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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Analyses of ∼0.05–2 MeV Ions Associated with the 2022 February 16 Energetic Storm Particle Event Observed By Parker Solar Probe

We present analyses of 0.05–2 MeV ions from the 2022 February 16 energetic storm particle event observed by Parker Solar Probeʼs (PSP) ISeIS/EPI-Lo instrument at 0.35 au from the Sun. This event was characterized by an enhancement in ion fluxes from a quiet background, increasing gradually with time with a nearly flat spectrum, rising sharply near the arrival of the coronal mass ejection (CME)–driven shock, becoming nearly a power-law spectrum, then decaying exponentially afterward, with a rate that was independent of energy. From the observed fluxes, we determine diffusion coefficients, finding that far upstream of the shock the diffusion coefficients are nearly independent of energy, with a value of 10 20 cm 2 s −1 . Near the shock, the diffusion coefficients are more than 1 order of magnitude smaller and increase nearly linearly with energy. We also determine the source of energetic particles, by comparing ratios of the intensities at the shock to estimates of the quiet-time intensity to predictions from diffusive shock acceleration theory. We conclude that the source of energetic ions is mostly the solar wind for this event. We also present potential interpretations of the near-exponential decay of the intensity behind the shock. One possibility we suggest is that the shock was over expanding when it crossed PSP and the energetic particle intensity decreased behind the shock to fill the expanding volume. Over expanding CMEs could well be more common closer to the Sun, and this is an example of such a case.

Interplanetary particle acceleration↗
DOE OSTI2025

Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.

17 WIND ENERGY↗
DOE OSTI2017

Characterization of induced seismicity patterns derived from internal structure in event clusters

Microseismicity induced by CO 2 injection at Decatur, Illinois, occurs in distinct clusters and shows no obvious correlation with the proceeding pressure front. Here, we analyze some of these clusters in more depth by using a waveform cross-correlation approach. With this approach we can associate about 1400 events from two clusters, with moment magnitudes between 1.1 and -1.7, with specific formations of much smaller vertical dimensions (tens of meters) than the depth resolution of traveltime-based event locations. The differentiation of reservoir and basement events, and the definition of subclusters by waveform correlation, rather than by location, helps to better analyze the spatiotemporal evolution of the events within a cluster. In the Decatur case, this is characterized by event migration from the reservoir into the adjacent basement. The spatial variation of Brune stress drop and Gutenberg b value exhibits signs of a fluid-driven triggering mechanism at the cluster level, revealing a punctual hydraulic connection between reservoir and basement, most likely associated with basement faults cutting into the reservoir. The observed clustering of microseismicity can thus be explained by the lateral heterogeneity of permeability and crustal strength and is overall consistent with a pressure-induced triggering mechanism. Hence, proper long-term risk mitigation for large-scale fluid injection close to the basement requires prior mapping of small subseismic basement-connected faults.

58 GEOSCIENCES↗
DOE OSTI2022

Quantifying Carbon Cycle Extremes and Attributing Their Causes Under Climate and Land Use and Land Cover Change From 1850 to 2300

The increasing atmospheric carbon dioxide (CO 2 ) mole fraction affects global climate through radiative (trapping longwave radiation) and physiological effects (reduction of plant transpiration). We use the simulations of the Community Earth System Model (CESM1-BGC) forced with Representative Concentration Pathway 8.5 to investigate climate-vegetation feedbacks from 1850 to the year 2300. Human-induced land use and land cover change (LULCC), through biogeochemical and biogeophysical processes, alter the climate and modify photosynthetic activity. The changing characteristics of extreme anomalies in photosynthesis, referred to as carbon cycle extremes, increase the uncertainty of terrestrial ecosystems to act as a net carbon sink. However, the role of LULCC in altering carbon cycle extremes under business-as-usual (continuously rising) CO 2 emissions is unknown. Here we show that LULCC magnifies the intensity, frequency, and extent of carbon cycle extremes, resulting in a net reduction in expected photosynthetic activity in the future. We found that large temporally contiguous negative carbon cycle extremes are due to a persistent decrease in soil moisture, which is triggered by declines in precipitation. With LULCC and global warming, vegetation exhibits increased vulnerability to hot and dry environmental conditions, increasing the frequency of fire events and resulting in considerable losses in photosynthetic activity. While most regions show strengthening of negative carbon cycle extremes, a few locations show a weakening effect driven by declining vegetation cover or benign climate conditions for photosynthesis. Increasing hot, dry, and fire-driven carbon cycle extremes are essential for improving carbon cycle modeling and estimation of ecosystem responses to LULCC and rising CO 2 mole fractions. Moreover, large aberrations in vegetation productivity represent potential and growing threats to human lives, wildlife, and food security.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Dynamo-driven plasmoid formation from a current-sheet instability

