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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Aircraft microwave observations and simulations of deep convection at 18-183 GHz

A radiative transfer model is used to simulate the aircraft multichannel microwave observations and to study a storm system observed on June 29, 1986 during the Cohmex program. The model, which is a revision of the model used by Wilheit et al. (1982), is described. The microwave upwelling brightness temperatures at the top of the atmosphere are calculated from hydrometeor profiles derived from ground-based radar data. The model is used to study various vertical hydrometeor phase profiles and particle size distributions. The results are compared with aircraft data from the Multispectral Cloud Radiometer and the Microwave Precipitation Radiometer. The results show that the brightness temperatures are directly influenced by the complex nature of hydrometeors, including size distribution and the mixture of ice and water phases.

Adler, R. F.↗
NASA NTRS1991

AMPR/SSMI data comparisons

The AMPR (Advanced Microwave Precipitation Radiometer) was flown for the first time with successful data collection over precipitation targets in Florida and off the Oregon coast. The AMPR met its expected performance levels with very low noise and relatively troublefree operation. Numerous rain cloud systems over land and ocean were overflown and the measurements at 10.7, 19.35, 37.1, and 85.5 GHz reveal a wide variety of microphysical conditions which exist within rain cloud systems. Although predicted by radiative transfer model calculations from cloud model simulations, this diversity was not observed before due to the poor spatial resolution of spaceborne microwave radiometers. Saturation of the 19.35 GHz rain emission signal was frequently observed in the oceanic rain systems, supporting the desirability of a 10 GHz channel on the TRMM (Tropical Rain Measuring Mission) microwave radiometer for sensitivity to the higher rain rates.

Spencer, Roy W.↗
NASA NTRS1993

Transfer of perceptual adaptation to space sickness: What enhances an individual's ability to adapt?

The objectives of this project were to explore systematically the determiners of transfer of perceptual adaptation as these principles might apply to the space adaptation syndrome. The perceptual experience of an astronaut exposed to the altered gravitational forces involved in spaceflight shares much with that of the subject exposed in laboratory experiments to optically induced visual rearrangement with tilt and dynamic motion illusions such as vection; and experiences and symptoms reported by the trainee who is exposed to the compellingly realistic visual imagery of flight simulators and virtual reality systems. In both of these cases the observer is confronted with a variety of inter- and intrasensory conflicts that initially disrupt perception, as well as behavior, and also produce symptoms of motion sickness.

Source record↗
NASA NTRS2017

Status and Plans for Reanalysis at NASA/GMAO

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

MERRA-2↗
NASA NTRS2018

Using Reanalysis in Crop Monitoring and Forecasting Systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980-2010 under potential and water-imited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.

Reanalysis↗
NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes Using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).

Brett Raczka↗
NASA NTRS2004

System-Level Reuse of Space Systems Simulations

One of the best ways to enhance space systems simulation fidelity is to leverage off of (reuse) existing high-fidelity simulations. But what happens when the model you would like to reuse is in a different coding language or other barriers arise that make one want to just start over with a clean sheet of paper? Three diverse system-level simulation reuse case studies are described based on experience to date in the development of NASA's Space Station Training Facility (SSTF) at the Johnson Space Center in Houston, Texas. Case studies include (a) the Boeing/Rocketdyne-provided Electrical Power Simulation (EPSIM), (b) the NASA Automation and Robotics Division-provided TRICK robotics systems model, and (c) the Russian Space Agency- provided Russian Segment Trainer. In each case, there was an initial tendency to dismiss simulation reuse candidates based on an apparent lack of suitability. A more careful examination based on a more structured assessment of architectural and requirements-oriented representations of the reuse candidates revealed significant reuse potential. Specific steps used to conduct the detailed assessments are discussed. The steps include the following: 1) Identifying reuse candidates; 2) Requirements compatibility assessment; 3) Maturity assessment; 4) Life-cycle cost determination; and 5) Risk assessment. Observations and conclusions are presented related to the real cost of system-level simulation component reuse. Finally, lessons learned that relate to maximizing the benefits of space systems simulation reuse are shared. These concepts should be directly applicable for use in the development of space systems simulations in the future.

