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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 253 records · Page 14
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NASA NTRS1985

Diffusion of strongly magnetized cosmic ray particles in a turbulent medium

Cosmic ray (CR) propagation in a turbulent medium is usually considered in the diffusion approximation. Here, the diffusion equation is obtained for strongly magnetized particles in the general form. The influence of a large-scale random magnetic field on CR propagation in interstellar medium is discussed. Cosmic rays are assumed to propagate in a medium with a regular field H and an ensemble of random MHD waves. The energy density of waves on scales smaller than the free path 1 of CR particles is small. The collision integral of the general form which describes interaction between relativistic particles and waves in the quasilinear approximation is used.

Ptuskin, V. S.↗
NASA NTRSDate not supplied

Ensemble Cancer Risk Model for Astronaut Risk Assessment

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

Lisa C Simonsen↗
NASA NTRS2010

Broken Ergodicity in MHD Turbulence

Ideal magnetohydrodynamic (MHD) turbulence may be represented by finite Fourier series, where the inherent periodic box serves as a surrogate for a bounded astrophysical plasma. Independent Fourier coefficients form a canonical ensemble described by a Gaussian probability density function containing a Hermitian covariance matrix with positive eigenvalues. The eigenvalues at lowest wave number can be very small, resulting in a large-scale coherent structure: a turbulent dynamo. This is seen in computations and a theoretical explanation in terms of 'broken ergodicity' contains Taylor s theory of force-free states. An important problem for future work is the case of real, i.e., dissipative flows. In real flows, broken ergodicity and coherent structure are still expected to occur in MHD turbulence at the largest scale, as suggested by low resolution simulations. One challenge is to incorporate coherent structure at the largest scale into the theory of turbulent fluctuations at smaller scales.

Shebalin, John V.↗
NASA NTRS2010

Improving a Spectral Bin Microphysical Scheme Using TRMM Satellite Observations

Comparisons between cloud model simulations and observations are crucial in validating model performance and improving physical processes represented in the mod Tel.hese modeled physical processes are idealized representations and almost always have large rooms for improvements. In this study, we use data from two different sensors onboard TRMM (Tropical Rainfall Measurement Mission) satellite to improve the microphysical scheme in the Goddard Cumulus Ensemble (GCE) model. TRMM observed mature-stage squall lines during late spring, early summer in central US over a 9-year period are compiled and compared with a case simulation by GCE model. A unique aspect of the GCE model is that it has a state-of-the-art spectral bin microphysical scheme, which uses 33 different bins to represent particle size distribution of each of the seven hydrometeor species. A forward radiative transfer model calculates TRMM Precipitation Radar (PR) reflectivity and TRMM Microwave Imager (TMI) 85 GHz brightness temperatures from simulated particle size distributions. Comparisons between model outputs and observations reveal that the model overestimates sizes of snow/aggregates in the stratiform region of the squall line. After adjusting temperature-dependent collection coefficients among ice-phase particles, PR comparisons become good while TMI comparisons worsen. Further investigations show that the partitioning between graupel (a high-density form of aggregate), and snow (a low-density form of aggregate) needs to be adjusted in order to have good comparisons in both PR reflectivity and TMI brightness temperature. This study shows that long-term satellite observations, especially those with multiple sensors, can be very useful in constraining model microphysics. It is also the first study in validating and improving a sophisticated spectral bin microphysical scheme according to long-term satellite observations.

Li, Xiaowen↗
NASA NTRS2020

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Michael G Bosilovich↗
NASA NTRS2017

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Hydrological models↗
NASA NTRS1992

Giant suppression of flux-flow resistivity in heavy-ion irradiated Tl2Ba2Ca2Cu3O10 films - Influence of linear defects on vortex transport

A large shift of the onset of flux-flow resistivity and the irreversibility line H(irr)(T) to higher temperatures is observed in Tl2Ba2Ca2Cu3O10 films containing linear defects created by Ag(+21) ion irradiation. The H(irr)(T), which has a characteristic L shape in highly anisotropic Tl and Bi based cuprates, becomes more like that of YBa2Cu3O7 in the presence of these defects. The Jc at 77 K also shows a large increase as a result of flux localization at the defects. The transport data indicate that in the H-T plane above H(irr)(T) of the unirradiated material, an ensemble of unoccupied defects is required for effective pinning of each flux line in the system.

