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At least 883 records · Page 49

Widening of Wind Stress Anomalies Amplifies ENSO in a Warming Climate

Abstract Climate change simulations generally indicate the strengthening of El Niño–Southern Oscillation (ENSO) sea surface temperature (SST) variability through the twenty-first century, yet a robust physical mechanism explaining this change across different models is still lacking, and the projections for ENSO amplitude exhibit a large spread. Most commonly, changes in the background state of the tropical Pacific are invoked to explain these changes of ENSO. Here, we show that changes in the structure of wind stress anomalies associated with ENSO are potentially as important as these background state changes. Specifically, changes in the magnitude, meridional width, and zonal structure of wind stress anomalies can explain approximately 53% of the intermodel variance in the projected change of ENSO magnitude through the twenty-first century as well as 43% in ENSO periodicity changes. Among these changes in the wind structure, the meridional widening of wind anomalies plays the most important role. To demonstrate that these changes are indeed critical, we develop a hybrid model of ENSO based on the Community Earth System Model, version 2, which incorporates a dynamical ocean coupled to a simplified statistical atmosphere within the tropical Pacific. In the absence of external forcing and corresponding mean-state changes, the imposed changes in wind stress anomalies in this hybrid model result in an increase of ENSO amplitudes of nearly 10% along the equator. Our results are also theoretically supported by a recharge-oscillator model that incorporates the meridional wind structure. Thus, changes in the structure of wind stress anomalies, together with changes in the mean state, likely play a critical role in the projected strengthening of ENSO.

Stuivenvolt-Allen, Jacob [Yale University, New Hav↗

Laboratory time series moisture manipulative experiment from sediment across San Antonio, Texas: time series aerobic respiration and geochemistry

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration. The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS Allison Veach collaboration (AV1). The data package associated with the AV1 study is available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2529428. AV1 sampling occurred across 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). This study uses subsamples from a subset of AV1 samples. The original field samples were labeled as AV1_###. Subsequent subsamples for this study were labeled as EV_###. The labels from the field samples and the EV subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EV_001 is a subsample from AV1_001). See the critical details section below for more details on sample naming. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) effect size; (2) iron (II); (3) gravimetric moisture; (4) respiration rates; (5) raw dissolved oxygen values and plots; (6) specific conductance; (7) pH; (8) temperature; (9) a summary containing mean, median, and standard deviation values of each data type for each treatment (wet and dry); and (10) methods codes. All files are .csv or.pdf.

54 ENVIRONMENTAL SCIENCES↗

Monitoring the Urban Heat Island Effect and the Efficacy of Future Countermeasures

To relate fine-scale spatial air-temperature variations in local urban heat islands and urban cool islands—increases and decreases in outside air temperature—within a large urban-climate archipelago to variations in land-use and land-cover properties in the Los Angeles Basin, the research team sought to (a) use fine-resolution meso-urban climate models to identify areas of urban heat and cool islands, select sites for fixed weather monitoring, and choose routes for mobile observations; (b) relate observed intraurban temperature variations to land use and land cover and surface physical properties; and (c) calibrate/validate the climate models. The research team assessed urban temperature variations via simulations and observations, including mobile transects, mesonet, dense networks of personal weather stations, and sparse but more accurate research-grade monitors. To identify the causative factors of the urban heat and cool islands at the neighborhood scale, the research team collected detailed urban morphometric and land use and land cover datasets, such as 1-meter (3.3 foot) resolution roof albedo (solar reflectance) and tree canopy cover. The research team used the observationvalidated model to finalize the transect routes and site the stationary monitors. This study provides the first observational evidence from analysis of high-spatial-density weather stations that increases in roof albedo at neighborhood scale are associated with reductions in near-surface air temperature. This finding was corroborated with the analysis from mobile transect measurements and correlation of observed air temperature with neighborhood-scale albedo and vegetation. This correlation revealed a cooling effect from areawide increase in albedo or canopy cover or both. The calibrated meteorological model accurately identified the localized urban heat and cool islands observed in this study. Interested stakeholders/researchers can use the same models and calibration/validation methodology to characterize within-city microclimate variations elsewhere in California, and can apply them to analyze the benefits from using urban heat island countermeasures. This project report is an extended and more detailed version of a related report prepared for California’s Fourth Climate Change Assessment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Using a Regional Cluster of AmeriFlux Sites in Central California to Advance Our Knowledge on Decadal-Scale Ecosystem-Atmosphere Carbon Dioxide Exchange