Axisymmetric current-carrying plasmoids are formed in the presence of nonaxisymmetric fluctuations during nonlinear three-dimensional resistive MHD simulations in a global toroidal geometry. In this study, we utilize the helicity injection technique to form an initial poloidal flux in the presence of a toroidal guide field. As helicity is injected, two types of current sheets are formed from the oppositely directed field lines in the injector region (primary reconnecting current sheet), and the poloidal flux compression near the plasma edge (edge current sheet). We first find that nonaxisymmetric fluctuations arising from the current-sheet instability isolated near the plasma edge have tearing parity but can nevertheless grow fast (on the poloidal Alfven time scale). These modes saturate by breaking up the current sheet. Second, for the first time, a dynamo poloidal flux amplification is observed at the reconnection site (in the region of the oppositely directed magnetic field). This fluctuation-induced flux amplification increases the local Lundquist number, which then triggers a plasmoid instability and breaks the primary current sheet at the reconnection site. Finally, the plasmoids formation driven by large-scale flux amplification, i.e., a large-scale dynamo, observed here has strong implications for astrophysical reconnection as well as fast reconnection events in laboratory plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

The frequency of extreme X-ray variability for radio-quiet quasars

ABSTRACT We analyse 1598 serendipitous Chandra X-ray observations of 462 radio-quiet quasars to constrain the frequency of extreme amplitude X-ray variability that is intrinsic to the quasar corona and innermost accretion flow. The quasars in this investigation are all spectroscopically confirmed, optically bright (mi ≤ 20.2), and contain no identifiable broad absorption lines in their optical/ultraviolet spectra. This sample includes quasars spanning z ≈ 0.1–4 and probes X-ray variability on time-scales of up to ≈12 rest-frame years. Variability amplitudes are computed between every epoch of observation for each quasar and are analysed as a function of time-scale and luminosity. The tail-heavy distributions of variability amplitudes at all time-scales indicate that extreme X-ray variations are driven by an additional physical mechanism and not just typical random fluctuations of the coronal emission. Similarly, extreme X-ray variations of low-luminosity quasars seem to be driven by an additional physical mechanism, whereas high-luminosity quasars seem more consistent with random fluctuations. The amplitude at which an X-ray variability event can be considered extreme is quantified for different time-scales and luminosities. Extreme X-ray variations occur more frequently at long time-scales (Δt ≳ 300 d) than at shorter time-scales and in low-luminosity quasars compared to high-luminosity quasars over a similar time-scale. A binomial analysis indicates that extreme intrinsic X-ray variations are rare, with a maximum occurrence rate of $\lt 2.4{{\ \rm per\ cent}}$ of observations. Finally, we present X-ray variability and basic optical emission-line properties of three archival quasars that have been newly discovered to exhibit extreme X-ray variability.

Timlin, III, John D.↗
DOE OSTI2017

Observations of a Coronal Shock Wave and the Production of Solar Energetic Particles

We present a study that clarifies the acceleration source/mechanism of the solar energetic particle (SEP) event on 2011 August 9. Based on the assumption of scatter-free propagation of charged particles along the interplanetary magnetic field, the solar particle release times of the electrons and protons are derived and both found to be in the decay phase of the flare emission. Furthermore, we compare the peak-flux spectra of the in situ particles and the remote-sensing hard X-ray photons and find a weak correlation between them. In particular, we note that an extreme ultraviolet shock wave, presumed to be a signature of coronal mass ejection (CME) shock front on the solar surface, and an associated type II radio burst were observed alongside this event. Under the framework of diffusive shock acceleration, the derived shock compression ratio can accelerate particles with a theoretical spectral index γ=2.14{sub −0.02}{sup +0.01}, which is comparable to the observational index of ∼2.0. Our results appear to support the notion that the coronal shock wave was most likely responsible for the SEP event. Specifically, we find that the electrons were released in a low coronal site at ∼0.58 solar radii, and protons were released when the CME-driven shock propagated to ∼1.38 solar radii. The multi-spacecraft observations, in addition, reveal the connection between the acceleration of shock waves and the release of SEPs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

The radio signatures of a slow coronal mass ejection - Electron acceleration at slow-mode shocks?

