Space Physics Data Facility

Hourly averaged interplanetary magnetic field (IMF) and plasma data from the Advanced Composition Explorer (ACE) and Wind spacecraft, generated from 1 to 4 min resolution data time‐shifted to Earth have been analyzed for systematic and random differences. ACE moments‐based proton densities are larger than Wind/Solar Wind Experiment (SWE) fits‐based densities by up to 18%, depending on solar wind speed. ACE temperatures are less than Wind/SWE temperatures by up to ∼25%. ACE densities and temperatures were normalized to equivalent Wind values in National Space Science Data Center's creation of the OMNI 2 data set that contains 1963–2004 solar wind field and plasma data and other data. For times of ACE‐Wind transverse separations <60 R E , random differences between Wind values and normalized ACE values are ∼0.2 nT for ∣ B ∣, ∼0.45 nT for IMF Cartesian components, ∼5 km/s for flow speed, and ∼15 and ∼30% for proton densities and temperatures. These differences grow as a function of transverse separation more rapidly for IMF parameters than for plasma parameters. Autocorrelation analyses show that spatial scales become progressively shorter for the parameter sequence: flow speed, IMF magnitude, plasma density and temperature, IMF X and Y components, and IMF Z component. IMF variations have shorter scales at solar quiet times than at solar active times, while plasma variations show no equivalent solar cycle dependence.

This chapter contains sections titled: Introduction The NASA Trapped Radiation Models: AP-8 & AE-8 Comparisons with Recent Observations A New Generation of Trapped Radiation Models Summary and Conclusions

Magnetic field, electric field and energetic electron measurements from CRRES, GOES‐6 and ‐7 satellites are used to investigate the production of up to 2 MeV electron fluxes through a storm sudden commencement (SSC) event on August 27, 1991. Strong Pc‐5 oscillations, whose electric field is mainly along the radial direction, and up to an order‐of‐magnitude enhancement in relativistic electron fluxes occurred simultaneously in a two‐hour period. The enhanced electron fluxes are found to have a pancake‐like pitch angle distribution, which is consistent with the fluxes being accelerated near the equatorial plane. The electron acceleration is shown to result from drift‐resonant interactions with the toroidal‐mode Pc‐5 ULF waves having wave frequencies three times the electron drift frequency. In view of the L‐variation of ULF wave frequencies, electron acceleration to relativistic energies becomes more effective in the geosynchronous region.

Prompt and accurate imaging of the ionosphere is essential to space weather services, given a broad spectrum of applications that rely on ionospherically propagating radio signals. As the 3D spatial extent of the ionosphere is vast and covered only fragmentarily, data fusion is a strong candidate for solving imaging tasks. Data fusion has been used to blend models and observations for the integrated and consistent views of geosystems. In space weather scenarios, low latency of the sensor data availability is one of the strongest requirements that limits the selection of potential datasets for fusion. Since remote plasma sensing instrumentation for ionospheric weather is complex, scarce, and prone to unavoidable data noise, conventional 3D-var assimilative schemas are not optimal. We describe a novel substantially 4D data fusion service based on near-real-time data feeds from Global Ionosphere Radio Observatory (GIRO) and Global Navigation Satellite System (GNSS) called GAMBIT (Global Assimilative Model of the Bottomside Ionosphere with Topside estimate). GAMBIT operates with a few-minute latency, and it releases, among other data products, the anomaly maps of the effective slab thickness (EST) obtained by fusing GIRO and GNSS data. The anomaly EST mapping aids understanding of the vertical plasma restructuring during disturbed conditions.

We present here for the first time observations of the inverse correlation between the ion temperature anisotropy and plasma beta in the Earth's high‐latitude magnetosheath. Hot proton data with energies of 0.3–8 keV were obtained from magnetosheath passages by the Hawkeye spacecraft which had a polar orbit with an apogee of 20–21 R E . A newly developed technique has been used to calculate the distribution functions of protons in their non‐streaming frame in which their first‐order anisotropy is absent. The ion‐energy dependence of distribution functions indicates the existence of two hot ion components. Thus the correlation has been examined for each hot ion component separately. We have analyzed three Hawkeye magnetosheath passes during which the magnetosheath's magnetic field was close to the spacecraft spin plane, so that the two‐dimensional Hawkeye sensor can adequately sample temperature anisotropies. Results of our analyses are consistent with the theoretical prediction given by Gary et al. [1994; 1995] that a universal inverse‐correlation relationship exists between the temperature anisotropy and plasma beta of hot ions.

