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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

CLIMATE LECTURE 3: Building a Climate Model

Climate, or the average of day-to-day weather, can be very different at various points on Earth. The local climate in the Arabian Desert is hot and dry, while that in the Amazon River basin is hot and humid with frequent rain. In upstate New York, the climate changes from being warm in the summer with sporadic rain to cold in the winter with sporadic snow. Hawaii, on the other hand, has a pleasant climate all year long. However, the day-to-day weather at all of these locations is much more variable. There can be dry days in the Amazon jungle, and rainy days in the Arabian Desert. There are some days in winter that are warmer than some days in summer. For further contrast, daylight in Antarctica lasts up to six months at a time with freezing cold day-in day-out. Can a climate model be built that can reproduce all of this complex behavior?

Russell, Gary↗
DOE OSTI2020

Light-absorbing impurities accelerating glacial melting in southeastern Tibetan Plateau

Deposition of light-absorbing particles on glacier surfaces poses a series of adverse impacts on the cryospheric environment, climate and human health. Broad attention of the scientific community has been paid on insoluble light-absorbing impurities (ILAIs) in snow and ice on glaciers over the Tibetan Plateau (TP). However, systematic investigation of ILAIs in snowpack of glaciers on the TP is scarce. In this study, the properties and darkening effect of ILAIs in snowpack on glaciers are extensively investigated in the southeast of TP. Results show that ILAIs concentrations in multiple types of snow and ice samples were significantly different. Snowpit depths varied substantially from one profile to another during May and June 2016. The average concentrations of ILAIs in snowpits increase as snow melting progresses. Black carbon (BC) and dust cause snow albedo reduction more in snow with larger grain size Re. Based on a radiative transfer model calculation, the average albedo reduction induced by BC in the snowpack was 0.141 ± 0.02, and associated daily maximum radiative forcing (RF) was 72.97 ± 12.7 W m-2. BC is a controlling light-absorbing factor in snowpack and causes substantial albedo reduction and thus the associated daily maximum RF. The maximum reduction of snow cover duration was 4.56 ± 0.71 days caused by BC and dust in snowpack in southeastern TP. The average mass absorption cross-section (MAC) of BC from multiple snowpits was 3.26 ± 0.46 m2 g-1, which represents a typical value of MAC in snow on glaciers, but it is type-dependent of snow/ice samples. Tropospheric aerosols vertically extended up to 8 km over the TP and its surrounding areas, which indicates the transport of aerosols from remote sources through elevated pathways. A large amount of carbon stored in the brittle glaciers can be potentially released with meltwater runoff under a warming climate. This study provides a new insight for investigating carbonaceous and light-absorbing particles in glacierization areas.

Niu, Hewen↗
NASA NTRS1994

Characterization of Metal Matrix Composites

Experimental methods were developed, adapted, and applied to the characterization of a metal matrix composite system, namely, silicon carbide/aluminim (SCS-2/6061 Al), and its constituents. The silicon carbide fiber was characterized by determining its modulus, strength, and coefficient of thermal expansion. The aluminum matrix was characterized thermomechanically up to 399 C (750 F) at two strain rates. The unidirectional SiC/Al composite was characterized mechanically under longitudinal, transverse, and in-plane shear loading up to 399 C (750 F). Isothermal and non-isothermal creep behavior was also measured. The applicability of a proposed set of multifactor thermoviscoplastic nonlinear constitutive relations and a computer code was investigated. Agreement between predictions and experimental results was shown in a few cases. The elastoplastic thermomechanical behavior of the composite was also described by a number of new analytical models developed or adapted for the material system studied. These models include the rule of mixtures, composite cylinder model with various thermoelastoplastic analyses and a model based on average field theory. In most cases satisfactory agreement was demonstrated between analytical predictions and experimental results for the cases of stress-strain behavior and thermal deformation behavior at different temperatures. In addition, some models yielded detailed three-dimensional stress distributions in the constituents within the composite.