Continuous eddy convariance measurements of carbon dioxide, water vapor and heat were measured continuously between an oak savanna and an annual grassland in California over a 4 year period. These systems serve as representative sites for biomes in Mediterranean climates and experience much seasonal and inter-annual variability in temperature and precipitation. These sites hence serve as natural laboratories for how whole ecosystem will respond to warmer and drier conditions. The savanna proved to be a moderate sink of carbon, taking up about 150 gC m-2y-1 compared to the annual grassland, which tended to be carbon neutral and often a source during drier years. But this carbon sink by the savanna came at a cost. This ecosystem used about 100 mm more water per year than the grassland. And because the savanna was darker and rougher its air temperature was about 0.5 C warmer. In addition to our flux measurements, we collected vast amounts of ancillary data to interpret the site and fluxes, making this site a key site for model validation and parameterization. Datasets consist of terrestrial and airborne lidar for determining canopy structure, ground penetrating radar data on root distribution, phenology cameras monitoring leaf area index and its seasonality, predawn water potential, soil moisture, stem diameter and physiological capacity of photosynthesis.

54 ENVIRONMENTAL SCIENCES↗

Novel CO 2 Foam Concepts and Injection Schemes for Improving CO 2 Sweep Efficiency in Sandstone and Carbonate Hydrocarbon Formations

We explored cationic, nonionic and zwitterionic surfactants to identify candidates that have the potential to satisfy all the key requirements for CO 2 foams in EOR. We have examined the formation, texture, rheology and stability of CO 2 foams as a function of the surfactant structure and formulation variables including temperature, pressure, water/CO 2 ratio, surfactant concentration, salinity and concentration of oil. Furthermore, the partitioning of surfactants between oil and water as well as CO 2 and water was examined in conjunction with adsorption measurements on limestone by the Hirasaki lab to develop strategies to optimize the transport of surfactants in reservoirs.

02 PETROLEUM↗

Flow, Mixing and Combustion of Transient Turbulent Gaseous Jets in Confined Cylindrical Geometries

Limitations in both experimental and modeling approaches inhibit the investigation of mixing and combustion in transient reacting jets. Even with heavy experimental effort, temporally resolved measurements to simultaneously assess the flow, mixing and combustion face significant difficulties in resolving the multitude of fast and spatially distributed variables (velocity, temperature and composition of a large number of chemical species) in large domains with spatial resolution sufficient to resolve the smallest scales.

42 ENGINEERING↗

Uranium-hydrogen reaction mechanism and numerical model

We have developed a numerical model to help predict lifetimes of uranium parts in situations where the uranium surface is exposed to hydrogen in the gas headspace. Assessments can be made based on hydrogen pressure and on an upper limit of size of a surface breached hydride spot (volume of hydride corrosion product produced). The model assumes development of a hydride nucleus at a single arbitrary subsurface location associated with an arbitrary surface defect and follows the development of the hydride nucleus to the break-through phase and further growth to the upper limit of acceptable volume of corrosion product. The model has been developed from an understanding of the hydriding mechanism outlined below in 10 steps and measured rates of hydrogen ingress at several types (chemically) of uranium surfaces at ambient temperature and variable pressure. The key points are 1) that the hydrides nucleate only at locations where a surface defect allows hydrogen ingress (reactant delivery) into the uranium metal subsurface (beyond the oxide), and 2) that the hydrides which eventually reach surface break-through status, nucleate and grow in the near surface (few 10s of micron depth maximum) – those beyond ~50 micron have arrested growth and never reach break-through status.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Verification and Validation of High Explosive Reactive Burn Models Implemented in LANL's EAP and LAP Code Base (FY2020 L2 Milestone MRT 7129) [Slides]

Advanced reactive burn models enable phenomena to be modeled that aren’t possible with programmed burn. Programmed burn propagates a burn front at a prescribed speed from a prescribed initiation point. Reactive burn uses the hydro variables (pressure, temperature, etc.) to determine when, how rapidly, and to what extent a zone detonates. This enables a completely new set of problems to be simulated. Our goal in this milestone has been to improve the usability of reactive burn modes. Thus, the closure criteria are: 1. Perform code and solution verification of the reactive burn models using appropriate solutions and simplified HE setups. 2. Perform validation assessments using small-scale experiments. 3. Evaluate sensitivities and quantify uncertainties due to model form variations and mesh dependencies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Nonadiabatic Flamelet Formulation for Predicting Wall Heat Transfer in Rocket Engines

A flamelet-based combustion model is introduced for the prediction of wall heat transfer in rocket engines and confined combustion systems. To account for convective heat loss due to the interaction of the flame with the wall, a permeable thermal boundary condition is introduced in the counterflow diffusion flame configuration. The solution of the resulting nonadiabatic flame structure forms a three-dimensional manifold, which is parameterized in terms of mixture fraction, progress variable, and temperature. The performance of the model is first assessed through a direct numerical simulation analysis of an H 2 /O 2 diffusion flame that is stabilized at an inert isothermal wall. The developed nonadiabatic flamelet model is shown to accurately predict the temperature, chemical composition, and wall heat transfer. Combined with a presumed probability density function closure, the model is then applied to large-eddy simulation of a single-injector rocket combustor to examine effects of heat transfer on the turbulent flame structure in rocket engines.

