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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Coherent Streamflow Variability in Monsoon Asia Over the Past Eight Centuries—Links to Oceanic Drivers

The Monsoon Asia region is home to ten of the world’s biggest rivers, supporting the lives of 1.7 billion people who rely on streamflow for water, energy, and food. Yet, a synoptic understanding of multi-centennial streamflow variability for this region is lacking. Here we produce the first large scale streamflow reconstruction over Monsoon Asia (63 stations in 16 countries), using a novel climate-informed dynamic algorithm that is skillful over 92% of the gauging stations. In this work, we show that streamflow in Monsoon Asia is spatially coherent, owing to common drivers from the Pacific, Indian, and Atlantic Oceans that exert their greatest influence over the Mekong and Chao Phraya basins. This work increases our understanding of streamflow variability over Monsoon Asia. We suggest that future water management in the region should be coordinated between basins, taking into account the states of the oceans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Pacific Tropical Decadal Variability Challenge for Climate Models

Understanding and forecasting Tropical Pacific Decadal-scale Variability (TPDV) strongly rely on climate model simulations. Using a Linear Inverse Modeling (LIM) diagnostic approach, we reveal Coupled Model Intercomparison Project Phase 6 models have significant challenges in reproducing the spatial structure and dominant mechanisms of TPDV. Specifically, while the models' ensemble mean pattern of TPDV resembles that of observations, the spread across models is very large and most models show significant differences from observations. In observations, removing the coupling between extratropics and tropics reduces TPDV by ~60%–70%, and removing the tropical thermocline variability makes the central tropical Pacific a key center of action for TPDV and El Niño Southern Oscillation variability. These characteristics are only confirmed in a subset of models. Differences between observations and simulations are outside the range of natural internal TPDV noise and pose important questions regarding our ability to model the impacts of natural internal low-frequency variability superimposed on long-term climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Numerical algorithms for water waves with background flow over obstacles and topography

Abstract We present two accurate and efficient algorithms for solving the incompressible, irrotational Euler equations with a free surface in two dimensions with background flow over a periodic, multiply connected fluid domain that includes stationary obstacles and variable bottom topography. One approach is formulated in terms of the surface velocity potential while the other evolves the vortex sheet strength. Both methods employ layer potentials in the form of periodized Cauchy integrals to compute the normal velocity of the free surface, are compatible with arbitrary parameterizations of the free surface and boundaries, and allow for circulation around each obstacle, which leads to multiple-valued velocity potentials but single-valued stream functions. We prove that the resulting second-kind Fredholm integral equations are invertible, possibly after a physically motivated finite-rank correction. In an angle-arclength setting, we show how to avoid curve reconstruction errors that are incompatible with spatial periodicity. We use the proposed methods to study gravity-capillary waves generated by flow around several elliptical obstacles above a flat or variable bottom boundary. In each case, the free surface eventually self-intersects in a splash singularity or collides with a boundary. We also show how to evaluate the velocity and pressure with spectral accuracy throughout the fluid, including near the free surface and solid boundaries. To assess the accuracy of the time evolution, we monitor energy conservation and the decay of Fourier modes and compare the numerical results of the two methods to each other. We implement several solvers for the discretized linear systems and compare their performance. The fastest approach employs a graphics processing unit (GPU) to construct the matrices and carry out iterations of the generalized minimal residual method (GMRES).

Ambrose, David M.↗
DOE OSTI2024

The National Climate Data Base (NCDB): A Bias-Corrected High-Resolution Climate Dataset

Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.

climate data↗
DOE OSTI2024

The National Climate Database (NCDB): An Unbiased 100-Year Dataset for PV Modeling

In this study, we develop a statistical technique to downscale the future projection of solar irradiance for photovoltaics (PV) energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the downscaling method, a summary of the 100-year dataset from 2001-2100, and future extension of this research.

bias correction↗
DOE OSTI2022

Dryness controls temperature-optimized gross primary productivity across vegetation types