Hazen, Michael R.↗
NASA NTRS1999

Global-Scale Hydrology: Simple Characterization of Complex Simulation

Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.

Koster, Randal D.↗
NASA NTRS1994

Experiments with the Mesoscale Atmospheric Simulation System (MASS) using the synthetic relative humidity

This study is intended to examine the impact of the synthetic relative humidity on the model simulation of mesoscale convective storm environment. The synthetic relative humidity is derived from the National Weather Services surface observations, and non-conventional sources including aircraft, radar, and satellite observations. The latter sources provide the mesoscale data of very high spatial and temporal resolution. The synthetic humidity data is used to complement the National Weather Services rawinsonde observations. It is believed that a realistic representation of initial moisture field in a mesoscale model is critical for the model simulation of thunderstorm development, and the formation of non-convective clouds as well as their effects on the surface energy budget. The impact will be investigated based on a real-data case study using the mesoscale atmospheric simulation system developed by Mesoscale Environmental Simulations Operations, Inc. The mesoscale atmospheric simulation system consists of objective analysis and initialization codes, and the coarse-mesh and fine-mesh dynamic prediction models. Both models are a three dimensional, primitive equation model containing the essential moist physics for simulating and forecasting mesoscale convective processes in the atmosphere. The modeling system is currently implemented at the Applied Meteorology Unit, Kennedy Space Center. Two procedures involving the synthetic relative humidity to define the model initial moisture fields are considered. It is proposed to perform several short-range (approximately 6 hours) comparative coarse-mesh simulation experiments with and without the synthetic data. They are aimed at revealing the model sensitivities should allow us both to refine the specification of the observational requirements, and to develop more accurate and efficient objective analysis schemes. The goal is to advance the MASS (Mesoscal Atmospheric Simulation System) modeling expertise so that the model output can provide reliable guidance for thunderstorm forecasting.

Chang, Chia-Bo↗
DOE OSTI2024

Poleward Migration of the Latitude of Maximum Tropical Cyclone Intensity—Forced or Natural?

Abstract Past studies have shown a significant observed poleward trend in the latitude at which tropical cyclones reach their lifetime maximum intensity (LMI), especially in the northwest Pacific basin. Given the brevity of the historical record, it remains difficult to separate the forced trend from internal variability of the climate system. A recently developed tropical cyclone downscaling model is used to downscale the Community Earth System Model, version 2 (CESM2), preindustrial control simulation. It is found that the observed trend in the latitude at which tropical cyclones reach their LMI in the northwest Pacific is very unlikely to be caused by internal variability. The same downscaling model is then used to downscale CESM2 simulations under historical forcing. The resulting trend distribution shows a significant poleward migration of tropical cyclone LMI even after regressing out both natural variability and the part of the forced warming pattern that projects onto natural variability. The results indicate that the observed poleward migration of the latitude at which tropical cyclones reach their LMI in the northwest Pacific basin is likely to be, at least in part, forced. However, the magnitude of the projected poleward trend in climate models can be significantly modulated by the simulated spatial pattern of ocean warming. This highlights how discrepancies between models and observations, with regard to projected changes to the equatorial zonal sea surface temperature gradient under anthropogenic forcing, can lead to large uncertainties in projected changes to the LMI latitude of tropical cyclones. Significance Statement Observations in the northwest Pacific basin show that the latitude at which tropical cyclones are at their most intense has been trending northward in the recent half century. These changes are important since tropical cyclones could bring hazardous weather to coastal areas that are poorly equipped to handle them. Here, we show that natural variations in Earth’s climate are very unlikely to explain the observed poleward trend in the latitude that tropical cyclone reach their maximum intensity. We find that it is much more likely that the observed trend is forced by human-related emissions, though the spatial pattern of warming in response to greenhouse emissions can have significant impacts on the magnitude of the trend.

