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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Precipitation processes developed during TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999): 3D Cloud Resolving Model Simulation

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research (NCAR), NOAA GFDL, the U.K. Met. Office, Colorado State University and NASA Goddard Space Flight Center. An improved 3D Goddard Cumulus Ensemble (GCE) model was recently used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (september 1-7, 1974), SCSMEX (May 18-26, June 2-11, 1998) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 by 512 km domain and 41 vertical layers. The major objectives of this paper are: (1) to identify the differences and similarities in the simulated precipitation processes and their associated surface and water energy budgets in TOGA COARE, GATE, KWAJEX, and SCSMEX, and (2) to asses the impact of microphysics, radiation budget and surface fluxes on the organization of convection in tropics.

Tao, W.-K.↗
DOE OSTI2022

Modeling the Electronic Absorption Spectra of the Indocarbocyanine Cy3

Accurate modeling of optical spectra requires careful treatment of the molecular structures and vibronic, environmental, and thermal contributions. The accuracy of the computational methods used to simulate absorption spectra is limited by their ability to account for all the factors that affect the spectral shapes and energetics. The ensemble-based approaches are widely used to model the absorption spectra of molecules in the condensed-phase, and their performance is system dependent. The Franck–Condon approach is suitable for simulating high resolution spectra of rigid systems, and its accuracy is limited mainly by the harmonic approximation. In this work, the absorption spectrum of the widely used cyanine Cy3 is simulated using the ensemble approach via classical and quantum sampling, as well as, the Franck–Condon approach. The factors limiting the ensemble approaches, including the sampling and force field effects, are tested, while the vertical and adiabatic harmonic approximations of the Franck–Condon approach are also systematically examined. Our results show that all the vertical methods, including the ensemble approach, are not suitable to model the absorption spectrum of Cy3, and recommend the adiabatic methods as suitable approaches for the modeling of spectra with strong vibronic contributions. We find that the thermal effects, the low frequency modes, and the simultaneous vibrational excitations have prominent contributions to the Cy3 spectrum. The inclusion of the solvent stabilizes the energetics significantly, while its negligible effect on the spectral shapes aligns well with the experimental observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

On the Influence of North Pacific Sea Surface Temperature on the Arctic Winter Climate

Differences between two ensembles of Goddard Earth Observing System Chemistry-Climate Model simulations isolate the impact of North Pacific sea surface temperatures (SSTs) on the Arctic winter climate. One ensemble of extended winter season forecasts is forced by unusually high SSTs in the North Pacific, while in the second ensemble SSTs in the North Pacific are unusually low. High Low differences are consistent with a weakened Western Pacific atmospheric teleconnection pattern, and in particular, a weakening of the Aleutian low. This relative change in tropospheric circulation inhibits planetary wave propagation into the stratosphere, in turn reducing polar stratospheric temperature in mid- and late winter. The number of winters with sudden stratospheric warmings is approximately tripled in the Low ensemble as compared with the High ensemble. Enhanced North Pacific SSTs, and thus a more stable and persistent Arctic vortex, lead to a relative decrease in lower stratospheric ozone in late winter, affecting the April clear-sky UV index at Northern Hemisphere mid-latitudes.

Hurwitz, Margaret M.↗
DOE OSTI2019

A probabilistic assessment of geomechanical reservoir integrity during CO 2 sequestration in flood basalt formations

Recent field experiments in Iceland and Washington State (USA) show that basalt formations may be favorable targets for carbon capture and sequestration (CCS) because CO 2 mineralization reactions proceed rapidly. These results imply that there is tremendous opportunity for implementing CCS in large igneous provinces. However, the magnitude of this opportunity comprises commensurate levels of uncertainty because basalt reservoirs are characterized by highly heterogeneous, fracture-controlled hydraulic properties. This geologic uncertainty is propagated as parametric uncertainty in quantitative risk models, thus limiting the efficacy of models to predict CCS performance attributes, such as reservoir integrity and storage potential. To overcome these limitations, here we present a stochastic approach for quantifying the geomechanical performance attributes of CCS operations in a highly heterogeneous basalt reservoir. We utilize geostatistical reservoir characterization to develop an ensemble of equally probable permeability distributions in a flood basalt reservoir with characteristics of the Wallula Basalt Pilot Project. We then simulate industrial-scale CO 2 injections within the ensemble and calculate the mean and variance of fluid pressure over a 1-year injection period. These calculations are combined with the state of stress in southeast Washington State to constrain the spatial extent at which shear failure, fracture initiation, and borehole breakdown may occur. Results from this study show that (i) permeability uncertainty alone causes injection pressure to vary over 25 MPa, (ii) shear failure is likely to occur at 7 times greater distances from the injection than the CO 2 migrates, and (iii) joint initiation pressures are localized within the volume comprising the CO 2 plume.