Temperature response of gross primary productivity (GPP) is a well-known property of ecosystem, but GPP at the optimum temperature (GPP_T opt ) has not been fully discussed. Our understanding of how GPP_T opt responds to warming and water availability is highly limited. Here, in this study, we analyzed data at 326 globally distributed eddy covariance sites (79°N-37°S), to identify controlling factors of GPP_T opt . Although GPP_T opt was significantly influenced by soil moisture, global solar radiation, mean annual temperature, and vapor pressure deficit in a non-linear pattern (R 2 = 0.47), the direction and magnitude of these climate variables’ effects on GPP_T opt depend on the dryness index (DI), a ratio of potential evapotranspiration to precipitation. The spatial pattern showed that soil moisture did not affect GPP_T opt across energy-limited sites with DI < 1 while dominated GPP_T opt across water-limited sites with DI >1. The temporal pattern showed that GPP_T opt was lowered by warming or low precipitation in water-limited sites while energy-limited sites tended to maintain a stable GPP_T opt regardless of changes in air temperature. Vegetation types in humid climates tended to have higher GPP_T opt and were more likely to benefit from a warmer climate since it was not restricted by water conditions. This study highlights that the response of GPP_T opt to global warming depends on the dryness conditions, which explains the nonlinear control of water and temperature over GPP_T opt . Our finding is essential to realistic prediction of terrestrial carbon uptake under future climate and vegetation conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite-derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above-ground biomass. The adjusted simulation significantly reduced the above-ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation-constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring the interplay between distributed wind generators and solar photovoltaic systems

This study investigates the spatial and temporal dynamics of wind and solar energy generation across the continental United States, focusing on energy availability, reliability, variability, and cooperation. Using data from the National Renewable Energy Laboratory, we analyze the performance of wind turbines and photovoltaic systems, revealing distinct patterns in energy production and reliability. The classification of wind and solar zones based on energy availability and reliability provides valuable insights for renewable energy planning and grid integration strategies. Overall, this methodology contributes to understanding wind and solar interactions, which will lead to informing effective renewable energy deployment and grid integration efforts.

14 SOLAR ENERGY↗
DOE OSTI2020

A Bezier Curve Informed Melt Pool Geometry to Model Additive Manufacturing Microstructures Using SPPARKS

Additive manufacturing is a transformative technology with the potential to manufacture designs which traditional subtractive machining methods cannot. Additive manufacturing offers fast builds at near final desired geometry; however, material properties and variability from part to part remain a challenge for certification and qualification of metallic components. AM induced metallic microstructures are spatially heterogeneous and highly process dependent. Engineering properties such as strength and toughness are significantly affected by microstructure morphologies resulting from the manufacturing process Linking process parameters to microstructures and ultimately to the dynamic response of AM materials is critical to certifying and qualifying AM built parts and components and improving the performance of AM materials. The AM fabrication process is characterized by building parts layer by layer using a selective laser melt process guided by a computer. A laser selectively scans and melts metal according to a designated geometry. As the laser scans, metal melts, fuses, and solidifies forming the final geometry in a layerwise fashion. As the laser heat source moves away, the metal cools and solidifies forming metallic microstructures. This work describes a microstructure modeling application implemented in the SPPARKS kinetic Monte Carlo computational framework for simulating the resulting microstructures. The application uses Bzier curves and surfaces to model the melt pool surface and spatial temperature profile induced by moving the laser heat source; it simulates the melting and fusing of metal at the laser hot spot and microstructure formation and evolution when the laser moves away. The geometry of the melt pool is quite flexible and we explore effects of variances in model parameters on simulated microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of Multi-Fidelity Soil Moisture Products Across the Continental United States

We have aggregated the most recent soil moisture datasets from a diverse range of sources, encompassing the Continental United States (CONUS). These sources encompass gridded data from remote sensing products, reanalysis products, machine learning-based projects, and land surface modeling products. Additionally, we have obtained and processed in-situ soil moisture observations from the International Soil Moisture Network. The collected datasets exhibit variations in both temporal and spatial resolutions. Among the 20 datasets, six are available at a spatial resolution of 0.25 degrees, while three are at a coarser spatial resolution of 25 km. To minimize spatial interpolation, we conducted data uncertainty evaluations at the 0.25-degree spatial resolution. For our data evaluations, we maintained a monthly temporal resolution, which effectively captures soil moisture seasonality and interannual variability. Our data processing strategy preserves the raw data and interpolated data at their original temporal resolutions. Datasets with higher temporal resolutions, including daily, three-hourly, and hourly datasets, are set aside for subsequent analyses. These analyses will delve into topics such as soil moisture changes and recovery during extreme weather events. Furthermore, we have processed auxiliary data to enhance our evaluation, leveraging tools such as Google Earth Engine. This includes incorporating topography data, land use land cover data, Köppen-Geiger climate classification, and more to provide a comprehensive assessment from multiple sources.

