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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Forecasted Dynamic Line Ratings for Regional Transmission Lines

This report was prepared for the Wind Energy Technology Office for the FY 2022, quarter 3 deliverable. This details the use of forecasted dynamic line rating as an improvement over static rating for three transmission lines in three regions of interest. A selection of wind plants across Idaho, the Columbia River Gorge and offshore wind in the NYSERDA territory were modeled for their concurrent cooling effects for dynamic line rating. Regional transmission lines for the wind plant interconnections were determined and a CFD domain was created to determine local wind flows over the lines. A dynamic line rating for each of the lines was calculated for both weather observation data and HRRR model forecast data. The comparison of peaks in the wind power production were compared to the DLR peaks. It was determined that for shorter regional transmission lines, the effect of concurrent cooling that commonly occur with gen-tie lines were still valid. Concurrent cooling effects drop as the length of the regional transmission lines increase in distance from the wind plants. In addition, the accuracy of the forecasted ampacity to the weather observation data for ampacity was assessed. In general, the accuracy was best for the INL region with the NOAA-maintained sites. The Columbia River Gorge and Long Island sites showed similar levels of accuracy for the forecasted DLR. The accuracy levels were around 11% for the INL region, 15% for Columbia River Gorge and 7% for New York Long Island. The higher error for the Columbia Gorge region is likely due to the sparse availability of weather stations available, whereas both the INL site and Long Island are well instrumented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

The interplanetary scattering mean free path - Collisionless wave-damping effects

The role of dissipation in the scattering of charged particles in the interplanetary medium (IPM) is analyzed to obtain a model for the interplanetary magnetic turbulence spectrum that yields particle free paths (PEP) which agree with observational data. The scattering processes are attributed to waves with small wavelengths intersected by particles with zero pitch angles. The waves, being strongly damped by collisionless cyclotron damping in the ambient thermal plasma, produce reduced scattering and longer MFPs. The model, which includes the damping factor, was used to generate proton propagation maps at kinetic energy levels of under, over, and within the 5 MeV-2 GeV range. The results, when compared with observational data, displayed good agreement. The same held true for the MFP propagation of energetic electrons.

Davila, J. M.↗
NASA NTRS2018

Advanced Analytics and Big Earth Data

NASA's Earth Science Data Systems process, archive and distribute petabytes of Earth Observation data to a variety of end users. These end users will face dramatically increased data size in the near future, bringing about new challenges and opportunities in analyzing those data. One area of particular ferment currently is Machine Learning. Many Machine Learning methods are black boxes, limiting direct insight into the data's properties. However, they can be used for a variety of data enhancement purposes, such as parameter retrieval, data fusion and image classification and segmentation. The Earth Observing System Data and Information System is also evolving to host large data volumes in the cloud, enabling data proximal analysis. As part of this effort, an Analytics framework is being developed to support and enhance user analysis of the data. By using standards based services in the framework, diverse user communities can be served, while also allowing inter-system collaboration in the analysis process.

Cloud Computing↗
DOE OSTI2015

Model performance in spatiotemporal patterns of precipitation: New methods for identifying value added by a regional climate model: Value added by a regional climate model

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, and time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

On the cause of variability of the cosmic ray spectrum in the knee region

Cosmic ray (CR) energy spectra for H, He, Si, and Fe nuclei with energy-to-charge number ratios ℰ/Z in the range from 10 to 5 × 10{sup 7} GeV are studied using observational data obtained at different times in different energy ranges: AMS-02, CREAM, Tibet ASγ, Tibet (hybrid), GRAPES-3, KASCADE, and KASCADE-Grande. Comparison of the H and He CR fluxes according to the KASCADE and KASCADE-Grande data (for different models of deconvolving CR spectra) with the Tibet ASγ and Tibet (hybrid) data obtained at another time in the range of ℰ/Z ∼ 3 × 10{sup 6} GeV demonstrates space weather-caused variability of the CR flux. This feature of CR energy spectra in the Tibet ASγ data is most clearly observed in the spectra of heavier nuclei (Si and Fe) according to the KASCADE-Grande and GRAPES-3 data. The variability in the energy spectra of all CRs in the vicinity of the “knee” is shown in the data of Yakutsk EAS, CASA-BLANCA, and Tibet-III experiments. The variability of the CR flux on a time scale on the order of several years exists only if the source corresponding to the peak in the energy spectrum is situated at a distance of no more than 1 pc from the Sun. Rapid surfatron acceleration of CRs may result from colliding interstellar clouds nearest to the Sun (LIC and G). This acceleration mechanism allows one to explain the variability of the CR spectrum in the range 10{sup 3} GeV < ℰ/Z < 10{sup 8} GeV. Conditions for the trapping of strongly relativistic Fe nuclei by an electromagnetic wave, the dynamics of the components of the particle velocity and momentum, and the dependence of the particle acceleration rate on the initial parameters of the problem are analyzed using numerical calculations. The structure of the phase plane of the accelerated Fe nuclei is examined. Optimal conditions for the implementation of ultrarelativistic surfatron acceleration of Fe nuclei by an electromagnetic wave are formulated.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Simulations of Sulfate-Nitrate-Ammonium (SNA) aerosols during the extreme haze events over Northern China in 2014

