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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Can the angular scale of cosmic homogeneity be used as a cosmological test?

Abstract In standard cosmology, the cosmic homogeneity scale is the transition scale above which the patterns arising from non-uniformities – such as groups and clusters of galaxies, voids, and filaments – become indistinguishable from a random distribution of sources. Recently, different groups have investigated the feasibility of using such a scale as a cosmological test and arrived at different conclusions. In this paper, we complement and extend these studies by exploring the evolution of the spatial ( $$R_{\textrm{H}}$$ R H ) and angular ( $$\theta _{\textrm{H}}$$ θ H ) homogeneity scales with redshift, assuming a spatially flat, $$\varLambda $$ Λ -Cold Dark Matter universe and linear cosmological perturbation theory. We confirm previous results concerning the non-monotonicity of $$R_{\textrm{H}}$$ R H with the matter density parameter $$\varOmega _{\textrm{m0}}$$ Ω m0 but also show that it exhibits a monotonical behavior with the Hubble constant $$H_{0}$$ H 0 within a large redshift interval. More importantly, we find that, for $$z \gtrsim 0.6$$ z ≳ 0.6 , $$\theta _{\textrm{H}}$$ θ H presents a monotonical behavior with $$\varOmega _{\textrm{m0}}$$ Ω m0 , as well as for $$H_0$$ H 0 the entire redshift interval analyzed. We find also that the angular homogeneity scale is sensitive to $$H_{0}$$ H 0 , especially at higher redshifts. Using the currently available $$\theta _{\textrm{H}}$$ θ H measurements, we illustrate the constraints on the $$\varOmega _{\textrm{m0}}$$ Ω m0 – $$H_{0}$$ H 0 plane through a MCMC analysis and show the feasibility of using the angular homogeneity scale as a new, model-independent way to constrain cosmological parameters.

Physics↗
DOE OSTI2024

Approaching Angstrom-Scale Resolution in Lithography Using Low-Molecular-Mass Resists (<500 Da)

Resists that enable high-throughput and high-resolution patterning are essential in driving the semiconductor technology forward. The ultimate patterning performance of a resist in lithography is limited because of the trade-off between resolution, line-width roughness, and sensitivity; improving one or two of these parameters typically leads to a loss in the third. As the patterned feature sizes approach angstrom scale, the trade-off between these three metrics becomes increasingly hard to resolve and calls for a fundamental rethinking of the resist chemistry. Low-molecular-mass monodispersed metal-containing resists of high atom economy can provide not only very high resolution but also very low line-width roughness without sacrificing sensitivity. Here we describe a modular metal-containing resist platform (molecular mass <500 Da) where a molecular resist consists of just two components: a metal and a radical initiator bonded to it. This simple system not only is amenable to high-resolution electron beam lithography (EBL) and extreme ultraviolet lithography (EUVL) but also unites them mechanistically, giving a consolidated perspective of molecular and chemical processes happening during exposure. Irradiation of the resist leads to the production of secondary electrons that generate radicals in the initiator bonded to metal. This brings about an intramolecular rearrangement and causes solubility switch in the exposed resist. We demonstrate record 1.9–2.0 nm isolated patterns and 7 nm half-pitch dense line-space features over a large area using EBL. With EUVL, 12 nm half-pitch line-space features are shown at a dose of 68 mJ/cm 2 . In both of these patterning techniques, the line-width roughness was found to be ≤2 nm, a record low value for any resist platform, also leading to a low-performance trade-off metric, Z factor, of 0.6 × 10 –8 mJ·nm 3 . With the ultimate resolution limited by instrumental factors, potential patterning at the level of a unit cell can be envisaged, making low-molecular-mass resists best poised for angstrom-scale lithography.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Detecting Coastal Wetland Degradation by Combining Remote Sensing and Hydrologic Modeling