The evolution of a coronal mass ejection (CME) event observed on February 17, 1985 is studied using two-dimensional radio imaging observations along with simultaneously obtained coronagraph observations. This event shows that a slow CME can be associated with type II and type IV radio bursts. The implications of the spatial association of the radio bursts with the CME are discussed. It is argued that the CME is due to an instability of the large-scale magnetic field in a helmet streamer and that the radio bursts are some of the responses to this instability. The new feature of this event is the clear association of the moving type IV burst with a CME traveling slower than the coronal Alfven speed. The structure of slow shocks driven by such a CME is discussed, and it is shown that shock drift and diffusive acceleration are ineffective. An acceleration mechanism involving current-driven lower hybrid waves is proposed.

Kundu, M.↗
NASA NTRS1996

Thermal Control Subsystem Design for the Avionics of a Space Station Payload

A case study of the thermal control subsystem development for a space based payload is presented from the concept stage through preliminary design. This payload, the Space Acceleration Measurement System 2 (SAMS-2), will measure the acceleration environment at select locations within the International Space Station. Its thermal control subsystem must maintain component temperatures within an acceptable range over a 10 year life span, while restricting accessible surfaces to touch temperature limits and insuring fail safe conditions in the event of loss of cooling. In addition to these primary design objectives, system level requirements and constraints are imposed on the payload, many of which are driven by multidisciplinary issues. Blending these issues into the overall system design required concurrent design sessions with the project team, iterative conceptual design layouts, thermal analysis and modeling, and hardware testing. Multiple tradeoff studies were also performed to investigate the many options which surfaced during the development cycle.

Moran, Matthew E.↗
NASA NTRS2012

Solar Radio Bursts and Space Weather

Radio bursts from the Sun are produced by electron accelerated to relativistic energies by physical processes on the Sun such as solar flares and coronal mass ejections (CMEs). The radio bursts are thus good indicators of solar eruptions. Three types of nonthermal radio bursts are generally associated with CMEs. Type III bursts due to accelerated electrons propagating along open magnetic field lines. The electrons are thought to be accelerated at the reconnection region beneath the erupting CME, although there is another view that the electrons may be accelerated at the CME-driven shock. Type II bursts are due to electrons accelerated at the shock front. Type II bursts are also excellent indicators of solar energetic particle (SEP) events because the same shock is supposed accelerate electrons and ions. There is a hierarchical relationship between the wavelength range of type /I bursts and the CME kinetic energy. Finally, Type IV bursts are due to electrons trapped in moving or stationary structures. The low frequency stationary type IV bursts are observed occasionally in association with very fast CMEs. These bursts originate from flare loops behind the erupting CME and hence indicate tall loops. This paper presents a summary of radio bursts and their relation to CMEs and how they can be useful for space weather predictions.

Gopalswamy, Natchimuthuk,↗
NASA NTRS2018

Forecasting the Arrival Time of Coronal Mass Ejections: Analysis of the CCMC CME Scoreboard

Accurate forecasting of the properties of coronal mass ejections (CMEs) as they approach Earth is now recognized as an important strategic objective for both NOAA and NASA. The time of arrival of such events is a key parameter, one that had been anticipated to be relatively straightforward to constrain. In this study, we analyze forecasts submitted to the Community Coordinated Modeling Center at NASA's Goddard Space Flight Center over the last 6 years to answer the following questions: (1) How well do these models forecast the arrival time of CME-driven shocks? (2) What are the uncertainties associated with these forecasts? (3) Which model(s) perform best? (4) Have the models become more accurate during the past 6 years? We analyze all forecasts made by 32 models from 2013 through mid-2018, and additionally focus on 28 events, all of which were forecasted by six models. We find that the models are generally able to predict CME-shock arrival times, in an average sense, to within ±10 hr, but with standard deviations often exceeding 20 hr. The best performers, on the other hand, maintained a mean error (bias) of 1 hr, a mean absolute error of 13 hr, and a precision (standard deviation) of 15 hr. Finally, there is no evidence that the forecasts have become more accurate during this interval. We discuss the intrinsic simplifications of thevarious models analyzed, the limitations of this investigation, and suggest possible paths to improve these forecasts in the future.

space weather↗
NASA NTRS2010

The Fate of Saharan Dust Across the Atlantic: An Integrated Modeling and Observational Study of the TC4 Field Campaign

