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323 records · Page 18
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An Update on the Hydrological Land Surface Data and Services at NASA GES DISC

"The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth Observing System data centers that document, process, archive and distribute data from Earth science missions and related projects. The GES DISC hosts many hydrological land surface data products including North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and assimilated-Gravity Recovery and Climate Experiment (GRACE). The Land Surface Model (LSM) products contain model output, including heat fluxes, rain, snow, soil temperature, soil moisture and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at the GES DISC ranges from hourly to monthly and the spatial resolution 0.1 degree to 1.0 degree. The variability of Earth’s water and energy cycles can be characterized with these spatially and temporally consistent, and quality controlled hydrological land surface data. These data could support ongoing modeling activities, and help improve our understanding of land-surface-atmosphere interactions and their impact on climate. Over the years, new data is added, and older data is reprocessed and updated. This presentation provides a summary table of the hydrological data and discusses recent updates to the data and data services at the GES DISC. New data products include (1) GRACE Global Version 3.0 drought indicators and (2) FLDAS monthly global and Central Asia daily data. Reprocessed and updated products include (1) NLDAS Version 2.0 and (2) GRACE United States Version 4.0 drought indicators. Lastly, this presentation will discuss the opportunities for accessing some of our hydrology data from the cloud. As the hydrology land surface data is moved to the cloud, users can expect faster service for longer time series, notably the hydrology data rods time series service."

Ashley Heath↗
NASA NTRS2022

Influence of Vegetation on Simulation of the Water Balance and Hydrological Response to El Niño–Southern Oscillation in Western Tropical South America

Land surface models (LSMs) rely on vegetation parameters for use in hydrological and energy balance analysis, monitoring, and forecasting. This study examines the influence that vegetation representation in the Noah-Multiparameterization (Noah-MP) LSM has on hydrological simulations across the diverse climate zones of western tropical South America (WTSA), with specific consideration of hydrological variability associated with El Niño–Southern Oscillation (ENSO). The influence of model representation of vegetation on simulated hydrology is evaluated through three simulation experiments that use 1) satellite-derived constant MODIS; 2) satellite-derived time-varying MODIS; and 3) the Noah-MP dynamic leaf model. We find substantial differences in vegetation fields between these simulations, with the Noah-MP dynamic leaf model diverging significantly from satellite-derived vegetation fields in many ecoregions. Impacts on simulated hydrology were, however, found to be modest across climate zones, except for select extreme events. Also, although impacts on hydrology under ENSO-induced variability were small, we find that the Noah-MP dynamic leaf model simulates a positive relationship between rainfall and vegetation in humid ecoregions of WTSA, where satellite observations may indicate the opposite. The relatively small sensitivity of simulated hydrology to vegetation scheme suggests that the performance of hydrological monitoring and forecasting in WTSA that uses Noah-MP is largely unaffected by the choice of vegetation scheme, such that using a simple climatological default is generally no worse than adopting more complicated options. The presence of some differences between the time-varying and constant MODIS simulations for hydrologic extremes, however, indicates that time-varying MODIS configuration might be more suitable for hydrological hazards applications.

South America↗
NASA NTRS2024

Enabling Advanced Snow Physics within Land Surface Models Through an Interoperable Model-Physics Coupling Framework

Accurate estimation of snow accumulation and melt is a critical part of decision-making in snow-dominated watersheds. In this study, we demonstrate a flexible methodology to couple a detailed snow model, Crocus, separately to two different land surface models (LSMs), Noah-MP and Noah. The original LSMs and the coupled models (Noah-MP-Crocus and Noah-Crocus) are used to simulate snow depth, snow water equivalent, and other water and energy states and fluxes. The results of simulations are compared against a wide range of independent gridded and point scale reference datasets. Our results show that coupling the detailed snow model, Crocus, with the LSMs improves the snow depth and snow water equivalent relative to independent observations. Overall, larger improvements are obtained with coupling Crocus to the Noah LSM, with the coupled Noah-Crocus configuration reducing the RMSE and bias of snow depth from 2-12% and 57-75%, respectively, relative to Snow Data Assimilation System (SNODAS) and snow product from the University of Arizona. On the other hand, smaller improvements are obtained by coupling Crocus with Noah-MP. The Coupled Noah-MP-Crocus reduces the snow depth bias but slightly degrades the RMSE of snow depth and snow water equivalent. The corresponding impacts in other water budget terms such as evapotranspiration, soil moisture, and streamflow, however, are mixed, pointing to the significant need to improve the coupling assumptions of these processes within land models. Overall, the interoperable coupling framework demonstrated here offers the opportunity to include more detailed snow physics and processes, and to advance data assimilation systems through improved exploitation of information from snow remote sensing instruments.