Budhani, R. C.↗
NASA NTRS2002

Self-Consistent Magnetosphere-Ionosphere Coupling and Associated Plasma Energization Processes

Magnetosphere-Ionosphere (MI) coupling and associated with this process electron and ion energization processes have interested scientists for decades and, in spite of experimental and theoretical research efforts, are still ones of the least well known dynamic processes in space plasma physics. The reason for this is that the numerous physical processes associated with MI coupling occur over multiple spatial lengths and temporal scales. One typical example of MI coupling is large scale ring current (RC) electrodynamic coupling that includes calculation of the magnetospheric electric field that is consistent with the ring current (RC) distribution. A general scheme for numerical simulation of such large-scale magnetosphere-ionosphere coupling processes has been presented earlier in many works. The mathematical formulation of these models are based on "modified frozen-in flux theorem" for an ensemble of adiabatically drifting particles in the magnetosphere. By tracking the flow of particles through the inner magnetosphere, the bounce-averaged phase space density of the hot ions and electrons can be reconstructed and the magnetospheric electric field can be calculated such that it is consistent with the particle distribution in the magnetosphere. The new a self-consistent ring current model has been developed that couples electron and ion magnetospheric dynamics with calculation of electric field. Two new features were taken into account in addition to the RC ions, we solve an electron kinetic equation in our model, self-consistently including these results in the solution. Second, using different analytical relationships, we calculate the height integrated ionospheric conductances as the function of precipitated high energy magnetospheric electrons and ions as produced by our model. This results in fundamental changes to the electric potential pattern in the inner magnetosphere, with a smaller Alfven boundary than previous potential formulations would predict but one consistent with recent satellite observations. This leads to deeper penetration of the plasma sheet ions and electrons into the inner magnetosphere and more effective ring current ions and electron energization.

Khazanov, G. V.↗
NASA NTRS2003

Shared motion signals for human perceptual decisions and oculomotor actions

A fundamental question in primate neurobiology is to understand to what extent motor behaviors are driven by shared neural signals that also support conscious perception or by independent subconscious neural signals dedicated to motor control. Although it has clearly been established that cortical areas involved in processing visual motion support both perception and smooth pursuit eye movements, it remains unknown whether the same or different sets of neurons within these structures perform these two functions. Examination of the trial-by-trial variation in human perceptual and pursuit responses during a simultaneous psychophysical and oculomotor task reveals that the direction signals for pursuit and perception are not only similar on average but also co-vary on a trial-by-trial basis, even when performance is at or near chance and the decisions are determined largely by neural noise. We conclude that the neural signal encoding the direction of target motion that drives steady-state pursuit and supports concurrent perceptual judgments emanates from a shared ensemble of cortical neurons.

Visual Cortex/physiology↗
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.↗
NASA NTRS2011

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

Kumar, Sujay V.↗
NASA NTRS2022

Investigation of the Potential Saturation of Information from Global Navigation Satellite System Radio Occultation Observations with an Observing System Simulation Experiment

The potential impact of large numbers of Global Navigation Satellite System radio occultation (GNSS-RO) observations on numerical weather prediction is investigated using a global observing system simulation experiment (OSSE). The hybrid four-dimensional ensemble variational Gridpoint Statistical Interpolation (GSI) data assimilation system and Global Earth Observing System (GEOS) model are used to ingest up to 100,000 GNSS-RO soundings per day in addition to the current suite of conventional and radiance data. Analysis quality, forecast skill, and forecast sensitivity to observation impact are examined with differing quantities of additional GNSS-RO profiles. It is found that saturation of information from additional RO soundings has not been reached with 100,000 soundings per day. There are some indications of suboptimal performance of the GSI in handling GNSS-RO observations particularly in the middle and lower tropospheric extratropics.

GNSS-RO↗
NASA NTRS2023

Impacts of Stratospheric Ozone Recovery on Southern Ocean Temperature and Heat Budget

The impacts of stratospheric ozone recovery on Southern Ocean surface and interior temperature, heat content, heat uptake, and heat transport are investigated by contrasting two ensemble chemistry-climate model simulations in 2005–2099: one with fixed ozone depleting substances (ODSs) and another with decreasing ODSs. In our simulations ozone recovery significantly affects Southern Ocean temperature, with large latitudinal and vertical variations. Ozone recovery causes a dipole change of the full-depth ocean heat content (OHC) with an increase south of 60°S and a decrease between 45°S and 60°S. Integrated over latitudes south of 40°S, OHC decreases in response to ozone recovery. This ocean heat loss is shown to be driven by weakened poleward ocean heat transport (OHT) across 40°S, which is partly canceled by enhanced heat uptake. The weakening of poleward OHT into the Southern Ocean is caused by the ozone-induced equatorward shift of the meridional overturning circulation.