Extreme haze events have occurred frequently over China in recent years. Although many studies have investigated the formation mechanisms associated with PM2.5 for heavily polluted regions in China based on observational data, adequately predicting peak PM2.5 concentrations is still challenging for regional air quality models. In this study, we evaluate the performance of one configuration of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) and use the model to investigate the sensitivity of heterogeneous reactions on simulated peak sulfate, nitrate, and ammonium concentrations in the vicinity of Beijing during four extreme haze episodes in October 2014 over the North China Plain. The highest observed PM2.5 concentration of 469 μg m-3 occurred in Beijing. Comparisons with observations show that the model reproduced the temporal variability in PM2.5 with the highest PM2.5 values on polluted days (defined as days in which observed PM2.5 is greater than 75 μg m-3), but predictions of sulfate, nitrate, and ammonium were too low on days with the highest observed concentrations. Observational data indicate that the sulfur/nitric oxidation rates are strongly correlated with relative humidity during periods of peak PM2.5; however, the model failed to reproduce the highest PM2.5 concentrations due to missing heterogeneous reactions. As the parameterizations of those reactions is not well established yet, estimates of SO2-to-H2SO4 and NO2/NO3-to-HNO3 reaction rates that depend on relative humidity were applied which improved the simulation of sulfate, nitrate, and ammonium enhancement on polluted days in terms of both concentrations and partitioning among those species. Sensitivity simulations showed that the extremely high heterogeneous reaction rates and also higher emission rates than those reported in the emission inventory

Chen, Dan↗
NASA NTRS2018

Explicit Cloud Representation in the Atmos 1D Climate Model for Earth and Rocky Planet Applications

1D climate models are less sophisticated than 3D global circulation models (GCMs), however their computational time is much less expensive, allowing a large number of runs in a short period of time to explore a wide parameter space. Exploring parameter space is particularly important for predicting the observable properties of exoplanets, for which few parameters are known with certainty. Therefore, 1D climate models are still very useful tools for planetary studies. In most of these 1D models, clouds are not physically represented in the atmosphere, despite having a well-known, significant impact on a planetary radiative budget. This impact is simulated by artificially raising surface albedo, in order to reproduce the observed-averaged surface temperature (i.e. 288 K for modern Earth) and a radiative balance at the top of the atmosphere. This non-physical representation of clouds, causes atmospheric long wave and shortwaves fluxes to not match observational data. Additionally, this technique represents a parameter that is highly-tuned to modern Earth’s climate, and may not be appropriate for planets that deviate from modern Earth’s climate conditions. In this paper, we present an update to the climate model within the Atmos 1­D atmospheric modeling package with a physical representation of clouds. We show that this physical representation of clouds in the atmosphere allows both long wave and shortwave fluxes to match observational data. This improvement will allow us to study the energy fluxes for a variety of cloudy rocky planets, and increase our confidence in future simulations of temperature profile and net energy balance.

