nest-guarding fishes. Flow displayed direct relationships with biotic responses; however, results indicated that changes in temperature and substrate had equal, if not stronger, effects on fish assemblage composition. The strength and nature of relationships depended on whether flow metrics were standardized for river size. Here, we suggest that restoration efforts in regulated rivers focus on improving flow conditions in conjunction with temperature and substrate restoration.

58 GEOSCIENCES↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness of Variable Renewable Generation

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an innovative, open-source tool for visualizing variable renewable resource forecasts and alerts for significant up- and down-ramps in renewable generation and the consequent system net load. The modular dashboard of RAVIS contains configurable panes for viewing probabilistic time-series forecasts, ramp event alerts on the look-ahead timeline, and spatially resolved resource sites, and forecasts. For comprehensive situational awareness, the tool can add additional data layers from simulation and independent system operator (ISO) market clearing data---including electric line utilization, nodal price, and available generation flexibility---in response to continuously updated renewable forecasts. This paper introduces the RAVIS technology suite employed to provide optimum visualization and flexible design characteristics. The paper also illustrates some use cases of the tool using site-specific solar power forecast data obtained from the IBM Watt-Sun forecasting platform for the California ISO and Midcontinent ISO footprints. The source code for RAVIS is public (https://github.com/ravis-nrel/ravis), and the intended users are forecasters, utility planners, ISO operators, and researchers.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness of Variable Renewable Generation: Preprint

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an innovative, open-source tool for visualizing variable renewable resource forecasts and alerts for significant up- and down-ramps in renewable generation and the consequent system net load. The modular dashboard of RAVIS contains configurable panes for viewing probabilistic time-series forecasts, ramp event alerts on the look-ahead timeline, and spatially resolved resource sites, and forecasts. For comprehensive situational awareness, the tool can add additional data layers from simulation and independent system operator (ISO) market clearing data—including electric line utilization, nodal price, and available generation flexibility—in response to continuously updated renewable forecasts. This paper introduces the RAVIS technology suite employed to provide optimum visualization and flexible design characteristics. The paper also illustrates some use cases of the tool using site-specific solar power forecast data obtained from the IBM Watt-Sun forecasting platform for the California ISO and Midcontinent ISO footprints. The source code for RAVIS is public (https://github.com/ravis-nrel/ravis), and the intended users are forecasters, utility planners, ISO operators, and researchers.

41 EE - Solar Energy Technologies Office (EE-4S)↗