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At least 469 records · Page 26

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DOE OSTI2018

Predictability of phases and magnitudes of natural decadal climate variability phenomena in CMIP5 experiments with the UKMO HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 global earth system models

Data from decadal hindcast experiments conducted under CMIP5 were used to assess the ability of CM2.1, HadCM3, MIROC5, and CCSM4 Earth System Models (ESMs) to hindcast sea-surface temperature (SST) indices of the Pacific Decadal Oscillation (PDO), the tropical Atlantic SST gradient (TAG) variability, and the West Pacific Warm Pool (WPWP) SST variability from 1961 to 2010. The ESMs were initialized at specific times with observed data to make 10- and 30-year hindcasts/forecasts. Deterministic and probabilistic skill estimates show predictability of detrended WPWP index to 5 years’ lead time and of non-detrended WPWP index to 10 years’ lead time. These estimates also show atypical skill dependence of PDO and TAG indices on lead times, with increasing skill in the middle to end of 10-year hindcasts. The skill of ESMs to hindcast an observed DCV index (signal skill) is surprisingly greater than the skill to hindcast their own DCV index (noise skill) at some lead times. All ESMs hindcast occurrence frequencies of positive and negative phases of the indices, and probabilities of same-phase transitions from one year to the next reasonably well. Four, major, low-latitude volcanic eruptions are associated with phase transitions of all observed and some of the ensemble-average hindcast indices. All ESMs’ WPWP index hindcasts respond correctly to all eruptions as do three observed PDO phase transitions. No one of the ESMs’ hindcasts of the TAG index responds correctly to these eruptions. Some of the ESMs hindcast correct phase transitions in the absence of eruptions also, implying that initializations with observed data are beneficial in predicting phase transitions. The skills of DCV indices’ phase prediction up to at least two years in advance can be used to inform societal impacts adaptation decisions in water resources management and agriculture. The Atlantic region’s responses in these ESMs appear to be fundamentally incorrect.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1985

On the cosmic ray diffusion in a violent interstellar medium

A variety of the available observational data on the cosmic ray (CR) spectrum, anisotropy and composition are in good agreement with a suggestion on the diffusion propagation of CR with energy below 10(15) eV in the interstellar medium. The magnitude of the CR diffusion coefficient and its energy dependence are determined by interstellar medium (ISM) magnetic field spectra. Direct observational data on magnetic field spectra are still absent. A theoretical model to the turbulence generation in the multiphase ISM is resented. The model is based on the multiple generation of secondary shocks and concomitant large-scale rarefactions due to supernova shock interactions with interstellar clouds. The distribution function for ISM shocks are derived to include supernova statistics, diffuse cloud distribution, and various shock wave propagation regimes. This permits calculation of the ISM magnetic field fluctuation spectrum and CR diffusion coefficient for the hot phase of ISM.

Bykov, A. M.↗

DOE OSTI2018

The near-nucleus gas coma of comet 67P/Churyumov-Gerasimenko prior to the descent of the surface lander PHILAE

Context. The European Space Agency (ESA) Rosetta mission was the most comprehensive study of a comet ever performed. In particular, the Rosetta orbiter, which carried many instruments for monitoring the evolution of the dusty gas emitted by the cometary nucleus, returned an enormous volume of observational data collected from the close vicinity of the nucleus of comet 67P/Churyumov-Gerasimenko. Aims. Such data are expected to yield unique information on the physical processes of gas and dust emission, using current physical model fits to the data. We present such a model (the RZC model) and our procedure of adjustment of this model to the data. Methods. The RZC model consists of two components: (1) a numerical three-dimensional time-dependent code solving the Eulerian/Navier-Stokes equations governing the gas outflow, and a direct simulation Monte Carlo (DSMC) gaskinetic code with the same objective; and (2) an iterative procedure to adjust the assumed model parameters to best-fit the observational data at all times. Results. We demonstrate that our model is able to reproduce the overall features of the local neutral number density and composition measurements of Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA) Comet Pressure Sensor (COPS) and Double Focusing Mass Spectrometer (DFMS) instruments in the period August 1–November 30, 2014. The results of numerical simulations show that illumination conditions on the nucleus are the main driver for the gas activity of the comet. We present the distribution of surface inhomogeneity best-fitted to the ROSINA COPS and DFMS in situ measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