We present the results from a study of time correlation between the low‐altitude relativistic trapped electron fluxes and the solar wind speeds. Our trapped electron observations in the energy range of 0.19–3.2 MeV were obtained by the OHZORA spacecraft in an altitude range of 350–850 km, near a solar minimum period (1984–87). The solar wind data with a 5‐minute time resolution were obtained from IMP‐8 observations. Linear correlation analyses between the two data sets have been performed for relative time lags varying from 12 minutes to 60 days. The 2.5–day, 13‐day, 27‐day and 54‐day correlation peaks previously reported for energetic electrons near geosynchronous orbits are clearly seen in our results. However, the use of higher time resolution solar wind data than in previous studies allows correlation analyses to be performed at shorter time lags. We report here that correlation at shorter time lags (<10 hrs) exists and that while such correlation is stronger than those observed at longer lag times, it can not be entirely attributed to storm or substorm injections. The correlation is also found to decrease with drift shell magnetic equatorial radii, r t . In addition, local‐time and radial variations in the responses of different drift shells to solar wind speed enhancements indicate that the energetic electron population enters the inner magnetosphere predominantly through the midnight sector.

As research instruments with large information capacities become a reality, automated systems for intelligent data analysis become a necessity. Scientific archives containing huge volumes of data preclude manual manipulation or intervention and require automated exploration and mining that can at least preclassify information in categories. The large data set from the radio plasma imager (RPI) instrument on board the IMAGE satellite shows a critical need for such exploration in order to identify and archive features of interest in the volumes of visual information. In this research we have developed such a preclassifier through a model of preattentive vision capable of detecting and extracting traces of echoes from the RPI plasmagrams. The overall design of our model complies with Marr's paradigm of vision, where elements of increasing perceptual strength are built bottom up under the Gestalt constraints of good continuation and smoothness. The specifics of the RPI data, however, demanded extension of this paradigm to achieve greater robustness for signature analysis. Our preattentive model now employs a feedback neural network that refines alignment of the oriented edge elements (edgels) detected in the plasmagram image by subjecting them to collective global‐scale optimization. The level of interaction between the oriented edgels is determined by their distance and mutual orientation in accordance with the Yen and Finkel model of the striate cortex that encompasses findings in psychophysical studies of human vision. The developed models have been implemented in an operational system “CORPRAL” (Cognitive Online RPI Plasmagram Ranking Algorithm) that currently scans daily submissions of the RPI plasmagrams for the presence of echo traces. Qualifying plasmagrams are tagged in the mission database, making them available for a variety of queries. We discuss CORPRAL performance and its impact on scientific analysis of RPI data.

Abstract Non‐linear Error Compensation Technique with Associative Restoration (NECTAR) is a novel approach to the assimilation of fragmentary sensor data to produce a global nowcast of the near‐Earth space weather. NECTAR restores missing information by iteratively transforming (“morphing”) an underlying global climatology model into agreement with currently available sensor data. The morphing procedure benefits from analysis of the inherent multiscale diurnal periodicity of the geosystems by processing 24‐hr time histories of the differences between measured and climate‐expected values at each sensor site. The 24‐hr deviation time series are used to compute and then globally interpolate the diurnal deviation harmonics. NECTAR therefore views the geosystem in terms of its periodic planetary‐scale basis to associate observed fragments of the activity with the grand‐scale weather processes of the matching variability scales. Such approach strengthens the restorative capability of the assimilation, specifically when only a limited number of observatories is available for the weather nowcast. Scenarios where the NECTAR concept works best are common in planetary‐scale near‐Earth weather applications, especially where sensor instrumentation is complex, expensive, and therefore scarce. To conduct the assimilation process, NECTAR employs a Hopfield feedback recurrent neural network commonly used in the associative memory architectures. Associative memories mimic human capability to restore full information from its initial fragments. When applied to the sparse spatial data, such a neural network becomes a nonlinear multiscale interpolator of missing information. Early tests of the NECTAR morphing reveal its enhanced capability to predict system dynamics over no‐data regions (spatial interpolation).

