Investigation of Different ΣO/N 2 Variations Observed by GOLD During a Minor Geomagnetic Storm From 2 to 4 August 2021
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Consideration is given to: variations in the Gauss coefficients of the geomagnetic potential over the last several hundred years; eccentric geomagnetic dipole drift; and evidence for geomagnetic jerks from 1931 to 1971. Among other topics discussed are: models of the geomagnetic field in western Europe from 1960 to 1980; the external and internal parts of the geomagnetic jerk of 1970; secular variation of the magnetic mean energy density at the source layer depth; and motions at the core surface in the geostrophic approximation. Consideration is also given to: the unpredictability of geomagnetic secular variation; the use of short-term core-mantle coupling and geomagnetic variation impulses as Lagrangian tracers of core motions; and a comparison of two sequential geomagnetic polarity transitions in the upper Olduvai and the lower Jarmillio in the Southern Hemisphere.
The most important parameter in the coupling between solar wind and geomagnetic activity is the B(sub z)‐component of the interplanetary magnetic field (IMF). However, recent studies have shown that IMF B(sub y) is an additional, independent driver of geomagnetic activity. We use here local geomagnetic indices from a large network of magnetic stations to study how IMF B(sub y) affects geomagnetic activity at different latitudes for all solar wind and, separately, during coronal mass ejections. We show that geomagnetic activity, for all solar wind, is 20% stronger for B(sub y) > 0 than for B(sub y) < 0 at subauroral latitudes of about 60° corrected geomagnetic latitude. During coronal mass ejections, the B(sub y)‐effect is larger, about 40%, at slightly lower latitudes of about 57° (corrected geomagnetic) latitude. These results highlight the importance of the IMF B(sub y)‐component for space weather at different latitudes and must be taken into account in space weather modeling
Abstract We examine how Sudden Commencements (SCs) and Storm Sudden Commencements (SSCs) influence the occurrence of high rates of change of the magnetic field ( R ) as a function of geomagnetic latitude. These rapid, high amplitude variations in the ground‐level geomagnetic field pose a significant risk to ground infrastructure, such as power networks, as the drivers of geomagnetically induced currents. We find that rates of change of ∼30 nT min −1 at near‐equatorial stations are up to 700 times more likely in an SC than in any random interval. This factor decreases with geomagnetic latitude such that rates of change around 30 nT min −1 are only up to 10 times more likely by 65°. At equatorial latitudes we find that 25% of all R in excess of 50 nT min −1 occurs during SCs. This percentage also decreases with geomagnetic latitude, reaching ≤1% by 55°. However, the time period from the SC to 3 days afterward accounts for ≥90% of geomagnetic field fluctuations over 50 nT min −1 , up to ∼60° latitude. Above 60°, other phenomena such as isolated substorms account for the majority of large R . Furthermore, the elevated rates of change observed during and after SCs are solely due to those classified as SSCs. These results show that SSCs are the predominant risk events for large R at mid and low latitudes, but that the risk from the SC itself decreases with latitude.
For improving the reliability of Space Weather prediction, we developed a new, Polar Magnetic (PM) index of geomagnetic activity, which shows high correlation with both upstream solar wind data and related events in the magnetosphere and ionosphere. Similarly to the existing polar cap PC index, the new PM index was computed from data from two near-pole geomagnetic observatories; however, the method for computing the PM index is different. The high correlation of the PM index with both solar wind data and events in Geospace environment makes possible to improve significantly forecasting geomagnetic disturbances and such important parameters as the cross-polar-cap voltage and global Joule heating, which play an important role in the development of geomagnetic, ionospheric and thermospheric disturbances. We tested the PM index for 10-year period (1995-2004). The correlation between PM index and upstream solar wind data for these years is very high (the average correlation coefficient R approximately equal to 0.86). The PM index also shows the high correlation with the cross-polar-cap voltage and hemispheric Joule heating (the correlation coefficient between the actual and predicted values of these parameters approximately equal to 0.9), which results in significant increasing the prediction reliability of these parameters. Using the PM index of geomagnetic activity provides a significant increase in the forecasting reliability of geomagnetic disturbances and related events in Geospace environment. The PM index may be also used as an important input parameter in modeling ionospheric, magnetospheric, and thermospheric processes.
During periods of rapidly changing geomagnetic conditions electric fields form within the Earth’s surface and induce currents known as geomagnetically induced currents(GICs), which interact with unprotected electrical systems our society relies on. In this study, we train multi-variate Long-Short Term Memory neural networks to predict magnitude of north-south component of the geomagnetic field (|BN|) at multiple ground magnetometer stations across Alaska provided by the SuperMAG database with a future goal of predicting geomagnetic field disturbances. Each neural network is driven by solar wind and interplanetary magnetic field inputs from the NASA OMNI database spanning from 2000–2015 and is fine tuned for each station to maximize the effectiveness in predicting |BN|. The neural networks are then compared against multivariate linear regression models driven with the same inputs at each station using Heidke skill scores with thresholds at the 50, 75, 85, and 99 percentiles for |BN|. The neural network models show significant increases over the linear regression models for |BN| thresholds. We also calculate the Heidke skill scores for d|BN|/dt by deriving d|BN|/dt from |BN| predictions. However, neural network models do not show clear outperformance compared to the linear regression models. To retain the sign information and thus predict BN instead of |BN|, a secondary so-called polarity model is utilized. The polarity model is run in tandem with the neural networks predicting geomagnetic field in a coupled model approach and results in a high correlation between predicted and observed values for all stations. We find this model a promising starting point for a machine learned geomagnetic field model to be expanded upon through increased output time history and fast turnaround times.