THE MIRA–TITAN UNIVERSE: PRECISION PREDICTIONS FOR DARK ENERGY SURVEYS

Large-scale simulations of cosmic structure formation play an important role in interpreting cosmological observations at high precision. The simulations must cover a parameter range beyond the standard six cosmological parameters and need to be run at high mass and force resolution. A key simulation-based task is the generation of accurate theoretical predictions for observables using a finite number of simulation runs, via the method of emulation. Using a new sampling technique, we explore an eight-dimensional parameter space including massive neutrinos and a variable equation of state of dark energy. We construct trial emulators using two surrogate models (the linear power spectrum and an approximate halo mass function). The new sampling method allows us to build precision emulators from just 26 cosmological models and to systematically increase the emulator accuracy by adding new sets of simulations in a prescribed way. Emulator fidelity can now be continuously improved as new observational data sets become available and higher accuracy is required. Finally, using one ΛCDM cosmology as an example, we study the demands imposed on a simulation campaign to achieve the required statistics and accuracy when building emulators for investigations of dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Use of Remote Sensing and In-Situ Observations to Develop and Evaluate Improved Representations of Convection and Clouds for the ACME Model

The overachieving goal of the whole CMDV-MCS project is to improve understanding of warm season continental convection and to develop treatments of convection and microphysics capable of representing mesoscale convective systems (MCSs) features in large-scale models. Our tasks for this project contributing to the overachieving goal include: (1) Improve the ice nucleation formulation for MG2 and P3 cloud microphysics schemes; (2) Improve the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM; and (3) Test the performance of improved ice microphysics in E3SM with observation data. In this project, we have (1) Improved the ice nucleation parameterization for MG2 and P3 in E3SM by implementing two advanced empirical parameterizations with connection to aerosols. The two deterministic heterogeneous ice nucleation parameterizations (i.e., DeMott et al., 2015; Niemand et al., 2012) were merged with the MG2 and P3 cloud microphysics schemes in E3SM. Long-term simulations were conducted to examine the impacts of these new parameterizations on simulated cloud properties; (2) Improved the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM. We evaluated the double Gaussian PDF of vertical velocity simulated by the Cloud Layers Unified By Binormals (CLUBB) and the sub-column vertical velocity sampled from the Subgrid Importance Latin Hypercube Sampler (SILHS) in E3SM. We introduced the vertical velocity variance induced by topographic gravity waves for ice nucleation and droplet activation; and (3) Tested the performance of improved ice microphysics in E3SM with observation data. We tested the new treatments of ice nucleation in the single column model (SCM) mode for the stratiform mixed-phase clouds observed during 9-10 October 2004 in the DOE ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) and for the convective clouds observed on 20 May 2011 in the Midlatitude Continental Convective Clouds Experiment (MC3E). Modeled ice nucleating particles (INPs) concentrations were compared against observations collected around the globe.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Improving Prediction of Surface Solar Irradiance Variability by Integrating Observed Cloud Characteristics and Machine Learning

A 5-year, 1-minute resolution observational dataset of clouds and solar radiation was produced that includes two metrics of the variability in surface solar irradiance due to cloud type and fractional sky cover. Multiple regression models were trained to fit observations of surface solar irradiance variability from those two cloud property predictors. We found that ensemble tree-based methods, Random Forest and Gradient Boosting Machine, have the least overfitting issues and showed the best performance with an R2 of 0.42. While the observational data trained in this study was only from one site, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, initial comparisons of the seasonality of the statistics suggest that these results are relatively weather regime independent; the generality of such a finding across sites will be tested in future work. The observational data and developed machine learning model are being used to create a numerical weather prediction model parameterization to enable day-ahead solar variability prediction in a computationally efficient way. This is a first step towards creating a new paradigm of predicting day-ahead variability with the potential to provide a new tool to improve grid operation, planning, and resilience.

Riihimaki, Laura↗

NASA NTRS1990

The program on radiative inputs of the sun to the Earth (rise)

General concerns about changes in the Earth's climate and in the ozone layer have increased the importance of measuring and understanding variations in the sun's radiative outputs. These outputs appear, for instance, at the top of the list of global change forcing agents in the recent FY-90 document on the U.S. Global Change Program. Significant advances have been made over the past decade in radiometry of the total solar irradiance. Photometry of light variations in stars similar to the sun, but much younger, is providing new insights into the sun's variations in luminosity and UV radiation at previous epochs of interest to paleoclimate studies. Measurement of the sun's 11-year output variability in the ultraviolet and extreme ultraviolet still possess a challenge of great importance. All of these topics are addressed by the program on Radiative Inputs of the Sun to Earth (RISE). RISE is a 5-year program of observations, data analysis, and theory, that has been defined at two workshops held in Boulder, Colorado in November 1987, and in Tucson, Arizona in October 1989. These meetings involved about 60 solar and atmospheric physicists, and stellar astronomers. A proceedings of the 1987 workshop was issued in early 1988. A substantial component of the program, consisting of ground-based observations, data analysis, and theory, is directed at the National Science Foundation (NSF) and the program is seeking a FY-92 funding start at the NSF. RISE also makes recommendations on measurements required from NASA and NOAA satellites.