Daniel, I. M.↗
NASA NTRS1995

The second-moment climatology of the GATE rain rate data

The first part of this paper presents the description of the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) 1 rain-rate data and its two-dimensional spectral and correlation characteristics, which has made it possible to accomplish the following: to show the concentration of a significant power along the frequency axis in the spatiotemporal spectra; to detect a diurnal cycle (which has a range of variation of about 3.4-5.4 mm/n) as one of the sources of bias in the rain statistics of satellite data; to study the distinction between the north-south and east-west transport of spatial rain-rate field and character of its anisotropy; to evaluate the scales of the distinction between second-moment estimates associated with ground and satellite samples; and to determine the appropriate spatial and temporal scales of simple linear stochastic models fitted to averaged rain-rate fields. The second part of this paper is devoted to an analysis of the diffusion of the rain rate by establishing a relationship between the parameters of the multivariate autoregressive model and the coefficients of a diffusion equation. This analysis led to the use of rain data to estimate the rain advection velocity as well as other coefficients of the diffusion equation of the corresponding field. The results obtained can be used for comparison with corresponding estimates of other sources of data (satellite, Tropical Oceans Global Atmosphere Coupled Ocean - Atmosphere Response Experiment (TOGA, COARE) or simulated by physical models), for generating multiple samples of any size, for solving the inverse problems of some of the hydrodynamic equations, and in some other areas of rain data analysis and modeling.

Polyak, Ilya↗
DOE OSTI2025

Scalar flux transport models for self-similar turbulent mixing

A common approach to closing turbulent species flux in multicomponent Reynolds-averaged Navier-Stokes models is to use the standard gradient diffusion approximation. While such an approach has been shown to work well when applied to many canonical turbulent mixing configurations, a gradient diffusion approach is fundamentally limited in its ability to capture complex phenomena such as countergradient transport. For this reason, complicated mixing applications may benefit by treating the turbulent diffusivity with a model transport equation in a manner analogous to second-moment momentum closure in Reynolds-stress transport models. Here, the present work explores the development and application of two different scalar flux transport (SFT) models. Self-similarity constraints are derived for these models, and they are evaluated against gradient-diffusion-based models in several one- and two-dimensional problems of turbulent mixing. It is found that the new SFT models out-perform gradient diffusion models in problems involving rapid acceleration reversal and in problems involving anisotropic transport of materials. In addition, it is found that even a hybrid-SFT approach, in which an SFT equation is utilized along with a gradient diffusion closure, provides some measure of improvement over models that transport the mass flux rather than the scalar flux.

Reynolds-averaged Navier Stokes↗
NASA NTRS1981

A comparison of Type III metric radio bursts and global solar potential field models

Evidence of coronal magnetic fields from polarized metric type III radio bursts is compared with (1) global potential field models, (2) direct averages of the observed photospheric magnetic field, and (3) H-alpha synoptic charts. The comparison clearly indicates both that the principal aspects of type III burst radiation are understood and that global potential field models are a significantly more accurate representation of coronal magnetic field structure than either the large-scale photospheric field or H-alpha synoptic charts.

Jackson, B. V.↗
NASA NTRS2008

Initial Observations of the Magnetic Field Measurements on the C/NOFS Satellite

The Vector Electric Field Instrument (VEFI) suite onboard the C/NOFS spacecraft includes a sensitive fluxgate magnetometer to measure DC and ULF magnetic fields in the low latitude ionosphere. The instrument includes a DC vector measurement at 1 sample/sec with a range of +/- 45,000 nT whose primary objective is to enable a V x B measurement that is more accurate than that provided by using a magnetic field model. These data will also be used to provide signatures of large-scale ionospheric current systems, which, when analyzed in conjunction with the C/NOFS DC electric field measurements, promise to advance our understanding of equatorial electrodynamics. The instrument also includes an AC-coupled vector measurement in the 0.05 - 8 Hz frequency range at 16 samples/sec with an output range of +/- 900 nT in order to measure small-scale current filaments and possible Alfven waves associated with plasma irregularities. We compare the Earth's magnetic field models such as the most recently updated IGRF (the International Geomagnetic Reference Field) model and the POMME (the POtsdam Magnetic Model of the Earth) model with the measurements in order to provide an in-flight "calibration" of the data as well as compute magnetic field differences to reveal large scale ionospheric currents. Our initial results show that, on average, the POMME model accurately reproduces the C/NOFS-measured magnetic field within 20 nT in magnitude and within 0.1 deg in field direction everywhere in the low latitude ionosphere except in the region of the South Atlantic Anomaly. Initial results of the C/NOFS magnetic field measurements will be shown.