Sea-level rise and climate change stresses pose increasing threats to coastal wetlands that are vital to wildlife habitats, carbon sequestration, water supply, and other ecosystem services with global significance. However, existing studies are limited in individual sites, and large-scale mapping of coastal wetland degradation patterns over a long period is rare. Our study developed a new framework to detect spatial and temporal patterns of coastal wetland degradation by analyzing fine-scale, long-term remotely sensed Normalized Difference Vegetation Index (NDVI) data. Then, this framework was tested to track the degradation of coastal wetlands at the Alligator River National Wildlife Refuge (ARNWR) in North Carolina, United States, during the period from 1995 to 2019. We identified six types of coastal wetland degradation in the study area. Most of the detected degradation was located within 2 km from the shoreline and occurred in the past five years. Further, we used a state-of-the-art coastal hydrologic model, PIHM-Wetland, to investigate key hydrologic processes/variables that control the coastal wetland degradation. The temporal and spatial distributions of simulated coastal flooding and saltwater intrusion confirmed the location and timing of wetland degradation detected by remote sensing. The combined method also quantified the possible critical thresholds of water tables for wetland degradation. The remote sensing–hydrologic model integrated scheme proposed in this study provides a new tool for detecting and understanding coastal wetland degradation mechanisms. Our study approach can also be extended to other coastal wetland regions to understand how climate change and sea-level rise impact wetland transformations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Comparative Model Evaluation Studies of Biogenic Trace Gas Fluxes in Tropical Forests

Simulation modeling can play a number of important roles in large-scale ecosystem studies, including synthesis of patterns and changes in carbon and nutrient cycling dynamics, scaling up to regional estimates, and formulation of testable hypotheses for process studies. Recent comparative studies have shown that ecosystem models of soil trace gas exchange with the atmosphere are evolving into several distinct simulation approaches. Different levels of detail exist among process models in the treatment of physical controls on ecosystem nutrient fluxes and organic substrate transformations leading to gas emissions. These differences are is in part from distinct objectives of scaling and extrapolation. Parameter requirements for initialization scalings, boundary conditions, and time-series driven therefore vary among ecosystem simulation models, such that the design of field experiments for integration with modeling should consider a consolidated series of measurements that will satisfy most of the various model requirements. For example, variables that provide information on soil moisture holding capacity, moisture retention characteristics, potential evapotranspiration and drainage rates, and rooting depth appear to be of the first order in model evaluation trials for tropical moist forest ecosystems. The amount and nutrient content of labile organic matter in the soil, based on accurate plant production estimates, are also key parameters that determine emission model response. Based on comparative model results, it is possible to construct a preliminary evaluation matrix along categories of key diagnostic parameters and temporal domains. Nevertheless, as large-scale studied are planned, it is notable that few existing models age designed to simulate transient states of ecosystem change, a feature which will be essential for assessment of anthropogenic disturbance on regional gas budgets, and effects of long-term climate variability on biosphere-atmosphere exchange.

Potter, C. S.↗
NASA NTRS2016

GEM-CEDAR Challenge: Poynting Flux at DMSP and Modeled Joule Heat

Poynting flux into the ionosphere measures the electromagnetic energy coming from the magnetosphere. This energy flux can vary greatly between quiet times and geomagnetic active times. As part of the Geospace Environment Modeling-coupling energetics and dynamics of atmospheric regions modeling challenge, physics-based models of the 3-D ionosphere and ionospheric electrodynamics solvers of magnetosphere models that specify Joule heat and empirical models specifying Poynting flux were run for six geomagnetic storm events of varying intensity. We compared model results with Poynting flux values along the DMSP-15 satellite track computed from ion drift meter and magnetic field observations. Although being a different quantity, Joule heat can in practice be correlated to incoming Poynting flux because the energy is dissipated primarily in high latitudes where Poynting flux is being deposited. Within the physics-based model group, we find mixed results with some models overestimating Joule heat and some models agreeing better with observed Poynting flux rates as integrated over auroral passes. In contrast, empirical models tend to underestimate integrated Poynting flux values. Modeled Joule heat or Poynting flux patterns often resemble the observed Poynting flux patterns on a large scale, but amplitudes can differ by a factor of 2 or larger due to the highly localized nature of observed Poynting flux deposition that is not captured by the models. In addition, the positioning of modeled patterns appear to be randomly shifted against the observed Poynting flux energy input. This study is the first to compare Poynting flux and Joule heat in a large variety of models of the ionosphere.

Rastaetter, Lutz↗
NASA NTRS2013

Development of National Future Extreme Heat Scenario to Enable the Assessment of Climate Impacts on Public Health

The project's emphasis is on providing assessments of the magnitude, frequency and geographic distribution of EHEs to facilitate public health studies. We focus on the daily to weekly time scales on which EHEs occur, not on decadal-scale climate changes. There is, however, a very strong connection between air temperature patterns at the two time scales and long-term climatic changes will certainly alter the frequency of EHEs.