Li, Lingcheng↗
DOE OSTI2021

Exploring the Grid Value of Offshore Wind Energy in Oregon

The significant offshore wind energy potential of Oregon faces several challenges, including a power grid which was not developed for the purpose of transmitting energy from the ocean. The grid impacts of the energy resource are considered through the lenses of (i) resource complementarity with Variable Renewable Energy resources; (ii) correlations with load profiles from the four balancing authorities with territory in Oregon; and (iii) spatial value to regional and coastal grids as represented through a production cost model of the Western Interconnection. The capacity implications of the interactions between offshore wind and the historical east-to-west power flows of the region are discussed. The existing system is shown to accommodate more than two gigawatts of offshore wind interconnections with minimal curtailment. Through three gigawatts of interconnection, transmission flows indicate a reduction of coastal and statewide energy imports as well as minimal statewide energy exports.

17 WIND ENERGY↗
DOE OSTI2021

Changes in Future Precipitation Mean and Variability across Scales

Changes in precipitation variability can have large societal consequences, whether at the short time scales of flash floods or the longer time scales of multiyear droughts. Recent studies have suggested that in future climate projections, precipitation variability rises more steeply than does its mean, leading to concerns about societal impacts. Here we evaluate changes in mean precipitation over a broad range of spatial and temporal scales using a range of models from high-resolution regional simulations to millennial-scale global simulations. Results show that changes depend on the scale of aggregation and involve strong regional differences. On local scales that resolve individual rainfall events (hours and tens of kilometers), changes in precipitation distributions are complex and variances rise substantially more than means, as is required given the well-known disproportionate rise in precipitation intensity. On scales that aggregate across many events, distributional changes become simpler and variability changes smaller. At regional scale, future precipitation distributions can be largely reproduced by a simple transformation of present-day precipitation involving a multiplicative shift and a small additive term. The “extra” broadening is negatively correlated with changes in mean precipitation: in strongly “wetting” areas, distributions broaden less than expected from a simple multiplicative mean change; in “drying” areas, distributions narrow less. Precipitation variability changes are therefore of especial concern in the subtropics, which tend to dry under climate change. Outside the tropics, variability changes are similar on time scales from days to decades (i.e., show little frequency dependence). This behavior is highly robust across models, suggesting it may stem from some fundamental constraint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Verification Suite of Test Cases for the Barotropic Solver of Ocean Models

Abstract The development of any atmosphere or ocean model warrants a suite of test cases (TCs) to verify its spatial and temporal discretizations, order of accuracy, stability, reproducibility, portability, scalability, etc. In this paper, we present a suite of shallow water TCs designed to verify the barotropic solver of atmosphere and ocean models. These include the non‐dispersive coastal Kelvin wave; the dispersive inertia‐gravity wave; the dispersive planetary and topographic Rossby waves; the barotropic tide; and a non‐linear manufactured solution. These TCs check the implementation of the linear pressure gradient term; the linear constant or variable‐coefficient Coriolis and bathymetry terms; and the non‐linear advection terms. Simulation results are presented for a variety of time‐stepping methods as well as two spatial discretizations: a mimetic finite volume method based on the TRiSK scheme, and a high‐order discontinuous Galerkin spectral element method. The experimental procedure for conducting these numerical experiments is detailed. It underscores several key considerations that vary depending on the chosen spatial discretization method. Finally, convergence studies of every TC are conducted with refinement in both space and time, only in space, and only in time. The convergence slopes match the expected theoretical predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Probing the γ -Ray Emission Origin of Two Star-forming Galaxies NGC 2403 and NGC 3424 with the Fermi-LAT