Lin, Jonathan↗
DOE OSTI2022

Object-Based Evaluation of Tropical Precipitation Systems in DYAMOND Simulations over the Maritime Continent

The present study uses an object-based evaluation metric to examine the precipitation bias over the Maritime Continent in the global cloud-resolving models. We specifically focus on the difference between the models that directly resolve convection and those using convection parameterization. The 40-day hindcast experiments of the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domain (DYAMOND) intercomparison project are evaluated against the high-resolution satellite rainfall products. The hindcast of the Central Weather Bureau Global Forecast System (CWBGFS) under the DYAMOND protocol is also included. The results indicate that most models simulate insufficient numbers of large precipitation system [object-based precipitation system (OPS), > 370 km in scale], indicating weaker convection organization. The observation indicates that the maximum precipitation within the OPS intensifies with increasing object size. All of the models capture this positive relationship, but most of them overestimate the sensitivity. Most of the models overestimate both the frequency and intensity of small OPS (< 160 km), except for the models with convection parameterization [i.e., CWBGFS, European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS)-9 km]. Although most of the models can reproduce the observed peak time of diurnal precipitation over the land area in the Maritime Continent, the simulated fractional contribution of different sizes of OPS to the total precipitation varies from model to model, and their peak times do not follow the observed ones with delayed peak times as the size of OPS increases from small, mid-size, to large categories. Most of the models reasonably capture the mean diurnal cycle peak time, but only the models with convection parameterization and Model for Prediction Across Scales (MPAS) can represent the diurnal evolution of fractional contribution from different OPSs. The implications of the current results to the upscale processes of the tropical convection systems in the global models are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Inertia Estimation Under High Penetration of Inverter-based Resources

Many types of renewable energy sources, especially solar and wind generation, are connected to the electric grid through power-electronic-based interfaces (inverters). These inverter-based resources (IBRs) are mechanically decoupled from the grid, which reduces system inertia and thus may compromise its stability and reliability. In this study, we examine the impact of high penetration of IBRs on the power grid’s inertia. To achieve this, we intentionally introduce disturbances into a simulation case study, such as a step load change, to observe and record the system’s frequency responses. This study offers a nuanced understanding of how the integration of IBRs affects grid stability, and it provides essential guidance for future grid management and resilience strategies.

Yadav, Ajay↗
DOE OSTI2023

Influences of cloud vertical overlapping on the calculated cloud albedo and their validation with satellite observations

Cloud albedo is expected to influence cloud radiative forcing in addition to cloud fraction, and inadequate description of the cloud overlapping effects on the cloud fraction may influence the simulated cloud fraction, and thus the relative cloud radiative forcing (RCRF) and cloud albedo. In this study, we first present a new formula by extending that presented previously in Liu et al. (2011) to consider multilayer clouds directly in the relationship between cloud albedo, cloud fraction and RCRF, and then quantitatively evaluate the effects of different cloud vertical overlapping structures, represented by the decorrelation length scales (L cf ), on the simulated cloud albedos. We use the BCC_AGCM2.0_CUACE/Aero model with simultaneous validation by observations from the Clouds and the Earth's Radiation Energy System (CERES) satellite. When L cf < 4 km (i.e., the cloud overlap is closer to the random overlap), the simulated cloud albedos are generally in good agreement with the satellite-based albedos for December– February and June–August; when L cf ≥ 4 km (i.e., the cloud vertical overlap is closer to the maximum overlap), the difference between simulated and observed cloud albedos became larger, due mainly to significant differences in cloud fractions and RCRF. Further quantitative analysis shows that the relative Euclidean distance, which represents the degree of overall model–observation disagreement, increases with the L cf for all three variables (cloud albedo, cloud fraction and RCRF), indicating the importance of cloud vertical overlapping in determining the accuracy of the calculated cloud albedo for multilayer clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine learning-based observation-constrained projections reveal elevated global socioeconomic risks from wildfire