Quattrochi, Dale A.↗
NASA NTRS2019

Significant Spatial Variability in Radar-Derived West Antarctic Accumulation Linked to Surface Winds and Topography

Across the Antarctic Ice Sheet, accumulation heavily influences firn compaction and surface height changes. Therefore, accumulation varies over short distances (<25 km), complicating the derivation of ice sheet mass changes from altimetry and reducing how accurately field measurements can be spatially extrapolated. However, current atmospheric reanalyses have grid spacings (>25 km) that are too coarse to resolve this variability. To address this limitation, we construct a fine-scale accumulation product from airborne snow radar observations by superimposing along-track fluctuations in accumulation onto an atmospheric reanalysis product. Our resulting airborne product reflects large-scale (>25 km) orographic precipitation patterns while providing robust and unprecedented insight into Antarctic accumulation variability on subgrid scales. On these smaller scales, we find significant, regionally dependent accumulation variability (𝜎(sub relative) > 40%). This variability in accumulation is correlated with variability in topographic surface slope in the wind direction (p < 0.01), confirming that subgrid-scale accumulation variability is driven by snow redistribution by wind.

Dattler, Marissa E.↗
NASA NTRS1988

Observation of airplane flow fields by natural condensation effects

In-flight condensation patterns can illustrate a variety of airplane flow fields, such as attached and separated flows, vortex flows, and expansion and shock waves. These patterns are a unique source of flow visualization that has not been utilized previously. Condensation patterns at full-scale Reynolds number can provide useful information for researchers experimenting in subscale tunnels. It is also shown that computed values of relative humidity in the local flow field provide an inexpensive way to analyze the qualitative features of the condensation pattern, although a more complete theoretical modeling is necessary to obtain details of the condensation process. Furthermore, the analysis revealed that relative humidity is more sensitive to changes in local static temperature than to changes in pressure.

Campbell, James F.↗
DOE OSTI2026

Subseasonal Forecasting and MJO Teleconnections in Machine Learning Weather Prediction Models

Abstract In recent years, machine‐learning (ML) models trained on reanalysis data have rivaled physics‐based forecast models in terms of performance skill for global weather forecasting. With increased rollout stability, the question of how these models perform for subseasonal to seasonal (S2S, week 3–8) forecasting has emerged. In this study we run a large set of subseasonal hindcasts over 2004–2023 to evaluate two ML weather forecast models at the S2S time scale, SFNO‐HENS (Nvidia, fully ML) and NeuralGCM (Google Research, hybrid). Corresponding hindcasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) are used as a baseline for comparison to a physics‐based model. Because our focus is on predicting moisture transport over the Western United States between October and March, we evaluate the models' prediction skill for the Madden‐Julian Oscillation (MJO) and its associated teleconnections in the North Pacific. We find that both ML models are competitive with the ECWMF model, with comparable skill in predicting the North Pacific large‐scale circulation and the MJO at week 3 and beyond. Even though overall the mid‐latitude subseasonal prediction skill remains low, the ML models exhibit interesting behavior such as a realistic propagation of the MJO across the Maritime Continent and realistic teleconnections. A SFNO‐HENS sensitivity experiment with altered initial conditions in the tropics demonstrates the stability of the model, and it illustrates the capability of ML models to represent important physical processes of the atmosphere at the S2S time scale. Plain Language Summary Predicting weather patterns and precipitation a few weeks in advance (subseasonal time scale) is of great interest for stakeholders such as water managers in the Southwest United States (US), where arid conditions prevail. Subseasonal forecasts from traditional weather forecast models exhibit low skill in the region, limiting their applicability. Here we examine whether the recent breakthrough in weather forecasting made with machine learning/artificial intelligence models can translate to improved subseasonal forecasts. Recently‐developed machine learning models exhibit comparable skill to a state‐of‐the‐art physics‐based model for predicting weather patterns in the North Pacific/North America region, and associated moisture transport. The same applies to their skill in predicting the tropical pattern, the Madden‐Julian Oscillation, and its important remote perturbations over the midlatitude East Pacific and Southwest US. Additionally, a perturbation experiment carried out with one of the machine learning models illustrates their ability to not only predict the evolution of atmospheric fields, but also to learn and represent physical processes such as tropics‐extratropics Rossby wave propagation. Key Points Two machine learning weather forecast models exhibit state‐of‐the‐art prediction skill at the subseasonal time scale in the Pacific sector The models equal ECWMF in terms of Madden‐Julian oscillation (MJO) prediction skill, and they accurately predict the MJO propagation and associated teleconnections The two machine‐learning models represent key physical processes for subseasonal prediction, despite being trained for weather forecasting