Snow model↗
DOE OSTI2010

SURFACE SEGREGATION STUDIES OF SOFC CATHODES: COMBINING SOFT X-RAYS AND ELECTROCHEMICAL IMPEDENCE SPECTROSCOPY

A system to grow heteroepitaxial thin-films of solid oxide fuel cell (SOFC) cathodes on single crystal substrates was developed. The cathode composition investigated was 20% strontium-doped lanthanum manganite (LSM) grown by pulsed laser deposition (PLD) on single crystal (111) yttria-stabilized zirconia (YSZ) substrates. By combining electrochemical impedance spectroscopy (EIS) with x-ray photoemission spectroscopy (XPS) and x-ray absorption spectroscopy XAS measurements, we conclude that electrically driven cation migration away from the two-phase gas-cathode interface results in improved electrochemical performance. Our results provide support to the premise that the removal of surface passivating phases containing Sr2+ and Mn2+, which readily form at elevated temperatures even in O2 atmospheric pressures, is responsible for the improved cathodic performance upon application of a bias.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2010

Electrochemical characteristics of samaria-doped ceria infiltrated strontium-doped LaMnO3 cathodes with varied thickness for yttria-stabilized zirconia electrolytes

Samaria-doped ceria (SDC) infiltrated into strontium-doped LaMnO3 (LSM) cathodes with varied cathode thickness on yttria-stabilized zirconia (YSZ) were investigated via symmetrical cell, half cell, and full cell configurations. The results of the symmetrical cells showed that the interfacial polarization resistance (RP) decreased with increasing electrode thickness up to∼30m, and further increases in the thickness of the cathode did not cause significant variation of electrode performance. At 800 ◦C, the minimum RP was around 0.05cm2. The impedance spectra indicated that three main electrochemical processes existed, possibly corresponding to the oxygen ion incorporation, surface diffusion of oxygen species and oxygen adsorption and dissociation. The DC polarization on the half cells and characterization of the full cells also demonstrated a similar correlation between the electrode performance and the electrode thickness. The peak power densities of the single cells with the 10, 30, and 50-m thick electrodes were 0.63, 1.16 and 1.11Wcm−2, respectively. The exchange current densities under moderate polarization are calculated and possible rate-determining steps are discussed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2011

Microstructural effects on the oxygen exchange kinetics of La{<_0.7}Sr{<_0.3}MnO{<_3} thin films.

We investigated the relative contribution of the native surface and of the grain boundaries intersecting the surface to the chemical surface exchange of La{sub 0.7}Sr{sub 0.3}MnO{sub 3} (LSM) thin films. The chemical surface exchange coefficients, k{sub chem}, were determined using electrical conductivity relaxation (ECR). Two k{sub chem} values were obtained, indicating two surface exchange processes occurred in parallel. These two k{sub chem} values had different activation energies (Ea), which were interpreted as belonging to (1) the native surface response of individual grains/variants and (2) the variant/grain boundaries of the textured films. The first process has an activation energy of E{sub a,1} {approx} 1.57 eV, while E{sub a,2} {approx} 0.87 eV. The k{sub chem,2} values are almost 3 orders of magnitude higher than the k{sub chem,1} values at low temperatures. At higher temperatures, the data can be fit with one k{sub chem} that has an intermediate value of Ea, indicative of a transition region.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Microorganisms having enhanced tolerance to inhibitors and stress