stratospheric ozone↗
NASA NTRS2003

Limits to the Indirect Aerosol Forcing in Stratocumulus

The indirect radiative forcing of aerosols is poorly constrained by the observational data underlying the simple cloud parameterizations in GCMs. signal of cloud response to increased aerosol concentrations from meteorological noise. Recent satellite observations indicate a significant decrease of cloud water in ship tracks, in contrast to an ensemble of in situ measurements showing no average change in cloud water relative to the surrounding clouds. Both results contradict the expectation of cloud water increasing in polluted clouds. We find through large-eddy simulations of stratocumulus that the trend in the satellite data is likely an artifact of sampling only overcast clouds. The simulations instead show cloud cover increasing with droplet concentrations. The simulations also show that increases in cloud water from suppressing drizzle by increased droplet concentrations are favored at night or at extremely low droplet concentrations. At typical droplet concentrations we find that the Twomey effect on cloud albedo is amplified very little by the secondary indirect effect of drizzle suppression, largely because the absorption of solar radiation by cloud water reduces boundary-layer mixing in the daytime and thereby restricts any possible increase in cloud water from drizzle suppression. The cloud and boundary layer respond to radiative heating variations on a time scale of hours, and on longer time scales respond to imbalances between large-scale horizontal advection and the entrainment of inversion air. We analyze the co-varying response of cloud water, cloud thickness, width of droplet size distributions, and dispersion of the optical depth, as well as the overall response of cloud albedo, to changes in droplet concentrations. We also dissect the underlying physical mechanisms through sensitivity studies. Ship tracks represent an ideal natural laboratory to extricate the

Ackerman, Andrew↗
NASA NTRS2001

A Study of the Response of Deep Tropical Clouds to Mesoscale Processes: Modeling Strategies and Simulations of TOGA-COARE Convective Systems - Part 1

Interactions between deep tropical clouds over the western Pacific warm pool and the larger-scale environment are key to understanding climate change. Cloud models are an extremely useful tool in simulating and providing statistical information on heat and moisture transfer processes between cloud systems and the environment, and can therefore be utilized to substantially improve cloud parameterizations in climate models. In this paper, the Goddard Cumulus Ensemble (GCE) cloud-resolving model is used in multi-day simulations of deep tropical convective activity over the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Large-scale temperature and moisture advective tendencies, and horizontal momentum from the TOGA-COARE Intensive Flux Array (IFA) region, are applied to the GCE version which incorporates cyclical boundary conditions. Sensitivity experiments show that grid domain size produces the largest response to domain-mean temperature and moisture deviations, as well as cloudiness, when compared to grid horizontal or vertical resolution, and advection scheme. It is found that a minimum grid-domain size of 500 km is needed to adequately resolve the convective cloud features. The control experiment shows that the atmospheric heating and moistening is primarily a response to cloud latent processes of condensation/evaporation, and deposition/sublimation, and to a lesser extent, melting of ice particles. Air-sea exchange of heat and moisture is found to be significant, but of secondary importance, while the radiational response is small. The simulated rainfall and atmospheric heating and moistening, agrees well with observations, and performs favorably to other models simulating this case.

Johnson, Daniel E.↗
NASA NTRS2016

Numerical Simulation of HIWC Conditions with the Terminal Area Simulation System

Three-dimensional, numerical simulation of a mesoconvective system is conducted in order to better understand conditions associated with High Ice Water Content (HIWC) and its threat to aviation safety. Although peak local values of ice water content may occur early in the storm lifetime, large areas of high concentrations expand with time and persist even when the storm tops begin to warm. The storm canopy which contains HIWC, has low radar reflectivity factor and is fed by an ensemble of regenerating thermal pulses.

Proctor, Fred H.↗
NASA NTRS2020

High Ice Water Content Associated with a Darwin, Austrailia, Mesoscale Convective System

A mesoscale convective complex that occurred during the 2014 Darwin, Australia, flight campaign is examined via a three-dimensional, numerical simulation. The focus of the study is to better understand the presence and development of High Ice Water Content (HIWC) that was observed in the actual storm. Although peak values of ice water content may occur early in the storm lifetime, large areas of high concentrations expand with time and persist even when the storm tops begin to warm. The storm canopy which contains HIWC, has low radar reflectivity factor and is fed by an ensemble of regenerating thermal plumes. Detection via weather radar of the aviation hazard associated HIWC is challenging due the low values of radar reflectivity factor.

Aviation hazards↗
NASA NTRS2014

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Data Assimilation↗