42 ENGINEERING↗

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗

Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes

As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the uncertainties of the resulting AMO indices and the corresponding spatial patterns derived from three observational SST datasets. We found that the known coherent spatial pattern of the AMO at the basin scale over the North Atlantic appears in two out of the three datasets. Further analysis indicates that both the warming trend and the different techniques used to construct these observed gridded SSTs contribute to the AMO’s spatial coherence over the North Atlantic, especially during periods of sparse data sampling. The SST in the Extended Reconstructed SST dataset version 5 (ERSSTv5), changes from being systematically below the other datasets during the dense sampling periods on either side of the Second World War (WWII), to systematically above the other datasets during WWII, thereby introducing an artificial 10–20-year variability that affects the AMO’s spatial coherence. This coherence in the AMO’s spatial pattern is also affected by bias adjustment in ERSSTv5 at relative cool (i.e., non-summer) seasons, and by the heterogeneous North Atlantic warming pattern. The different AMO patterns can induce the different effects of wind, surface heat fluxes, and then drive ocean circulation and its heat transport convergence, especially for some seasons. For AMO indices, both the different detrending methods and different observational data result in uncertainty for the period 1935–1950. Such SST uncertainty is important to detect the relative role of the atmosphere and ocean in shaping the AMO.

54 ENVIRONMENTAL SCIENCES↗

Predictability and empirical dynamics of fisheries time series in the North Pacific

Previous studies have documented a strong relationship between marine ecosystems and large-scale modes of sea surface height (SSH) and sea surface temperature (SST) variability in the North Pacific such as the Pacific Decadal Oscillation and the North Pacific Gyre Oscillation. In the central and western North Pacific along the Kuroshio-Oyashio Extension (KOE), the expression of these modes in SSH and SST is linked to the propagation of long oceanic Rossby waves, which extend the predictability of the climate system to ~3 years. Using a multivariate physical-biological linear inverse model (LIM) we explore the extent to which this physical predictability leads to multi-year prediction of dominant fishery indicators inferred from three datasets (i.e., estimated biomasses, landings, and catches). We find that despite the strong autocorrelation in the fish indicators, the LIM adds dynamical forecast skill beyond persistence up to 5-6 years. By performing a sensitivity analysis of the LIM forecast model, we find that two main factors are essential for extending the dynamical predictability of the fishery indicators beyond persistence. The first is the interaction of the fishery indicators with the SST/SSH of the North and tropical Pacific. The second is the empirical relationship among the fisheries time series. This latter component reflects stock-stock interactions as well as common technological and human socioeconomic factors that may influence multiple fisheries and are captured in the training of the LIM. These results suggest that empirical dynamical models and machine learning algorithms, such as the LIM, provide an alternative and promising approach for forecasting key ecological indicators beyond the skill of persistence.

60 APPLIED LIFE SCIENCES↗

Editorial: Applications of spectroscopy and chemometrics in nuclear materials analysis

Optical analysis techniques, including spectroscopy and image analysis, have many advantages when applied to the study of nuclear materials. They require small sample sizes, can be performed remotely, and can be proceduralized through consistent practice. Most importantly, they provide a wealth of information by generating multivariate data. For example, ultraviolet–visible–near-infrared absorbance spectroscopy of actinides in aqueous and organic solutions is dependent on the oxidation state, anionic complexation, and temperature. These variables are important for solution-based separation processes, and sensitivity to these factors, combined with online monitoring, can drive the efficiency and control of these processes. The morphology and chemical composition of actinide particles can also provide a vital clue to the mechanisms by which the particles were formed, providing forensic information on the origins of the particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

XMM-Newton X-Ray Observations of LkCa 15: A T Tauri Star with a Formative Planetary System

High-resolution ground-based images of the T Tauri star LkCa 15 have revealed multiple companions that are thought to comprise a formative planetary system. The candidate protoplanets orbit at distances of ∼15–20 au within the dust-depleted inner region of the circumstellar disk. Because of its young age (∼1–4 Myr), LkCa 15 provides a benchmark system for testing planet-formation models. We detected LkCa 15 as a bright X-ray source in a short 10 ks Chandra observation in 2009. We report here new results obtained from a deeper 37 ks XMM-Newton observation in 2014. The new data provide better sampling in the time domain and improved sensitivity at low energies below 1 keV. Spectral fits with thermal emission models require at least two temperature components at kT {sub cool} ≈ 0.4 keV and kT {sub hot} ≈ 2.2 keV. The value of kT {sub hot} is about a factor of two less than inferred from Chandra, suggesting that the hot-component temperature is variable. The best-fit absorption column density is in good agreement with that expected from optical extinction estimates A{sub V} ≈ 1.3–1.7 mag. The intrinsic X-ray luminosity is L {sub x}(0.2–10 keV) = 3 × 10{sup 30} erg s{sup −1}. Estimates of the X-ray heating rate of the inner disk and protoplanets are sensitive to the assumed disk gas surface density for which recent ALMA observations give estimates Σ{sub 0,gas} ∼10{sup 2} g cm{sup −2} at 1 au from the star. At such densities, X-ray heating is confined mainly to the upper disk layers and X-ray penetration through the disk midplane to the protoplanets at r ≈ 15–20 au is negligible.