Reliable projections of wildfire and associated socioeconomic risks are crucial for the development of efficient and effective adaptation and mitigation strategies. The lack of or limited observational constraints for modeling outputs impairs the credibility of wildfire projections. Here, we present a machine learning framework to constrain the future fire carbon emissions simulated by 13 Earth system models from the Coupled Model Intercomparison Project phase 6 (CMIP6), using historical, observed joint states of fire-relevant variables. During the twenty-first century, the observation-constrained ensemble indicates a weaker increase in global fire carbon emissions but higher increase in global wildfire exposure in population, gross domestic production, and agricultural area, compared with the default ensemble. Such elevated socioeconomic risks are primarily caused by the compound regional enhancement of future wildfire activity and socioeconomic development in the western and central African countries, necessitating an emergent strategic preparedness to wildfires in these countries.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Aircraft noise synthesis system

A second-generation Aircraft Noise Synthesis System has been developed to provide test stimuli for studies of community annoyance to aircraft flyover noise. The computer-based system generates realistic, time-varying, audio simulations of aircraft flyover noise at a specified observer location on the ground. The synthesis takes into account the time-varying aircraft position relative to the observer; specified reference spectra consisting of broadband, narrowband, and pure-tone components; directivity patterns; Doppler shift; atmospheric effects; and ground effects. These parameters can be specified and controlled in such a way as to generate stimuli in which certain noise characteristics, such as duration or tonal content, are independently varied, while the remaining characteristics, such as broadband content, are held constant. The system can also generate simulations of the predicted noise characteristics of future aircraft. A description of the synthesis system and a discussion of the algorithms and methods used to generate the simulations are provided. An appendix describing the input data and providing user instructions is also included.

Mccurdy, David A.↗
DOE OSTI2024

Data-driven discovery of dynamics from time-resolved coherent scattering

Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Can the GEOS CCM Simulate the Temperature Response to Warm Pool El Nino Events in the Antarctic Stratosphere?

"Warm pool" (WP) El Nino events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. During austral spring. WP El Nino events are associated with an enhancement of convective activity in the South Pacific Convergence Zone, provoking a tropospheric planetary wave response and thus increasing planetary wave driving of the Southern Hemisphere stratosphere. These conditions lead to higher polar stratospheric temperatures and to a weaker polar jet during austral summer, as compared with neutral ENSO years. Furthermore, this response is sensitive to the phase of the quasi-biennial oscillation (QBO): a stronger warming is seen in WP El Nino events coincident with the easterly phase of the quasi-biennial oscillation (QBO) as compared with WP El Nino events coincident with a westerly or neutral QBO. The Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) is used to further explore the atmospheric response to ENSO. Time-slice simulations are forced by composited SSTs from observed WP El Nino and neutral ENSO events. The modeled eddy heat flux, temperature and wind responses to WP El Nino events are compared with observations. A new gravity wave drag scheme has been implemented in the GEOS CCM, enabling the model to produce a realistic, internally generated QBO. By repeating the above time-slice simulations with this new model version, the sensitivity of the WP El Nino response to the phase of the quasi-biennial oscillation QBO is estimated.

Hurwitz, M. M.↗
NASA NTRS2011

Can the GEOS CCM Simulate the Temperature Response to Warm Pool El Nino Events in the Antarctic Stratosphere?

"Warm pool" (WP) El Nino events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific. During austral spring, WP El Nino events are associated with an enhancement of convective activity in the South Pacific Convergence Zone, provoking a tropospheric planetary wave response and thus increasing planetary wave driving of the Southern Hemisphere stratosphere. These conditions lead to higher polar stratospheric temperatures and to a weaker polar jet during austral summer, as compared with neutral ENSO years. Furthermore, this response is sensitive to the phase of the quasi-biennial oscillation (QBO): a stronger warming is seen in WP El Nino events coincident with the easterly phase of the quasi-biennial oscillation (QBO) as compared with WP El Nino events coincident with a westerly or neutral QBO. The Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) is used to further explore the atmospheric response to ENSO. Time-slice simulations are forced by composited SSTs from observed NP El Nino and neutral ENSO events. The modeled eddy heat flux, temperature and wind responses to WP El Nino events are compared with observations. A new gravity wave drag scheme has been implemented in the GEOS CCM, enabling the model to produce e realistic, internally generated QBO. By repeating the above time-slice simulations with this new model version, the sensitivity of the WP El Nino response to the phase of the quasi-biennial oscillation QBO is estimated.

Hurwitz, M. M.↗