Foukal, Peter V.↗

NASA NTRS2022

Preferential Acceleration of Heavy Ions in a Spontaneously Fragmenting Flare Current Sheet

We study the ion acceleration in a mesoscale, spontaneously fragmenting flare current sheet (SFCS) characterized by the presence of a plasmoid cascade. The main subject of our investigation is to determine whether and how plasmoid cascades at intermediate scales in a fragmented current sheet of a solar flare can impact the (preferential) acceleration of specific ions. The time evolution of the SFCS is obtained from high-resolution 2.5D MHD simulations. The ion trajectories (in the background fields resulting from the MHD model), energies, and pitch angles are calculated using a relativistic test-particle code based on the half-acceleration–rotation–half-acceleration method. For light ions, the main acceleration effects of electromagnetic fields within the SFCS are analyzed using the guiding center approximation. We identify regions with the most-efficient ion acceleration within the SFCS, the accelerator efficiency, and spectra of the accelerated ions. The influence of the charge-to-mass ratio on ion behavior is also studied and resulting ion abundances are compared with observational data. The main ion acceleration takes place in the regions with a strong polarization term, which is part of the first-order Fermi acceleration. Because the term is mass dependent, heavier ions undergo preferential acceleration. The ion energy spectra, abundance-enhancement factors, and differential fluxes, obtained from the model, exhibit power-law profiles, in agreement with observed solar energetic particle events. Nonetheless, the obtained slopes for the abundance-enhancement factor do not exactly match the observed data. The computed slopes and profiles are not sensitive to changes in the initial plasma temperature.

David Kramoliš↗

NASA NTRSDate not supplied

Populating a Graph Database to Run a Usage-Based Discovery Tool

Most dataset discovery tools for Earth Observation data rely on descriptions and other metadata of the datasets, using keyword searches or attribute filtering to determine relevance. However, these descriptions often do not include the potential uses of the data. Thus, a user working on floods will rarely see few if any rainfall datasets show up in such a search. The Usage Based Discovery tool, on the other hand, offers usage instances to the user, either research articles or applications, along with the datasets that those usage instances used. This allows a user, particularly one new to the world of Earth Observation data, to investigate which datasets are used in similar cases. The information that powers Usage-Based Discovery is a graph database of relationships of usage to dataset and usage to topic, allowing the user to narrow their search for similar cases. In order to scale out to a graph database rich enough to provide a satisfactory user experience, we combine manual and automated processes to populate the graph. The initial content of the graph has been seeded primarily via human-aided data curation methods, using sites like Google Scholar. To scale up this effort, we’ve employed crowdsourcing. It is easy for anyone to contribute to our graph using their Open Researcher and Contributor Identifier for authorization. We’re now experimenting with Machine Learning and Natural Language Processing to help automate population of the graph, starting with the classification of research articles by topic. Finding adequate training data in the absence of a comprehensive and open research article API continues to be a significant challenge.

Vincent Inverso↗

DOE OSTI2018

Wave Resource Characterization Using an Unstructured Grid Modeling Approach

This paper presents a modeling study conducted on the central Oregon coast for wave resource characterization using the unstructured-grid SWAN model coupled with a nested-grid WWIII model. The flexibility of models of various spatial resolutions and the effects of open- boundary conditions simulated by a nested-grid WWIII model with different physics packages were evaluated. The model results demonstrate the advantage of the unstructured-grid modeling approach for flexible model resolution and good model skills in simulating the six wave resource parameters recommended by the International Electrotechnical Commission in comparison to the observed data in Year 2009 at National Data Buoy Center Buoy 46050. Notably, spectral analysis indicates that the ST4 physics package improves upon the model skill of the ST2 physics package for predicting wave power density for large waves, which is important for wave resource assessment, device load calculation, and risk management. In addition, bivariate distributions show the simulated sea state of maximum occurrence with the ST4 physics package matched the observed data better than that with the ST2 physics package. This study demonstrated that the unstructured-grid wave modeling approach, driven by the nested-grid regional WWIII outputs with the ST4 physics package, can efficiently provide accurate wave hindcasts to support wave resource characterization. Our study also suggests that wind effects need to be considered if the dimension of the model domain is greater than approximately 100 km, or O (10^2 km).

Wu, Wei-Cheng↗

NASA NTRS1987

The terminal area simulation system. Volume 2: Verification cases

The numerical simulation of five case studies are presented and are compared with available data in order to verify the three-dimensional version of the Terminal Area Simulation System (TASS). A spectrum of convective storm types are selected for the case studies. Included are: a High-Plains supercell hailstorm, a small and relatively short-lived High-Plains cumulonimbus, a convective storm which produced the 2 August 1985 DFW microburst, a South Florida convective complex, and a tornadic Oklahoma thunderstorm. For each of the cases the model results compared reasonably well with observed data. In the simulations of the supercell storms many of their characteristic features were modeled, such as the hook echo, BWER, mesocyclone, gust fronts, giant persistent updraft, wall cloud, flanking-line towers, anvil and radar reflectivity overhang, and rightward veering in the storm propagation. In the simulation of the tornadic storm a horseshoe-shaped updraft configuration and cyclic changes in storm intensity and structure were noted. The simulation of the DFW microburst agreed remarkably well with sparse observed data. The simulated outflow rapidly expanded in a nearly symmetrical pattern and was associated with a ringvortex. A South Florida convective complex was simulated and contained updrafts and downdrafts in the form of discrete bubbles. The numerical simulations, in all cases, always remained stable and bounded with no anomalous trends.