03 NATURAL GAS↗
DOE OSTI2025

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗
NASA NTRS2021

The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations

The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

Last Glacial Maximum↗
DOE OSTI2021

Joint CO 2 Mole Fraction and Flux Analysis Confirms Missing Processes in CASA Terrestrial Carbon Uptake Over North America

Terrestrial biosphere models (TBMs) play a key role in the detection and attribution of carbon cycle processes at local to global scales and in projections of the coupled carbon-climate system. TBM evaluation commonly involves direct comparison to eddy-covariance flux measurements. This study uses atmospheric CO 2 mole fraction ([CO 2 ]) measured in situ from aircraft and tower, in addition to flux-measurements from summer 2016 to evaluate the CASA TBM. WRF-Chem is used to simulate [CO 2 ] using biogenic CO 2 fluxes from a CASA parameter-based ensemble and CarbonTracker version 2017 (CT2017) in addition to transport and CO 2 boundary condition ensembles. The resulting “super ensemble” of modeled [CO 2 ] demonstrates that the biosphere introduces the majority of uncertainty to the simulations. Both aircraft and tower [CO 2 ] data show that the CASA ensemble net ecosystem exchange (NEE) of CO 2 is biased high (NEE too positive) and identify the maximum light use efficiency E max a key parameter that drives the spread of the CASA ensemble in summer 2016. These findings are verified with flux-measurements. The direct comparison of the CASA flux ensemble with flux-measurements confirms missing sink processes in CASA. Separating the daytime and nighttime flux, we discover that the underestimated net uptake results from missing sink processes that result in overestimation of respiration. NEE biases are smaller in the CT2017 posterior biogenic fluxes, which assimilates observed [CO 2 ]. Flux tower analyses, however, reveal an unrealistic overestimation of nighttime respiration in CT2017 due to the limitation of inversion strategy.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

damage assessment↗
DOE OSTI2019

Projected Changes to Extreme Precipitation Along North American West Coast From the CESM Large Ensemble

Precipitation events along the North American (NA) west coast are strongly modulated by atmospheric rivers, yet the mechanisms of their influences on the probability distributions of precipitation events are not well studied. Simulations from the Community Earth System Model (CESM) large ensemble under global warming are investigated using a moisture budget conditioned onto precipitation events for the recurrence intervals ranging from 0.1 to 50 years. In the midlatitudes, the increases in precipitation intensity and accumulation for all events over the NA west coast are predominantly controlled by moisture increases. In contrast, changes in the subtropical precipitation distributions in southwestern NA are associated with moisture increases and duration decreases for all events, with additional dynamical amplification for the heaviest precipitation events. These interpretations from the conditional moisture budget are more consistent with future projection of atmospheric rivers than the conventional mean and transient decomposition of the moisture budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Selecting representative geological realizations to model subsurface CO 2 storage under uncertainty

Carbon capture and storage (CCS) is one of the quickest and most effective solutions for reducing carbon emissions. The majority of subsurface storage occurs in saline aquifers, for which geological information is lacking which in turn results in geological uncertainty. To evaluate uncertainty in CO 2 injection projections, the use of multiple geological realizations (GRs) has been practiced very commonly. In this approach, hundreds or thousands of high-resolution GRs is used that quickly becomes computationally expensive. This issue can be addressed with representative geological realizations (RGRs) that preserve the uncertainty domain of the ensemble GRs. Here, in this study, we propose the use of unsupervised machine learning (UML) frameworks, including dissimilarity measurement, dimensionality reduction, clustering and sampling algorithms ta select a predetermined number of RGRs. We compare the simulation outputs of the RGR sets and the ensemble using the Kolmogorov–Smirnov (KS) test to select the best UML. The UML frameworks and their associated selection processes are evaluated using a saline aquifer with a single CO 2 injection well and 200 GRs with varying uncertain petrophysical characteristics. The best UML framework is selected to use only 5% of the GRs while maintaining the uncertainty domain of the ensemble GRs. In addition, the best UML framework is tested using a saline aquifer with three CO 2 injection wells and varied GRs. The results show that our proposed UML framework can be used to choose RGRs, capturing the whole uncertainty domain. Our approach leads to a significant reduction in the computational cost associated with scenario testing, decision-making, and development planning for CO 2 storage sites under geological uncertainty.