Thomas Fauchez↗
DOE OSTI2017

MAGNETIC PROPERTIES OF SOLAR ACTIVE REGIONS THAT GOVERN LARGE SOLAR FLARES AND ERUPTIONS

Solar flares and coronal mass ejections (CMEs), especially the larger ones, emanate from active regions (ARs). With the aim of understanding the magnetic properties that govern such flares and eruptions, we systematically survey all flare events with Geostationary Orbiting Environmental Satellite levels of ≥M5.0 within 45° from disk center between 2010 May and 2016 April. These criteria lead to a total of 51 flares from 29 ARs, for which we analyze the observational data obtained by the Solar Dynamics Observatory . More than 80% of the 29 ARs are found to exhibit δ -sunspots, and at least three ARs violate Hale’s polarity rule. The flare durations are approximately proportional to the distance between the two flare ribbons, to the total magnetic flux inside the ribbons, and to the ribbon area. From our study, one of the parameters that clearly determine whether a given flare event is CME-eruptive or not is the ribbon area normalized by the sunspot area, which may indicate that the structural relationship between the flaring region and the entire AR controls CME productivity. AR characterization shows that even X-class events do not require δ -sunspots or strong-field, high-gradient polarity inversion lines. An investigation of historical observational data suggests the possibility that the largest solar ARs, with magnetic flux of 2 × 10{sup 23} Mx, might be able to produce “superflares” with energies of the order of 10{sup 34} erg. The proportionality between the flare durations and magnetic energies is consistent with stellar flare observations, suggesting a common physical background for solar and stellar flares.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The Observed and Projected Changes of Global Monsoons: Current Status and Future Perspectives

The global monsoon system, encompassing the Asian-Australian, African, and American monsoons, sustains two-thirds of the world’s population by regulating water resources and agriculture. Monsoon anomalies pose severe risks, including floods and droughts. Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms. Observational data reveal a 20th-century shift: increased rainfall pre-1950s, followed by aridification and partial recovery post-1980s, driven by both internal variability (e.g., Atlantic Multidecadal Oscillation) and external forcings (greenhouse gases, aerosols), while ENSO drives interannual variability through ocean-atmosphere interactions. Future projections under greenhouse forcing suggest long-term monsoon intensification, though regional disparities and model uncertainties persist. Models indicate robust trends but struggle to quantify extremes, where thermodynamic effects (warming-induced moisture rise) uniformly boost heavy rainfall, while dynamical shifts (circulation changes) create spatial heterogeneity. Volcanic eruptions and proposed solar radiation modification (SRM) further complicate predictions: tropical eruptions suppress monsoons, whereas high-latitude events alter cross-equatorial flows, highlighting unresolved feedbacks. The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons. Critical challenges remain. Model biases and sparse 20th-century observational data hinder accurate attribution. The interplay between natural variability and anthropogenic forcings, along with nonlinear extreme precipitation risks under warming, demands deeper mechanistic insights. Additionally, SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation. Addressing these gaps necessitates enhanced observational networks, refined climate models, and interdisciplinary efforts to disentangle multiscale drivers, ultimately improving resilience strategies for monsoon-dependent regions.

climate extreme events↗
DOE OSTI2019

LDRD 20190608ER: Diagnosing Near-Future Changes in Arctic Sea Ice and Ocean Conditions

Environmental changes in the Arctic present opportunities and increased hazards as potential shipping corridors open. We apply novel statistical techniques to simultaneously characterize multiple physical properties and uncertainties relevant for Arctic shipping, analyzing existing model projections to understand the likelihood of encountering high wind and low ice conditions along potential transportation routes through the Arctic Ocean. We assess the quality of Department of Energy (DOE) simulations against observed data, for these purposes. We find that the Arctic system is highly variable, but its large-scale patterns are captured by the models, allowing us to consider the two major shipping routes along Arctic coasts: the Northern Sea Route on the Russian side of the Arctic Ocean, and the Northwest Passage through the Canadian Arctic Archipelago. Our work highlights the usefulness and promise of DOE’s new modeling system (E3SM) as well as limitations of the models and observed data, such as resolution, differing types of information available from models and measurements, and challenges for quantifying uncertainty and bias. A procedure developed to increase predictability in Community Earth System Model simulations could be beneficial for E3SM. This research provides insight into Arctic trends and a baseline to articulate future model development needs.