The present invention provides genetically modified strains of microorganisms that display enhanced tolerance to stress and/or inhibitors such as sodium acetate and vanillin. The enhanced tolerance can be achieved by increasing the expression of a protein of the Sm-like superfamily such as a bacterial Hfq protein and a fungal Sm or Lsm protein. Further, the present invention provides methods of producing alcohol from biomass materials by using the genetically modified microorganisms of the present invention.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Effect of Feed Composition on Cold-Cap Formation in Laboratory-Scale Melter

The development of advanced glass formulations are a part of the plan for reducing the cost and time for treatment and vitrification of the 210,000 m3 of nuclear waste at the Hanford Site in southeastern Washington State. One property of interest in this development is melt viscosity, which has a decisive influence on the rate of glass production. In an electric melter, the conversion process from feed-to-glass above the melt pool occurs in the cold cap. At the final stage of conversion when the glass-forming melt becomes connected, gas evolving reactions cause foaming. The melt viscosity affects foam stability. Three glasses were formulated with viscosities of 1.5, 3.5, and 9.5 Pa s at 1150°C by varying the SiO2 content at the expense of B2O3, Li2O, and Na2O kept at constant proportions. Cold caps were produced by charging simulated high-alumina, high-level waste feeds in a laboratory-scale melter (LSM). The spread of the feed on the cold cap during charging and the cross-sectional structure of the final cold caps were compared. The amount of the foam and the size of the bubbles increased as the viscosity increased.

Cold Cap↗
DOE OSTI2017

Effect of Silica Particle Size of Nuclear Waste-to-Glass Conversion - 17319

The process for converting nuclear waste-to-glass in an electric melter occurs in the cold cap, a crust of reacting solids floating on the glass pool. As the melter feed (a mixture of the nuclear waste and glass forming and modifying additives) heats up in the cold cap, glass-forming reactions ensue, causing the feed matrix to connect, trapping reaction gases to create a foam layer. The foam layer reduces the rate of melting by separating the reacting feed from the melt pool. The size of the silica particle additives in the melter feed affects melt viscosity and, hence, foam stability. To investigate this effect, seven nuclear waste simulant feeds of a high-level waste were batched as slurries and prepared with dissimilar ranges of silica particle size. Each slurry feed was charged into a laboratory-scale melter (LSM) to produce a cold cap and the propensity of feeds to foam was determined by pressing dried feeds into pellets and monitoring the change of pellet volume in response to heating. Two of these slurries were designed to have dissimilar glass viscosities at 1150°C. In the low temperature region of the cold cap, before the melter feed connects, the feeds without fine silica particles behaved similar to the high viscosity feed as their volume contracted while the feed with silica particles no larger than 5 µm reacted like the low viscosity feed. However, the feed volume similarities reversed as the feed connected and expanded through the foam region of the cold cap.

Cold Cap↗
DOE OSTI2020

Sensitivity Study for Forecasting Variables of WRF-Solar Using a Tangent Linear Approach

Integrating solar generation in recent years has highlighted the need for improved accuracy in predicting solar power. Confidence in solar power forecasting can be achieved by designing an ensemble that provides reliable probabilistic information for solar radiation with reduced uncertainty and error. Ideally, ensemble members are created through the optimized perturbation of the initial conditions in numerical weather prediction (NWP) models. Tangent linear models are capable of efficiently investigating the sensitivity of solar radiation to model input parameters because they do not require individual perturbation of each variable. This sensitivity study using tangent linear models provide us the capability to identify the right variables to perturb in an ensemble prediction system. In this study, we developed tangent linear models for WRF-Solar modules that directly impact the computation of solar radiation and the simulation of cloud formation and dissipation including the Fast All-sky Model for Solar Applications (FARMS), the Noah land surface model (LSM), the Thompson microphysics, the Mello-Yamada-Nakanishi-Niino (MYNN) boundary layer parameterization, and the Deng scheme for a shallow-convection parameterization. A sensitivity analysis was conducted under various scenarios based on satellite observations and model simulations from the National Solar Radiation Data Base (NSRDB) and WRF-Solar, respectively. Critical forecasting variables that are highly sensitive to the forecasting of global horizontal irradiance (GHI), direct normal irradiance (DNI), cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes were determined using the relevant WRF-Solar module. This study will be used as a guidance on future research leading to high-quality probabilistic solar forecasting. In this presentation, we discuss the validation of tangent linear approach for WRF-Solar modules and illustrate how the sensitivity results are valuable in the improvement of probabilistic solar prediction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Effect of Silica Particle Size on Nuclear Waste-to-Glass Conversion - 17319