Ray tracing modeling is used to investigate the plasma conditions under which high‐frequency ( f ≫ f uh ) extraordinary mode waves can be guided along geomagnetic field lines. These guided signals have often been observed as long‐range discrete echoes in the plasmasphere by the Radio Plasma Imager (RPI) onboard the Imager for Magnetopause‐to‐Aurora Global Exploration satellite. Field‐aligned discrete echoes are most commonly observed by RPI in the plasmasphere, although they are also observed over the polar cap region. The plasmasphere field‐aligned echoes appearing as multiple echo traces at different virtual ranges are attributed to signals reflected successively between conjugate hemispheres that propagate along or nearly along closed geomagnetic field lines. The ray tracing simulations show that field‐aligned ducts with as little as 1% density perturbations (depletions) and <10 wavelengths wide can guide nearly field‐aligned propagating high‐frequency X mode waves. Effective guidance of a wave at a given frequency and wave normal angle (Ψ) depends on the cross‐field density scale of the duct, such that ducts with stronger density depletions need to be wider in order to maintain the same gradient of refractive index across the magnetic field. While signal guidance by field aligned density gradient without ducting is possible only over the polar region, conjugate field‐aligned echoes that have traversed through the equatorial region are most likely guided by ducting.

We report the observations of changes of the nominal position of the quiet‐time radiation belt slot over the solar cycles. It has been found that the slot region, believed to be a result of enhanced precipitation losses of energetic electrons due to their interactions with VLF waves in the magnetosphere, tends to shift to higher L (∼3) during a solar maximum compared to its canonical L value of ∼2.5, which is more typical of a solar minimum. The solar‐cycle migration of the slot can be understood in terms of the solar‐cycle changes in ionospheric densities, which may cause the optimal wave‐particle interaction region during higher solar activity periods to move to higher altitudes and higher latitudes, thus higher L . Our analysis also suggests that the primary regions of wave‐particle interaction processes that result in the slot formation are located off of the magnetic equator.

A confluence of technologies is leading towards revolutionary new interactions between robust data sets, state-of-the-art models and simulations, high-data-rate sensors, and high-performance computing. Data and data systems are central to these new developments in various forms of eScience or grid systems. Space science missions are developing multi-spacecraft, distributed, communications- and computation-intensive, adaptive mission architectures that will further add to the data avalanche. Fortunately, Knowledge Discovery in Database (KDD) tools are rapidly expanding to meet the need for more efficient information extraction and knowledge generation in this data-intensive environment. Concurrently, scientific data management is being augmented by content-based metadata and semantic services. Archiving, eScience and KDD all require a solid foundation in interoperability and systems architecture. These concepts are illustrated through examples of space science data preservation, archiving, and access, including application of the ISO-standard Open Archive Information System (OAIS) architecture.

The Radio Plasma Imager (RPI) aboard the IMAGE spacecraft probes plasma at both far and near ranges by means of radio sounding. The RPI plasmagrams, similar in their concept to the ground‐based and topside ionograms, contain not only a variety of signatures pertaining to the remote plasma structures and boundaries, but also a suite of the local plasma resonances stimulated by the RPI radio transmissions. Detection and interpretation of the resonance signatures is a valuable diagnostic tool providing the actual electron density and magnetic field strength at the spacecraft location, which are needed for the accurate processing of the remote sensing information on the plasmagrams. The high volume of the RPI sounding data demanded the development of automated techniques for routine interpretation of the plasmagrams. This paper discusses a new method for the detection and interpretation of the resonance signatures in the RPI plasmagrams that employs pattern recognition techniques to localize the signatures and identifies them in relation to model‐based resonances.