58 GEOSCIENCES↗
NASA NTRS2008

Updated Results for the Wake Vortex Inverse Model

NorthWest Research Associates (NWRA) has developed an Inverse Model for inverting aircraft wake vortex data. The objective of the inverse modeling is to obtain estimates of the vortex circulation decay and crosswind vertical profiles, using time history measurements of the lateral and vertical position of aircraft vortices. The Inverse Model performs iterative forward model runs using estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Iterations are performed until a user-defined criterion is satisfied. Outputs from an Inverse Model run are the best estimates of the time history of the vortex circulation derived from the observed data, the vertical crosswind profile, and several vortex parameters. The forward model, named SHRAPA, used in this inverse modeling is a modified version of the Shear-APA model, and it is described in Section 2 of this document. Details of the Inverse Model are presented in Section 3. The Inverse Model was applied to lidar-observed vortex data at three airports: FAA acquired data from San Francisco International Airport (SFO) and Denver International Airport (DEN), and NASA acquired data from Memphis International Airport (MEM). The results are compared with observed data. This Inverse Model validation is documented in Section 4. A summary is given in Section 5. A user's guide for the inverse wake vortex model is presented in a separate NorthWest Research Associates technical report (Lai and Delisi, 2007a).

Robins, Robert E.↗
DOE OSTI2022

Alpert multi-wavelets for functional inverse problems: direct optimization and deep learning

Computational engineering models often contain unknown entities (e.g. parameters, initial and boundary conditions) that require estimation from other measured observable data. Estimating such unknown entities is challenging when they involve spatio-temporal fields because such functional variables often require an infinite-dimensional representation. Here, we address this problem by transforming an unknown functional field using Alpert wavelet bases and truncating the resulting spectrum. Hence the problem reduces to the estimation of few coefficients that can be performed using common optimization methods. We apply this method on a one-dimensional heat transfer problem where we estimate the heat source field varying in both time and space. The observable data is comprised of temperature measured at several thermocouples in the domain. This latter is composed of either copper or stainless steel. The optimization using our method based on wavelets is able to estimate the heat source with an error between 5% and 7%. We analyze the effect of the domain material and number of thermocouples as well as the sensitivity to the initial guess of the heat source. Finally, we estimate the unknown heat source using a different approach based on deep learning techniques where we consider the input and output of a multi-layer perceptron in wavelet form. We find that this deep learning approach is more accurate than the optimization approach with errors below 4%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Weighing neutrinos in the scenario of vacuum energy interacting with cold dark matter: application of the parameterized post-Friedmann approach

We constrain the neutrino mass in the scenario of vacuum energy interacting with cold dark matter by using current cosmological observations. To avoid the large-scale instability problem in interacting dark energy models, we employ the parameterized post-Friedmann (PPF) approach to do the calculation of perturbation evolution, for the Q = β H ρ{sub c} and Q = β H ρ{sub Λ} models. The current observational data sets used in this work include Planck (cosmic microwave background), BSH (baryon acoustic oscillations, type Ia supernovae, and Hubble constant), and LSS (redshift space distortions and weak lensing). According to the constraint results, we find that β > 0 at more than 1σ level for the Q = β H ρ{sub c} model, which indicates that cold dark matter decays into vacuum energy; while β = 0 is consistent with the current data at 1σ level for the Q = β H ρ{sub Λ} model. Taking the ΛCDM model as a baseline model, we find that a smaller upper limit, ∑ m {sub ν} < 0.11 eV (2σ), is induced by the latest BAO BOSS DR12 data and the Hubble constant measurement H {sub 0} = 73.00 ± 1.75 km s{sup −1} Mpc{sup −1}. For the Q = β H ρ{sub c} model, we obtain ∑ m {sub ν}<0.20 eV (2σ) from Planck+BSH. For the Q = β H ρ{sub Λ} model, ∑ m {sub ν}<0.10 eV (2σ) and ∑ m {sub ν}<0.14 eV (2σ) are derived from Planck+BSH and Planck+BSH+LSS, respectively. We show that these smaller upper limits on ∑ m {sub ν} are affected more or less by the tension between H {sub 0} and other observational data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Non-extensive statistics to the cosmological lithium problem

Big Bang nucleosynthesis (BBN) theory predicts the abundances of the light elements D, 3 He, 4 He, and 7 Li produced in the early universe. The primordial abundances of D and 4 He inferred from observational data are in good agreement with predictions, however, BBN theory overestimates the primordial 7 Li abundance by about a factor of three. This is the so-called "cosmological lithium problem." Solutions to this problem using conventional astrophysics and nuclear physics have not been successful over the past few decades, probably indicating the presence of new physics during the era of BBN. We have investigated the impact on BBN predictions of adopting a generalized distribution to describe the velocities of nucleons in the framework of Tsallis non-extensive statistics. This generalized velocity distribution is characterized by a parameter q, and reduces to the usually assumed Maxwell–Boltzmann distribution for q = 1. We find excellent agreement between predicted and observed primordial abundances of D, 4 He, and 7 Li for 1.069 ≤ q ≤ 1.082, suggesting a possible new solution to the cosmological lithium problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Highlighting the Impact of Yaw Control by Parsing Atmospheric Conditions Based on Total Variation: Preprint