79 ASTRONOMY AND ASTROPHYSICS↗

Fast, High-fidelity Lyα Forests with Convolutional Neural Networks

Full-physics cosmological simulations are powerful tools for studying the formation and evolution of structure in the universe but require extreme computational resources. Here, we train a convolutional neural network to use a cheaper N-body-only simulation to reconstruct the baryon hydrodynamic variables (density, temperature, and velocity) on scales relevant to the Lyα forest, using data from Nyx simulations. We show that our method enables rapid estimation of these fields at a resolution of ~20 kpc, and captures the statistics of the Lyα forest with much greater accuracy than existing approximations. Because our model is fully convolutional, we can train on smaller simulation boxes and deploy on much larger ones, enabling substantial computational savings. Furthermore, as our method produces an approximation for the hydrodynamic fields instead of Lyα flux directly, it is not limited to a particular choice of ionizing background or mean transmitted flux.

79 ASTRONOMY AND ASTROPHYSICS↗

Kinetic features of xylan de-polymerization in production of xylose monomer and furfural during acid pretreatment for kenaf, forage sorghums and sunn hemp feedstocks

A kinetic study of acid pretreatment was conducted for sorghum non-brown mid rib (SNBMR) ( Sorghum bicolor L Moench ), sorghum-brown mid rib (SBMR), sunn hemp ( Crotalaria juncea L ) and kenaf ( Gossypiumhirsutum L ), focusing on rates of xylose monomer and furfural formation. The kinetics was investigated using two independent variables, reaction temperature (150 and 160°C) and acid concentration (1 and 2 wt%), with a constant dry biomass loading of 10 wt% and a treatment time up to 20 min while sampling the mixture every 2 min. The experimental data were fitted using a two-step kinetic model based on irreversible pseudo first order kinetics at each step. Varied kinetic orders on the acid concentration, ranging from 0.2 to >3, were observed for both xylose and furfural formation, the values depending on the feedstock. The crystallinity index of raw biomass was shown to be a major factor influencing the rate of both xylose and furfural formation. As a result, a positive correlation was observed between the activation energy and biomass crystallinity index for xylose formation.

09 BIOMASS FUELS↗

Closed-loop control of active nematic flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware/software/wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Nishiyama, Katsu [Brandeis Univ., Waltham, MA (Uni↗

The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources

Abstract. Here, computer models are ubiquitous tools used to represent systems across many scientific and engineering domains. For any given system, many computer models exist, each built on different assumptions and demonstrating variability in the ways in which these systems can be represented. This variability is known as epistemic uncertainty, i.e. uncertainty in our knowledge of how these systems operate. Two primary sources of epistemic uncertainty are (1) uncertain parameter values and (2) uncertain mathematical representations of the processes that comprise the system. Many formal methods exist to analyse parameter-based epistemic uncertainty, while process-representation-based epistemic uncertainty is often analysed post hoc, incompletely, informally, or is ignored. In this model description paper we present the multi-assumption architecture and testbed (MAAT v1.0) designed to formally and completely analyse process-representation-based epistemic uncertainty. MAAT is a modular modelling code that can simply and efficiently vary model structure (process representation), allowing for the generation and running of large model ensembles that vary in process representation, parameters, parameter values, and environmental conditions during a single execution of the code. MAAT v1.0 approaches epistemic uncertainty through sensitivity analysis, assigning variability in model output to processes (process representation and parameters) or to individual parameters. In this model description paper we describe MAAT and, by using a simple groundwater model example, verify that the sensitivity analysis algorithms have been correctly implemented. The main system model currently coded in MAAT is a unified, leaf-scale enzyme kinetic model of C 3 photosynthesis. In the Appendix we describe the photosynthesis model and the unification of multiple representations of photosynthetic processes. The numerical solution to leaf-scale photosynthesis is verified and examples of process variability in temperature response functions are provided. For rapid application to new systems, the MAAT algorithms for efficient variation of model structure and sensitivity analysis are agnostic of the specific system model employed. Therefore MAAT provides a tool for the development of novel or toy models in many domains, i.e. not only photosynthesis, facilitating rapid informal and formal comparison of alternative modelling approaches.

54 ENVIRONMENTAL SCIENCES↗