Le, Guan↗
DOE OSTI2022

Integrated hydrological, power system and economic modelling of climate impacts on electricity demand and cost

Impacts of climate-related water stress and temperature changes can cascade through energy systems, although models have yet to capture this compounding of effects. Here, we employ a coupled water–power–economy model to capture these important interactions in a study of the exceedance of water temperature thresholds for power generation in the western United States. We find that not all reductions in reserve electricity-generation capacity result in impacts, and that when they occur, intermittent interruptions in electricity supply at critical times of the day, week and year account for much of the economic impacts. Finally, we find that impacts may be in different locations from the original water stress. Herein, we estimate that the consumption loss can be up to 0.3% annually and the drivers identified in coupled modelling can increase the average cost of electricity by up to 3%. Integrated models will be needed to capture the cascading effects of climate change through climatic, water, energy and economic systems. Webster et al. now develop a coupled hydrologic–power-production–economic model to estimate water-stress impacts on electricity cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1986

A cloud model-radiative model combination for determining microwave TB-rain rate relations

The development of a cloud model-radiative transfer model combination for computing average brightness temperature, T(B), is discussed. The cloud model and radiative transfer model used in this study are described. The relations between rain rate, cloud and rain water, cloud and precipitation ice, and upwelling radiance are investigated. The effects of the rain rate relations on T(B) under different climatological conditions are examined. The model-derived T(B) results are compared to the 92 and 183 GHz aircraft observations of Hakkarinen and Adler (1984, 1986) and the radar-estimated rain rate of Hakkarinen and Adler (1986); good correlation between the data is detected.

Szejwach, Gerard↗
DOE OSTI2023

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Development of Mechanistic Fission Gas Release and Swelling Models for UN Fuels in BISON

This report describes the work in NEAMS (Nuclear Energy Advanced Modeling and Simulation) to develop a mechanistic fission gas model for uranium nitride fuels in BISON. The existing Sifgrs (Simple integrated fission gas release and swelling) model tracks the average properties of two bubble populations in the bulk and at the grain boundaries. It was recognized that dislocations play a crucial role in the fission gas swelling of UN, and an irradiation-induced dislocation density model was needed, as well as a model describing how fission gas interacts with dislocations creating a third population of bubbles along dislocations. A mechanistic model that tracks dislocation bubbles was implemented in Sifgrs. This model was used to simulate fission gas swelling and release in UN. Lower-length-scale calculations and experimental observations from carbide fuel were leveraged to help populate the model with essential parameters. As a placeholder, an empirical function was formulated for the evolution of the dislocation network. Because of the difference in evolution of this network at different temperatures, the dislocation bubbles are able to capture behavior that the bulk intragranular bubbles cannot. It was found that the bulk bubbles dominate microscopic swelling at low temperatures, and the dislocation bubbles dominate at higher temperatures. Based on this model, the transition between the two bubble types is the main factor behind the breakaway swelling phenomenon in UN. In order to test the model, a couple of assessments were run. For the lower temperature JOYO pins, the model produces reasonable fission gas release and swelling values. For the higher temperature SP1 pin, the model dramatically underestimates the fission gas release. This issue is attributed to the gas being trapped inside dislocation bubbles, unable to escape to grain boundaries to cause fission gas release, and could be remedied by a mechanistic dislocation model that allows the dislocation density to decrease at very high temperatures. A preliminary mechanistic dislocation model was developed supported by first-principle calculations. These calculations provided valuable insight into how interstitial defects cluster in UN in the {110} orientation, and may eventually form dislocation loops, leading to the conclusion that dislocation loops may nucleate from these clusters. An estimate of the dislocation line energy in UN was obtained and will be improved in future work. The free-energy cluster dynamics code Centipede was used to track interstitial and vacancy absorption at dislocation loops and calculate their growth. In addition, improvements to Centipede were made including new convergence criteria for transient simulations and sink driving force updates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns

Abstract. A large part of the uncertainty in climate projections comes from uncertain aerosol properties and aerosol–cloud interactions as well as the difficulty in remotely sensing them. The southeastern Atlantic functions as a natural laboratory to study biomass-burning smoke and to constrain this uncertainty. We address these gaps by comparing the Weather Research and Forecasting with Chemistry Community Atmosphere Model (WRF-CAM5) to the multi-campaign observations ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing), and LASIC (Layered Atlantic Smoke Interactions with Clouds) in the southeastern Atlantic in August 2017 to evaluate a large range of the model's aerosol chemical properties, size distributions, processes, and transport, as well as aerosol–cloud interactions. Overall, while WRF-CAM5 is able to represent smoke properties and transport, some key discrepancies highlight the need for further analysis. Observations of smoke composition show an overall decrease in aerosol mean diameter as smoke ages over 4–12 d, while the model lacks this trend. A decrease in the mass ratio of organic aerosol (OA) to black carbon (BC), OA:BC, and the OA mass to carbon monoxide (CO) mixing ratio, OA:CO, suggests that the model is missing processes that selectively remove OA from the particle phase, such as photolysis and heterogeneous aerosol chemistry. A large (factor of ∼2.5) enhancement in sulfate from the free troposphere (FT) to the boundary layer (BL) in observations is not present in the model, pointing to the importance of properly representing secondary sulfate aerosol formation from marine dimethyl sulfide and gaseous SO2 smoke emissions. The model shows a persistent overprediction of aerosols in the marine boundary layer (MBL), especially for clean conditions, which multiple pieces of evidence link to weaker aerosol removal in the modeled MBL than reality. This evidence includes several model features, such as not representing observed shifts towards smaller aerosol diameters, inaccurate concentration ratios of carbon monoxide and black carbon, underprediction of heavy rain events, and little evidence of persistent biases in modeled entrainment. The average below-cloud aerosol activation fraction (NCLD/NAER) remains relatively constant in WRF-CAM5 between field campaigns (∼0.65), while it decreases substantially in observations from ORACLES (∼0.78) to CLARIFY (∼0.5), which could be due to the model misrepresentation of clean aerosol conditions. WRF-CAM5 also overshoots an observed upper limit on liquid cloud droplet concentration around NCLD= 400–500 cm−3 and overpredicts the spread in NCLD. This could be related to the model often drastically overestimating the strength of boundary layer vertical turbulence by up to a factor of 10. We expect these results to motivate similar evaluations of other modeling systems and promote model development to reduce critical uncertainties in climate simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Model capabilities, 2-D

Two dimensional (2-D) atmospheric models provide results for altitude versus latitude as a function of time and are developed primarily for two reasons: to help understand atmospheric occurrences and to give assessments and/or make predictions of future changes in the atmosphere. Historically, the formulation of transport in 2-D models has been a difficult problem. Most current 2-D models have a transport that is either an Eulerian mean circulation with large stratospheric eddy diffusion or a residual (diabatic or Lagragian) mean circulation which typically is accompanied with small stratospheric eddy diffusion. Because of the assumption of zonal averaging, 2-D models are primarily useful in making predictions of atmospheric changes of time scales longer than a season. Although decadel atmospheric changes may be reasonably well represented with a 2-D model, the year to year changes which result from interannual transport differences, stratospheric warmings, semiannual oscillations, or quasi-biennial oscillations may not be well represented in the stratosphere and troposphere.