Identification of atmospheric conditions within a multivariate atmospheric dataset is a necessary step in the validation of wind plant control strategies. Most often, operating conditions are characterized in terms of aggregated observations and assume that the atmosphere is 'quasi-steady'. Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of wind plant operating conditions. Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation sets the stage for more advanced model validation and the development of real-time control and operation strategies. Controlling observational data for statistical stationarity highlights significant enhancements to the power production of waked turbines under wake steering wind plant control. Considering the combined energy ratio of the turbine to which yaw offsets are prescribed as well as the waked turbine show only moderate improvements when filtering for total validation. The same quality control that highlights wake steering also serves to underpin the off-nominal operation of the controlled turbine.

17 WIND ENERGY↗
NASA NTRS2020

An Integrated Model of Models for Global Flood Alerting

A dramatic increase in frequency of minor to major flooding since 2000 has caused significant damage to infrastructure and economic losses across the world. To mitigate and recover from these losses, actions have been taken to build resilient communities and infrastructures. Situational awareness in near real-time is essential to ensure community resilience and enhance response and recovery efforts. Several hydrologic and hydraulic flood models are available at various spatial and temporal resolutions at regional to global scale. Given the global coverage of two operational flood models - GloFAS (Global Flood Awareness System) and GFMS (Global Flood Monitoring System), the first component of this project first focuses on integrating the outputs from these two models to classify flood severity and send alerts based on potential for impacts similar to the USGS PAGER (used for severity alerting and impact analysis for earthquakes). The second component of the project focuses on using flood outputs derived from earth observation data to validate, update and add additional exposure and impact products to flood alerts. The flood impacts and severity information will be disseminated as alerts and maps through the DisasterAWARE platform, operated by the Pacific Disaster Center (PDC), that provides global multi-hazard alerting and Situational Awareness information to the emergency management community and public. In this presentation, the following objectives will be covered: (i) the effective integration of the flood models, (ii) accuracy of the flood model outputs (flood extent and depth) for specific flood events both in the United States and globally in comparison with each other and earth observation data.

Glasscoe, Margaret↗
NASA NTRS1980

Coronal heating by stochastic magnetic pumping

Recent observational data cast serious doubt on the widely held view that the Sun's corona is heated by traveling waves (acoustic or magnetohydrodynamic). It is proposed that the energy responsible for heating the corona is derived from the free energy of the coronal magnetic field derived from motion of the 'feet' of magnetic field lines in the photosphere. Stochastic motion of the feet of magnetic field lines leads, on the average, to a linear increase of magnetic free energy with time. This rate of energy input is calculated for a simple model of a single thin flux tube. The model appears to agree well with observational data if the magnetic flux originates in small regions of high magnetic field strength. On combining this energy input with estimates of energy loss by radiation and of energy redistribution by thermal conduction, we obtain scaling laws for density and temperature in terms of length and coronal magnetic field strength.

Sturrock, P. A.↗
NASA NTRS1981

Coronal heating by stochastic magnetic pumping

Recent observational data cast serious doubt on the widely held view that the sun's corona is heated by traveling waves (acoustic or magnetohydrodynamic). It is here proposed that the energy responsible for heating the corona is derived from the free energy of the coronal magnetic field derived from motion of the 'feet' of magnetic field lines in the photosphere. Stochastic motion of the feet of magnetic field lines leads, on the average, to a linear increase of magnetic free energy with time. This rate of energy input is calculated for a simple model of a single thin flux tube. The model appears to agree well with observational data if the magnetic flux originates in small regions of high magnetic field strength as proposed by Tarbell et al. (1979). On combining this energy input with estimates of energy loss by radiation and of energy redistribution by thermal conduction, scaling laws are obtained for density and temperature in terms of length and coronal magnetic field strength.

Sturrock, P. A.↗