During the NASA TC-4 field campaign in July 2007, several Saharan dust events were observed over the Caribbean basin. A-Train observations suggest that these Saharan dust events are confined the Caribbean and rarely transported across Central America to the Pacific Ocean. We investigate the nature of this barrier to dust transport using the NASA GEOS-5 atmospheric general circulation model. Our simulations with GEOS-5 are driven by the Modern Era Retrospective-Analysis for Research and Applications (MERRA) meteorological analyses, and include online simulation of aerosol distributions using a version of the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model. Simulated dust distributions are evaluated using A-Train observations from MODIS and CALIOP, as well as MISR and ground-based AERONET sun photometers, and show good agreement with the observations in terms of the timing and magnitude of dust events. A component analysis of the dust transport and removal pathways is used to evaluate the relative roles of these processes in establishing the observed dust transport barrier. From this analysis, we show that while both atmospheric dynamics and wet removal contribute towards the Caribbean dust barrier, northward dust transport is the more dominant term. Additional simulations are performed to ascertain the sensitivity of our results to uncertain loss processes (i.e., wet removal) in our model.

Nowottnick, E.↗
NASA NTRS2010

The Relationship of Magnetotail Flow Bursts and Ground Onset Signatures

It has been known for decades that auroral substorm onset occurs on (or at least near) the most equatorward auroral arc, which is thought to map to the near geosynchronous region. The lack of auroral signatures poleward of this arc prior to onset has been a major criticism of flow-burst driven models of substorm onset. The combined THEMIS 5 spacecraft in-situ and ground array measurements provide an unprecedented opportunity to examine the causal relationship between midtail plasma flows, aurora, and ground magnetic signatures. I first present an event from 2008 using multi-spectral all sky imager data from Gillam and in-situ data from THEMIS. The multispectral data indicate an equatorward moving auroral form prior to substorm onset. When this forms reaches the most equatorward arc, the arc brightens and an auroral substorm begins. The THEMIS data show fast Earthward flows prior to onset as well. I discuss further the association of flow bursts and Pi2 pulsations, in the con text of the directly-driven Pi2 model. This model directly links flows and Pi2 pulsations, providing an important constraint on substorm onset theories.

Kepko, Larry↗
DOE OSTI2021

Episodic Earthquake Swarms in the Mineral Mountains, Utah Driven by the Roosevelt Hydrothermal System

Over 1,000 earthquakes (-2.0 < M < 2.0), identified using a matched-filter method, occurred in the Mineral Mountains, Utah between 2016 and 2019. The enhanced catalog is complete down to M -0.9 and contains roughly 15 times more events than originally cataloged. Earthquake relocation of ~800 earthquakes shows that activity is concentrated in a <2 km long E-W striking narrow zone, ~4 km east of the Roosevelt hydrothermal system. Two fault orientations, both N-S and E-W parallel to the Opal Mound and Mag Lee faults, respectively, are observed after computing composite focal mechanisms of highly similar earthquakes. Looking solely at the temporal distribution of the seismicity, we identify 15 periods of swarm-like activity, with two major clusters occurring in December 2016, recorded by three stations, and in October 2019 recorded by eight stations. The October 2019 swarm, the best recorded sequence in the area, provides evidence for the underlying triggering mechanism. We show that a complex mechanism of fluid diffusion and aseismic slip is responsible for the swarm evolution with migration velocities reaching 10 km/day. We hypothesize that these episodic swarms in the Mineral Mountains are primarily driven by migrating fluids that originate within the Roosevelt hydrothermal system.

58 GEOSCIENCES↗
NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗
NASA NTRS1995

El Nino and La Nina Events Simulated by the Cane and Zebiak's Model and Observed with Satellite or in situ Data

The Zebiak and Cane (1987) model is first run in its 'forced mode' where the oceanic part of the model is driven by FSU wind stress anomalies over 1980-1994 to simulate sea surface temperature anomalies and those are used in the atmospheric part of the model to generate wind anomalies. Simulated thermocline depths, sea surface temperature and wind stress anomalies are first validated with observations.

climate research sea temperature sea wind El Nino ↗
DOE OSTI2017

Idealized Simulations of a Squall Line from the MC3E Field Campaign Applying Three Bin Microphysics Schemes: Dynamic and Thermodynamic Structure

The squall line event on May 20, 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the pre-convection environment at 1200 UTC in Morris, Oklahoma show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

Xue, Lulin↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