The process for converting nuclear waste-to-glass in an electric melter occurs in the cold cap, a crust of reacting solids floating on the glass pool. As the melter feed (a mixture of the nuclear waste and glass forming and modifying additives) heats up in the cold cap, glass-forming reactions ensue, causing the feed matrix to connect, trapping reaction gases to create a foam layer. The foam layer reduces the rate of melting by separating the reacting feed from the melt pool. The size of the silica particle additives in the melter feed affects melt viscosity and, hence, foam stability. To investigate this effect, seven nuclear waste simulant feeds of a high-level waste were batched as slurries and prepared with dissimilar ranges of silica particle size. Each slurry feed was charged into a laboratory-scale melter (LSM) to produce a cold cap and the propensity of feeds to foam was determined by pressing dried feeds into pellets and monitoring the change of pellet volume in response to heating. Two of these slurries were designed to have dissimilar glass viscosities at 1150 deg. C. In the low temperature region of the cold cap, before the melter feed connects, the feeds without fine silica particles behaved similar to the high viscosity feed as their volume contracted while the feed with silica particles no larger than 5 μm reacted like the low viscosity feed. However, the feed volume similarities reversed as the feed connected and expanded through the foam region of the cold cap. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗
DOE OSTI2014

Structural model of an mRNA in complex with the bacterial chaperone Hfq

The Sm-like protein Hfq (host factor Q-beta phage) facilitates regulation by bacterial small noncoding RNAs (sRNAs) in response to stress and other environmental signals. In this paper, we present a low-resolution model of Escherichia coli Hfq bound to the rpoS mRNA, a bacterial stress response gene that is targeted by three different sRNAs. Selective 2'-hydroxyl acylation and primer extension, small-angle X-ray scattering, and Monte Carlo molecular dynamics simulations show that the distal face and lateral rim of Hfq interact with three sites in the rpoS leader, folding the RNA into a compact tertiary structure. These interactions are needed for sRNA regulation of rpoS translation and position the sRNA target adjacent to an sRNA binding region on the proximal face of Hfq. Finally, our results show how Hfq specifically distorts the structure of the rpoS mRNA to enable sRNA base pairing and translational control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Unraveling the Role of Transport, Electrocatalysis, and Surface Science in the Solid Oxide Fuel Cell Cathode Oxygen Reduction Reaction

This final report for project FE0009656 covers the period from 10/01/2012 to 09/30/2015 and covers research accomplishments on the effects of carbon dioxide on the surface composition and structure of cathode materials for solid oxide fuel cells (SOFCs), specifically La1-xSrxFeyCo1- yO3-δ (LSCF). Epitaxially deposited thin films of LSCF on various single-crystal substrates have revealed the selective segregation of strontium to the surface thereby resulting in a surface enrichment of strontium. The near surface compositional profile in the films have been measured using total x-ray fluorescence (TXRF), and show that the kinetics of strontium segregation are higher at higher partial pressures of carbon dioxide. Once the strontium segregates to the surface, it leads to the formation of precipitates of SrO which convert to SrCO3 in the presence of even modest concentrations of carbon dioxide in the atmosphere. This has important implications for the performance of SOFCs which is discussed in this report. These experimental observations have also been verified by Density Functional Theory calculations (DFT) which predict the conditions under which SrO and SrCO3 can occur in LSCF. Furthermore, a few cathode compositions which have received attention in the literature as alternatives to LSCF cathodes have been studied in this work and shown to be thermodynamically unstable under the operating conditions of the SOFCs.

25 ENERGY STORAGE↗