58 GEOSCIENCES↗
NASA NTRS2003

Simulated KWAJEX Convective Systems Using a 2D and 3D Cloud Resolving Model and Their Comparisons with Radar Observations

The 1999 Kwajalein Atoll field experiment (KWAJEX), one of several major TRMM (Tropical Rainfall Measuring Mission) field experiments, has successfully obtained a wealth of information and observation data on tropical convective systems over the western Central Pacific region. In this paper, clouds and convective systems that developed during three active periods (Aug 7-12, Aug 17-21, and Aug 29-Sep 13) around Kwajalein Atoll site are simulated using both 2D and 3D Goddard Cumulus Ensemble (GCE) models. Based on numerical results, the clouds and cloud systems are generally unorganized and short lived. These features are validated by radar observations that support the model results. Both the 2D and 3D simulated rainfall amounts and their stratiform contribution as well as the heat, water vapor, and moist static energy budgets are examined for the three convective episodes. Rainfall amounts are quantitatively similar between the two simulations, but the stratiform contribution is considerably larger in the 2D simulation. Regardless of dimension, fo all three cases, the large-scale forcing and net condensation are the two major physical processes that account for the evolution of the budgets with surface latent heat flux and net radiation solar and long-wave radiation)being secondary processes. Quantitative budget differences between 2D and 3D as well as between various episodes will be detailed.Morover, simulated radar signatures and Q1/Q2 fields from the three simulations are compared to each other and with radar and sounding observations.

Shie, Chung-Lin↗
DOE OSTI2021

The Fingerprints of Stratospheric Aerosol Injection in E3SM

The June 15, 1991 Mt. Pinatubo eruption is simulated in E3SM by injecting 10 Tg of SO 2 gas in the stratosphere, turning off prescribed volcanic aerosols, and enabling E3SM to treat stratospheric volcanic aerosols prognostically. This experimental prognostic treatment of volcanic aerosols in the stratosphere results in some realistic behaviors (SO 2 evolves into H 2 SO 4 which heats the lower stratosphere), and some expected biases (H 2 SO 4 aerosols sediment out of the stratosphere too quickly). Climate fingerprinting techniques are used to establish a Mt. Pinatubo fingerprint based on the vertical profile of temperature from the E3SMv1 DECK ensemble. By projecting reanalysis data and preindustrial simulations onto the fingerprint, the Mt. Pinatubo stratospheric heating anomaly is detected. Projecting the experimental prognostic aerosol simulation onto the fingerprint also results in a detectable heating anomaly, but, as expected, the duration is too short relative to reanalysis data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Predictability of Zonal Means During Boreal Summer

This study examines the predictability of seasonal means during boreal summer. The results are based on ensembles of June-July-August (JJA) simulations (started in mid May) carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTS) and sea ice for the years 1980-1999. We find that the predictability of the JJA extra-tropical height field is primarily in the zonal mean component of the response to the SST anomalies. This contrasts with the cold season (January-February-March) when the predictability of seasonal means in the boreal extratropics is primarily in the wave component of the El Nino/Southern Oscillation (ENSO) response. Two patterns dominate the interannual variability of the ensemble mean JJA zonal mean height field. One has maximum variance in the tropical/subtropical upper troposphere, while the other has substantial variance in middle latitudes of both hemispheres. Both are symmetric with respect to the equator. A regression analysis suggests that the tropical/subtropical pattern is associated with SST anomalies in the far eastern tropical Pacific and the Indian Ocean, while the middle latitude pattern is forced by SST anomalies in the tropical Pacific just east of the dateline. The two leading zonal height patterns are reproduced in model runs forced with the two leading JJA SST patterns of variability. A comparison with observations shows a signature of the middle latitude pattern that is consistent with the occurrence of dry and wet summers over the United States. We hypothesize that both patterns, while imposing only weak constraints on extratropical warm season continental-scale climates, may play a role in the predilection for drought or pluvial conditions.

Schubert, Siegfried↗
DOE OSTI2019

Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning

Internal atmospheric variability fundamentally limits predictability of climate and obscures evidence of anthropogenic climate change regionally and on time scales of up to a few decades. Dynamical adjustment techniques estimate and subsequently remove the influence of atmospheric circulation variability on temperature or precipitation. The residual component is expected to contain the thermodynamical signal of the externally forced response but with less circulation-induced noise. Existing techniques have led to important insights into recent trends in regional (hydro-) climate and their drivers, but the variance explained by circulation is often low. Here, we develop a novel dynamical adjustment technique by implementing principles from statistical learning. We demonstrate in an ensemble of Community Earth System Model (CESM) simulations that statistical learning methods, such as regularized linear models, establish a clearer relationship between circulation variability and atmospheric target variables, and need relatively short periods of record for training (around 30 years). The method accounts for, on average, 83% and 78% of European monthly winter temperature and precipitation variability at gridcell level, and around 80% of global mean temperature and hemispheric precipitation variability. We show that the residuals retain forced thermodynamical contributions to temperature and precipitation variability. Accurate estimates of the total forced response can thus be recovered assuming that forced circulation changes are gradual over time. Overall, forced climate response estimates can be extracted at regional or global scales from approximately 3–5 times fewer ensemble members, or even a single realization, using statistical learning techniques. We anticipate the technique will contribute to reducing uncertainties around internal variability and facilitating climate change detection and attribution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Numerical Simulations of TRMM LBA, TOGA, COARE, GATE, ARM and PRESTORM Convective Systems: Sensitivity tests on Microphysical Processes