Peings, Yannick↗
NASA NTRS1992

Global aspects of the Los Alamos general circulation model hydrologic cycle

The global hydrologic cycle in the Los Alamos general circulation model (GCM) is compared to available global observations. Global observations of the water vapor, water-vapor flux and water-vapor flux divergence are derived from the National Meteorological Center's final analysis for the period 1986-1989. The new precipitation data set of Legates and Willmott (1990) is used for the global precipitation observations. Global evaporation is derived as a residual of the precipitation and water-vapor flux divergence. There are a number of similarities as well as discrepancies between the GCM and observations. The large-scale nondivergent and divergent GCM circulations are remarkably similar to the observed circulations; the large-scale GCM precipitation and evaporation patterns are also qualitatively similar to observations. Discrepancies are mainly quantitative and small-scale in nature: the GCM atmosphere is relatively dry which results in a slightly greater evaporation and precipitation rate than is observed; the GCM South Pacific convergence zone is displaced too far to the northwest.

Roads, J. O.↗
NASA NTRS2002

Global Precipitation Analyses at Monthly to 3-HR Time Scales

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropica1 Rainfall Measuring Mission) tropical data set. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1deg latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will soon be available for the entire TRMM period (January 1998- present). A real-time version of this merged product is being produced and is available at 0.25deg latitude-longitude resolution over the latitude range from 50degN-50degS. Images from this data set can be seen at the U.S. TRMM web site (trmm.gsfc.nasa.gov). Examples will be shown, including its use in monitoring flood conditions and relating weather-scale events to climate variations.

Adler, Robert F.↗
DOE OSTI2024

Within‐field soil moisture variability and time‐invariant spatial structures of agricultural fields in the US Midwest

Abstract Understanding soil moisture variability and estimating high‐resolution soil moisture at subfield to field scales is critical for agricultural research and applications. However, systematic investigation of subfield scale soil moisture variability over cropland is still lacking from both measurement and satellite remote sensing. In this study, we aim to investigate (1) the characteristics of within‐field soil moisture distribution over typical cropland in the US Midwest and (2) the capabilities of satellite remote sensing in capturing the spatiotemporal variabilities of soil moisture at subfield scale. Specifically, we conducted soil moisture field experiments in three typical commercial agricultural fields (∼85 acres per field) in central Illinois, representing typical commercial farmlands in the US Midwest, and compared the soil moisture measurements with satellite remote sensing data from optical and active microwave sensors. In each field, dense soil moisture samples (spaced at 50–60 m) were obtained for two dry down events in May and July 2021, and multiple long‐term soil moisture stations were installed. We found prominent time‐invariant spatial structures of soil moisture at within‐field scales both during the dry down period and over longer time scales, and the stability is minimally affected by plant water use during the growing season. Comparing the field campaign measurements with satellite remote sensing data, we found that surface reflectance of shortwave infrared bands, such as SWIR1 (1610 nm) from Sentinel‐2, can capture relative surface soil moisture patterns at within‐field scales, but their relationships with soil moisture are field specific. These findings and the improved understanding of within‐field soil moisture dynamics could potentially help future research on high‐resolution soil moisture estimation with multi‐source remote sensing data.