Jackman, Charles H.↗
DOE OSTI2022

Field Sensitivity Analysis of Turbulence Model Parameters for Flow Over a Wing

Reynolds-averaged-Navier-Stokes (RANS) turbulence models are a critical tool in computational-fluid-dynamics simulations of aerodynamic systems, but simulation results can be highly sensitive to RANS-model parameter choices. Sensitivity analysis can be used to quantify these impacts, and the objective of this study is to demonstrate field sensitivity analysis with respect to ten parameters in the 2003 Menter shear-stress-transport (SST) turbulence model. Here, the analysis is demonstrated for an application relevant to wind energy, namely, flow over a NACA 0015 wing at 12 degree angle of attack and a Reynolds number of 1.5 x 10 6 . We quantify sensitivity using Sobol indices and the mean-squared gradient, which are estimated using polynomial chaos and active subspace models, respectively. Our results indicate that there are substantial spatial variations in parameter sensitivities, with different sets of most-sensitive parameters near the wing, as well as in the downstream wake, consistent with the physical interpretations of the turbulence model inputs. We show that, for this particular turbulence model and flow, simultaneous dimension reduction is possible across all quantities of interest, enabling efficient exploration of model outcomes. Ultimately, this analysis provides new insights into turbulence model parameter sensitivities in incompressible flows, and also demonstrates the implementation of field sensitivity analysis for applications relevant to aerodynamics simulations.

17 WIND ENERGY↗
NASA NTRS1976

Pioneer 10 and 11 and ground-based infrared data on Jupiter - The thermal structure and He-H2 ratio

Temperature profiles for four midlatitude regions on Jupiter and an improved value of the H2 molar mixing ratio are obtained from Pioneer 11 IR radiometer data and ground-based IR spectral data. The investigated regions include two in the Southern Hemisphere and two in the Northern Hemisphere, all of which consist of an adjacent belt and zone. The temperature profiles for the pressure regime between 0.1 and 1.0 bar are plotted along with the emitted net flux, flux divergence, and cooling rate for a temperature profile that is an average of those derived for the South Equatorial Belt and a 'cloudy' model of the South Tropical Zone. Averaging of the results obtained with clear and cloudy zone models yields a weighted mean value of 0.88 for the H2 molar mixing ratio, which corresponds to a He/H2 ratio of 0.14. It is emphasized that this value depends on perfect validity of the adopted opacity model, the absence of systematic errors in the data, and other factors. Local effective temperatures for each region are found to range from 124.2 to 127.6 K, which are close to the model-independent global average of 125 K.

Orton, G. S.↗
DOE OSTI2023

Comparison of methods to estimate aerosol effective radiative forcings in climate models

Abstract. Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet's radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing due to aerosol scattering and absorption and to the indirect forcing due to aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations conducted in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and find that they are biased as a result of two large coding errors that – in most cases – fortuitously compensate. The most notable exception is the direct radiative forcing from absorbing aerosols, which is more than 40 % larger averaged across CMIP6 models in the present study. Correcting these biases eliminates the residuals and leads to better agreement with benchmark estimates derived from double calls to the radiation code. The APRP method – when properly implemented – remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available.

58 GEOSCIENCES↗
NASA NTRS1979

Monte Carlo simulation of lunar megaregolith and implications

A realistic Monte Carlo model closely simulating the evolution of the lunar megaregolith over a large area of 67 million sq. km of the front surface of the moon is presented. Craters larger than 100 km in diameter observed over the entire surface of the moon and those less than 100 km lying in the referenced area are included in the simulation. A total of 21,664 craters are processed. The model predicts the average thickness of the megaregolith to be about 1.9-2.0 km. Curves for the variation of the regolith thickness across the simulated area are given and show that about 50% of the area is covered with regolith less than 1 km thick. The model produces crater structures similar to the ones observed in the lunar highlands, it partially supports the layering theory for crater structures that the variations in strength and density of target materials may be responsible for the observed differences in the morphologies of lunar craters, and rules out the possibility that all craters when formed are bowl-shaped with a fixed depth/diameter ratio characteristic of small craters.

Aggarwal, H. R.↗