Star-forming galaxies (SFGs) are a subclass of γ-ray emitters, and a correlation between their γ-ray luminosity (L γ ) and the total infrared (IR) luminosity (L IR ) has been established based on the Fermi Large Area Telescope (LAT) data. NGC 2403 and NGC 3424 have been reported as outliers in the L γ –L IR correlation with light curves showing significant variability, which contrasts with the temporally stable γ-ray emission in other SFGs, originating primarily from cosmic rays interacting with interstellar medium. In this study, we reanalyze the γ-ray emission in the directions of NGC 2403 and NGC 3424 using more than 16.5 yr Fermi-LAT data. NGC 3424 is found to be spatially coincident with the detected γ-ray source, while NGC 2403 is significantly offset from the nearest γ-ray source, suggesting an implausible association. We confirm the previously reported variability of both γ-ray sources and the significant deviation from the L γ –L IR correlation when assuming an association of both γ-ray sources with the two galaxies. Our findings lend further support to the interpretation that their γ-ray emission is driven primarily by alternative radiative processes—rather than by star formation activity—such as the ejecta of the Type IIP supernova SN 2004dj in NGC 2403 interacting with a surrounding high-density shell and an obscured active galactic nucleus in NGC 3424.

Liu, Linjie [Chinese Academy of Sciences (CAS), Ku↗
DOE OSTI2022

Middle to Late Holocene Sea Surface Temperature and Productivity Changes in the Northeast Pacific

Variations of the sea surface temperature (SST) and primary productivity in the northeast Pacific have far‐reaching implications. In addition to influencing the regional and global temperature and hydroclimate, these conditions also control marine ecosystems and their services, which subsequently impact regional economies. Yet, our understanding of the variability and controls of northeast Pacific SST and productivity on timescales exceeding observational records remains limited. Here, we use marine sediment records from seven locations, spanning 25.2°N–59.6°N, in the northeast Pacific to characterize the millennial‐scale variability of SST and productivity from 9,000 to 1,000 years BP. We explore the dynamics of their spatiotemporal evolution and compare these data with transient climate model outputs to identify potential drivers. Through a heat budget analysis and optimal fingerprinting analysis, we characterize the spatial pattern of forcings. We find that SST varied spatially in the northeast Pacific, with higher latitudes exhibiting greater magnitude changes than lower latitudes, which differs from previous work suggesting regional synchronicity and coherence during the Holocene. Our analysis did not find evidence for coherent variability of primary producer community nor carbon export, highlighting the difficulty of identifying the complex interactions between environmental conditions, producers, and carbon export. Model‐proxy disagreement demonstrates the need for higher resolution model frameworks, but shows nonetheless that observed variability in the proxy records can be explained by a combination of greenhouse gas and orbital forcing. Here we suggest that the complex SST variations and marine ecosystem responses to forced changes are important factors that can drive disagreements in model projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

In-situ qualification and physics-based process design for aerosol jet printing via spatially correlated light scattering measurements

Aerosol jet printing is a contactless, digital, and additive technique broadly used for manufacturing flexible, hybrid, and conformal electronics. However, batch-to-batch variability has hindered widespread industry adoption and scaling to production volumes. Recently, light scattering measurements have emerged as a tool to measure aerosol volume fraction – a key parameter determining deposition rate – and have proven an effective feedback source for closed loop control on timescales ranging from minutes to hours. Here, the efficacy of light scattering measurements as a tool for in-situ qualification over shorter time durations is explored. To be the linear relationship between light scattering measurements and deposition rate was validated at 500 ms time intervals, allowing deposition rate to be mapped to positional coordinates and providing a new data stream to drive quality control assessments. Because light scattering measurements are indicative of a physical process parameter, they were substituted into equations for resistance and sheet resistance, resulting in predictions nominally within 10% of measured values for sets of printed devices. Finally, to highlight a more active utility, light scattering measurements were employed in a print repair framework, successfully repairing prints with randomly induced defects to within 5% of the measured resistance of a control set.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation

Geologic Disposal Safety Assessment Framework is a state-of-the-art simulation software toolkit for probabilistic post-closure performance assessment of systems for deep geologic disposal of nuclear waste developed by the United States Department of Energy. This paper presents a generic reference case and shows how it is being used to develop and demonstrate performance assessment methods within the Geologic Disposal Safety Assessment Framework that mitigate some of the challenges posed by high uncertainty and limited computational resources. Variance-based global sensitivity analysis is applied to assess the effects of spatial heterogeneity using graph-based summary measures for scalar and time-varying quantities of interest. Behavior of the system with respect to spatial heterogeneity is further investigated using ratios of water fluxes. This analysis shows that spatial heterogeneity is a dominant uncertainty in predictions of repository performance which can be identified in global sensitivity analysis using proxy variables derived from graph descriptions of discrete fracture networks. New quantities of interest defined using water fluxes proved useful for better understanding overall system behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