Yang, Yi↗
NASA NTRS1992

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Michaels, Anthony F.↗
DOE OSTI2022

Wickability-optimized textured liquid-desiccant air dehumidifiers for independent moisture management in energy-efficient buildings

Liquid-desiccant-based air conditioning systems are envisioned to enable independent humidity management, thereby improving the energy efficiency of future buildings. Existing liquid-desiccant-based air conditioning concepts, however, suffer from a poor liquid flow distribution deteriorating moisture removal rate. They are consequently flooded with the liquid-desiccant solution, which significantly degrades the energy efficiency of the dehumidification process. Here, in this work, the capillary forces and wickability effect of textured air dehumidifier surfaces are altered to minimize the liquid-desiccant flow rate of the fully wetted state, thereby transforming the physics of interfacial desiccant flow distribution. Consequently, the wickability-optimized air dehumidifier surface maximizes both moisture removal rate and dehumidification energy efficiency. It was interestingly found that the length scale of a textured air dehumidifier surface concept is optimized at an intermediate pattern density. Dry solid-air menisci appear at length scales exceeding the optimum pattern distance while the effective liquid–air interfacial area is reduced at smaller length scales, both of which degrade the moisture removal rate. At the optimum pattern density, the effective liquid–air interfacial area increases with the solution flow rate, thereby increasing the dehumidification rate. At a water vapor pressure potential of 3 kPa and a solution flow rate of 2.8 g/s, experimental results indicated a moisture removal rate of 0.16 g/m2-s for a textured surface concept with a capillary length scale of 3 mm, a 28% improvement compared with that of smooth-plate dehumidifier surfaces. A high moisture removal rate of the textured surface at a low desiccant flow rate led to a high thermal efficiency of 0.75 at a water vapor pressure potential of 5.6 kPa and a LiBr flow rate of 2.8 g/s. The insights gained from the present study accelerate the development of advanced textured surface concepts for next-generation liquid-desiccant-based air dehumidification systems offering independent humidity management for future energy-efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1975

Stream pattern analysis using optical processing of ERTS imagery of Kansas

A spatial frequency analysis was carried out to obtain large-scale geologic and other ground pattern spatial frequency and orientational data from an optical data processing system using Earth Resources Technology Satellite-1 (ERTS-1) imagery of Kansas as input. The Diffraction Pattern Sampling Unit (DPSU) of the optical data processing system consists of a photodiode array containing 32 wedge-shaped photodiodes and 32 annular ring diodes. The curve obtained from the intensity distribution of the frequency spectrum yielded by the ring diodes gives the spatial frequency contributions due to ground features on the image. The curve obtained from the wedge-shaped diodes indicates the orientation of features in the sample area. Ten sample sites were used for each of eight geologic-physiographic regions. Comparison of ERTS-1 images with their respective spatial frequency and orientational curves reveals that preferred orientations of drainage produce recognizable peaks.

Mccauley, J.↗
DOE OSTI2020

Controlling Drug Absorption, Release, and Erosion of Photopatterned Protein Engineered Hydrogels

A protein-engineered triblock copolymer hydrogel composed of two self-assembling domains (SADs) has been fabricated by a photoactivatable diazirine group followed by ultraviolet (UV)-mediated crosslinking. The photocrosslinkable protein polymer CEC-D has been patterned into various features including different micrometer-scale stripes by using lithographic techniques. The patterned hydrogels are important for encapsulation of small molecules where a photopatterned fraction of 50% is optimal for maximum absorption. Stripe-patterned CEC-D 100–100 exhibits slightly lower swelling ratios, an 8.9 times lower erosion profile, and a 2.6-fold higher drug release compared to the unpatterned hydrogel control, CEC-D0. Our studies demonstrate the potential of photocrosslinkable protein polymer hydrogels to be used as scaffolds for therapeutic delivery of small molecules. Furthermore, through photolithographic techniques on the protein hydrogel, a variety of functionalities can be achieved by patterning different features enabling the mimicry of biological systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Characteristics of Precipitation and Mesoscale Convective Systems Over the Peruvian Central Andes in Multi 5‐Year Convection‐Permitting Simulations

Abstract Using the Weather Research and Forecasting model with two planetary boundary layer schemes, ACM2 and MYNN, convection‐permitting model (CPM) regional climate simulations were conducted for a 6‐year period, including a one‐year spin‐up period, at a 15‐km grid spacing covering entire South America and a nested convection‐permitting 3‐km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4‐km simulation covering South America produced by National Center for Atmospheric Research (NCAR), three gridded precipitation products, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and mesoscale convective systems (MCSs) in the Peruvian central Andes region. Results show that all km‐scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3‐km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4‐km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low‐level jet and terrain‐induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests model improvements and better model configurations for future regional climate projections.

Meteorology & Atmospheric Sciences↗