Proctor, F. H.↗

NASA NTRS1973

Gamma-ray observations of the galactic centre.

Review of observation data obtained with a portable gas-Cerenkov gamma-ray telescope flown twice from Parana, Argentina (31.8 deg S), to search for gamma radiation from the galactic center. The angular resolution of this detector is not good enough to resolve the source structure controversy, i.e. whether the gamma radiation is coming from point sources or from a diffuse source along the galactic plane. Comparisons with observation data of other investigators are presented and discussed.

Helmken, H. F.↗

NASA NTRS2011

Influence of Dust and Black Carbon on the Snow Albedo in the NASA Goddard Earth Observing System Version 5 Land Surface Model

Present-day land surface models rarely account for the influence of both black carbon and dust in the snow on the snow albedo. Snow impurities increase the absorption of incoming shortwave radiation (particularly in the visible bands), whereby they have major consequences for the evolution of snowmelt and life cycles of snowpack. A new parameterization of these snow impurities was included in the catchment-based land surface model used in the National Aeronautics and Space Administration Goddard Earth Observing System version 5. Validation tests against in situ observed data were performed for the winter of 2003.2004 in Sapporo, Japan, for both the new snow albedo parameterization (which explicitly accounts for snow impurities) and the preexisting baseline albedo parameterization (which does not). Validation tests reveal that daily variations of snow depth and snow surface albedo are more realistically simulated with the new parameterization. Reasonable perturbations in the assigned snow impurity concentrations, as inferred from the observational data, produce significant changes in snowpack depth and radiative flux interactions. These findings illustrate the importance of parameterizing the influence of snow impurities on the snow surface albedo for proper simulation of the life cycle of snow cover.

Yasunari, Teppei J.↗

NASA NTRS2000

Dynamical Reference Frame: Current Relevance and Future Prospects

Planetary and lunar ephemerides are no longer used for the determination of inertial space. Instead, the new fundamental reference frame, the International Celestial Reference Frame (ICRF), is inherently less susceptible to extraneous, non-inertial rotations than a dynamical reference frame determined by the ephemerides would be. Consequently, the ephemerides are now adjusted onto the ICRF, and they are fit to two modern, accurate observational data types: ranging (radar, lunar laser, spacecraft) and Very Long Baseline Interferometry (VLBI) (of spacecraft near planets). The uncertainties remaining in the inner planet ephemerides are on the order of 1 kilometer, both in relative positions between the bodies and in the orientation of the inner system as a whole. The predictive capabilities of the inner planet ephemerides are limited by the uncertainties in the masses of many asteroids. For this reason, future improvements to the ephemerides must await determinations of many asteroid masses. Until then, it will be necessary to constantly update the ephemerides with a continuous supply of observational data.

VLBI (VERY LONG BASELINE INTERFEROMETRY)↗

DOE OSTI2024

Multi-year assessment of the impact of ship-borne radiosonde observations on polar WRF forecasts in the Arctic

Abstract To compensate for the lack of conventional observations over the Arctic Ocean, ship-borne radiosonde observations have been regularly carried out during summer Arctic expeditions and the observed data have been broadcast via the global telecommunication system since 2017. With these data obtained over the data-sparse Arctic Ocean, observing system experiments were carried out using a polar-optimized version of the Weather Research and Forecasting (WRF) model and the WRF Data Assimilation (WRFDA) system to investigate their effects on analyses and forecasts over the Arctic. The results of verification against reanalysis data reveal: (1) DA effects on analyses and forecasts; (2) the reason for the year-to-year variability of DA effects; and (3) the possible role of upper-level potential vorticity in delayed DA effects. The overall assimilation effects of the extra data on the analyses and forecasts over the Arctic are positive. Initially, the DA effects are the most apparent in the temperature variables in the middle/lower troposphere, which spread to the wind variables in the upper troposphere. The effects decrease with time but reappear after approximately 120 h, even in the 240-h forecasts. The effects on forecasts vary depending on the proximity of the radiosonde observation locations to the high synoptic variability. The upper-level potential vorticity is known to play an important role in the development of Arctic cyclones, and it is suggested as a possible explanation for the delayed DA effects after about 120 h.

Geology↗

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↗