The 3D Goddard Cumulus Ensemble (GCE) model was utilized to examine the behavior and response of simulated deep tropical cloud systems that occurred over the west Pacific warm pool region, the Atlantic ocean and the central United States. The periods chosen for simulation were convectively active periods during TOGA-COARE (February 22 1993, December 11-17, 1992; December 19-28, February 9-13, 1993), GATE (September 4, 1974), LBA (January 26 and February 23, 1998), ARM (1997 IOP) and PRESTORM (June 11, 1985). We will examine differences in the microphysics for both warm rain and ice processes (evaporation /sublimation and condensation/ deposition), Q1 (Temperature), Q2 (Water vapor) and Q3 (momentum both U and V) budgets for these three convective events from different large-scale environments. The contribution of stratiform precipitation and its relationship to the vertical shear of the large-scale horizontal wind will also be examined. New improvements to the GCE model (i.e., microphysics: 4ICE two moments and 3ICE one moment; advection schemes) as well as their sensitivity to the model results will be discussed. Preliminary results indicated that various microphysical schemes could have a major impact on stratiform formation as well as the size of convective systems. However, they do not change the major characteristics of the convective systems, such as: arc shape, strong rotational circulation on both ends of system, heavy precipitation along the leading edge of systems.

Tao, W.-K.↗
DOE OSTI2026

Phosphoserine Charge State Drives Ion Condensation and Spatial Polyamine Presentation in Multirepeat Silaffin

Diatom silaffins direct silica biomineralization through heavily post-translationally modified repeat domains, yet how these modifications reshape the multirepeat conformational ensemble remains unknown. We report all-atom MD simulations of a 195-residue construct spanning repeats R1–R7 of Sil1p from Cylindrotheca fusiformis, carrying the full complement of native PTMs: phosphoserine (pSer), long-chain polyamines (LCPA), dimethyllysine (MLY), and trimethylhydroxylysine phosphate (TPL). We simulated three variants (Native, P1/singly deprotonated phosphate, and P2/doubly deprotonated phosphate) at two NaCl concentrations in triplicate for 500 ns each. All systems disorder from the AlphaFold 3 starting structure. Phosphate charge state, not ionic strength, is the dominant control of ensemble compaction and ion organization. Doubly deprotonated phosphate organizes an extensive Na + condensation shell (∼100 ions, 20% of box Na + ) and a heterogeneous bridging network that integrates both pSer and TPL phosphate groups. The resulting ensemble is compact with LCPA side chains exhibiting above-median solvent accessibility in 84% of simulation frames in P2 at 300 mM. This is higher than any other condition we simulated and indicates that polyamine groups are preferentially surface-presented in the most compact, ion-organized state. A charge-neutralization control confirms that this compact state is a structured intermediate maintained by the bridging network, not a simple collapsed globule. Here, this repeat-scale spatial organization is not captured by single-repeat peptide studies. Understanding the dynamics, mechanism, and spatial organization of PTM-rich silaffin at the repeat scale is a step closer to hierarchical biomimetic materials beyond simple silica morphologies.

Amines↗
DOE OSTI2020

Steering Molecular Dynamics Simulations of Membrane-Associated Proteins with Neutron Reflection Results

Herein, we present a novel method to incorporate structural results from surface-sensitive scattering, such as X-ray or neutron reflectometry, into molecular dynamics simulations. While reflectometry techniques generally provide a means to determine the molecular-scale structures of organized interfacial films, they were recently shown to offer the capability to characterize the structures of protein-membrane complexes supported by a solid substrate. One-dimensional information inherent in the experimental results is used in the form of component volume occupancy (CVO) profiles, which describe the distribution of molecular components within an interfacial architecture, to construct real-space constraints in the form of a biasing potential for the simulation that vanishes when the simulated and experimental profiles agree. This approach improves the correspondence between simulation and experiment, as shown in the re-evaluation of an neutron-reflection-derived structure which was approximated by an independent molecular dynamics simulation in earlier work, and it also leads to faster equilibration of ensemble structures. We further show that time averaging the CVO profile that develops in the simulation while biasing with this approach permits fluctuations about the average that are necessary for conformational exploration of the system. This method is particularly valuable for studies of proteins at interfaces that contain disordered regions since the conformation of such regions is difficult to judge from the analysis of one-dimensional experimental profiles and may take prohibitively long to equilibrate in simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