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation John F. Cooper, Matthew E. Hill, John D. Richardson, Steven J. Sturner; Proton irradiation environment of solar system objects in the heliospheric boundary regions. AIP Conf. Proc. 26 September 2006; 858 (1): 372–380. https://doi.org/10.1063/1.2359353 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search

Abstract Since the mid-1990s, many geomagnetic datasets began appearing on the World Wide Web. Often these data were not submitted to the World Data Centers as recommended since the International Geophysical Year (1957- 58). As a result, existing data become naturally distributed creating an urgent need for more sophisticated search engines capable of identifying and retrieving the data from Web for scientific analyses. We introduce a Virtual Global Magnetic Observatory concept for “pulling” geomagnetic data distributed worldwide. The VGMO moves information exchange from simple file transfers to a higher level of abstraction, forming the distributed databases through establishment of self-organizing data nodes. We present the first working VGMO prototype: an “on-demand” objects-building Internet application that is transparent in its internal data management to the external users/clients. The VGMO server continuously builds data-objects only from client requests by going through a pre-set list of Web-based data nodes (including WDCs). As the retrieved data are added to the server (or node) database, future requests of the same interval would not force a new Web search. Furthermore, new nodes can be made available to others through the VGMO network, building the worldwide geomagnetic data “fabric” in a platform-independent and location-neutral environment of newly “webbed“ digital data. Application is on a server at http://mist.engin.umich.edu.

On-chip interconnects form complex networks composed of coupled metal lines on oxide and substrate layers. Substrate parasitic effects (substrate currents and propagation loss) are becoming limiting factors to the performance of modern high-speed digital and analog integrated circuits (ICs). Signals traveling along the metal-insulator-silicon-metal (MISM) structure (a fundamental on-chip interconnect unit) will have different attenuation and dispersion when changing operation frequencies and substrate doping densities. These are categorized into three fundamental propagation modes: the slow-wave mode, the dielectric quasi-TEM mode, and the skin-effect mode (Hasegawa et al., 1971). In high-speed radio frequency (RF) circuits, interconnects are likely to operate in the skin-effect mode. In this mode, the nonideal substrate functions as a current return path of the signal, located very close to the oxide layer. Accurate modeling of interconnects in this mode is difficult, because the Courant's stability condition limits most explicit time-domain full-wave Maxwell solvers. To overcome this problem, we apply the alternating-direction-implicit finite-difference time-domain (ADI-FDTD) method (Namiki, 1999) to solve Maxwell's equations. In spite of the conductor loss, we have found considerable substrate current and loss, which depend on the substrate doping and operation frequency

This chapter contains sections titled: Introduction Simulation Models Three Types of Particle Trajectory in the Magnetosphere Shabansky Orbit Accessibility Map Summary

Alternating-Direction-Implicit (ADI) method is used to solve the Maxwell's equation in ICs, and to overcome the Courant's limit. We have used ADI method to model the Metal-Insulator-Semiconductor-Substrate (MISS) structure. The simulations allowed us to calculate propagation losses, skin depth and dispersion of digital signals on non-ideal interconnects. The simulation results substrate currents and losses that depend on the substrate doping.

International audience

Plasma flow velocity, critical for studying plasma dynamics, usually has been obtained by computing the first moment of the measured ion velocity distribution. This standard method is valid when a full ion distribution is sufficiently sampled. Alternate ways to calculate the flow velocity also exist. For instance, by assuming the existence of a rest frame in which energetic ions are isotropic, Gloeckler et al. [1984] found that the velocity of the rest' frame relative to the spacecraft frame is equal to the ion flow velocity. However, in many cases including the magnetosheath or magnetospheric boundaries, the existence of a rest frame is doubtful because of the presence of ion temperature anisotropies. We hence generalize the rest frame concept by introducing a non-streaming frame in which the ion first-order anisotropy is assumed to be absent. If this non-streaming frame indeed exists, its velocity relative to the spacecraft frame represents the flow velocity of a given ion component. An iteration technique has been developed to search for the non-streaming frame. Magnetosheath ion observations indicate that our approach is suitable for examining the co-existence of multiple plasma populations.

Whitepaper #289 in the Decadal Survey for Solar and Space Physics (Heliophysics) 2024-2033. Main topics: space weather applications; infrastructure/workforce/other programmatic. Additional topics: other programmatic; other space weather.