Abstract From low‐Earth orbit, the Earth is an extremely bright γ ‐ray source compared to distant astrophysical objects. The high‐energy γ ‐ray emission, from the Earth's upper atmosphere, is produced by the interactions between cosmic rays (CRs) and air molecules. As CRs are predominantly charged particles, the geomagnetic field acts as a spectrometer, forbidding CRs below a certain energy to arrive and interact with the atmosphere at a given geomagnetic location from a given direction. We use photon data between 0.2 and 20 GeV as observed by the Fermi Large Area Telescope (LAT) to create, for the first time, stratospheric γ ‐ray emission maps of the Earth in the geographical coordinate system, for different viewing directions from LAT altitude. These maps confirm a strong association between measured γ ‐ray fluxes and geomagnetic cutoffs for CRs. We also report the spectrum of the Earth's stratospheric γ ‐ray emission in cardinal directions and use the geomagnetic spectrometer effect to infer the atmosphere's yield function of γ rays per incoming CR proton as a function of CR rigidity at the altitude of the Fermi spacecraft. This work is relevant to the study of near‐Earth radiation exposure for astronauts and spacecraft, modeling the geomagnetic field, and CR‐air interactions.
Fabry-Perot interferometer observations of the thermospheric O I (6300 A) emission have been conducted from an airglow observatory at a dark field site in the southeastern Yukon Territory, Canada, for the period November 1991 to April 1993. The experiment operated in unattended, remote fashion, has resulted in a substantial data set from which mean neutral winds have been determined. Dependent upon geomagnetic activity, the nocturnal location of the site is either equatorward of the auroral oval or within oval boundaries. The data set is rich enough to permit hourly binning of neutral winds based upon the K(sub p) geomagnetic disturbance index as well as the season. For cases of low geomagnetic activity the averaged vector horizontal neutral wind exhibits the characteristics of a midlatitude site displaying antisunward pressure-gradient-driven winds. As the geomagnetic activity rises in the late afternoon and evening winds slowly rotate sunward in an anticlockwise direction, initially remaining near 100 m/s in speed but eventually increasing to 300 m/s for K(sub p) greater than 5. For the higher levels of activity the observed neutral wind flow pattern resembles a higher-latitude polar cap pattern characterized by ion drag forcing of thermospheric neutral gases. In addition, rotational Coriolis forcing on the dusk side enhances the ion drag forcing, resulting in dusk winds which trace out the clockwise dusk cell plasma flow. On the dawn side the neutral winds also rotate in an anticlockwise direction as the strength of geomagnetic disturbances increase. Since the site is located at a transition latitude between the midlatitude and the polar cap the data set provides a sensitive test for general circulation models which attempt to parameterize the contribution of magnetospheric processes. A comparison with the Vector Spherical Harmonic (VSH) model indicates several regions of poor correspondence for December solstice conditions but reasonable agreement for the vernal equinox.
One of the oldest mysteries in geomagnetism is the linkage between solar and geomagnetic activity. The 11-year cycles of both the numbers of sunspots and Earth geomagnetic storms were first noted by Sabine. A few years later, speculation on a causal relationship between flares and storms arose when Carrington reported that a large magnetic storm followed the great September 1859 solar flare. However, it was not until this century that a well-accepted statistical survey on large solar flares and geomagnetic storms was performed, and a significant correlation between flares and geomagnetic storms was noted. Although the two phenomena, one on the Sun and the other on the Earth, were statistically correlated, the exact physical linkage was still an unknown at this time. Various hypotheses were proposed, but it was not until interplanetary spacecraft measurements were available that a high-speed plasma stream rich in helium was associated with an intense solar flare. The velocity of the solar wind increased just prior to and during the helium passage, identifying the solar ejecta for the first time. Space plasma measurements and Skylab's coronagraph images of coronal mass elections (CMES) from the Sun firmly established the plasma link between the Sun and the Earth. One phenomenon associated with magnetic storms is brilliant "blood" red auroras, as shown.
Studies using all-sky imagers have revealed the presence of various ionospheric irregularities in the nighttime midlatitude F region. The most prevalent and well known of these are the medium-scale traveling ionospheric disturbances (MSTIDs) that usually occur when the geomagnetic activity is low and midlatitude spread F plumes that are often observed when the geomagnetic activity is high. The inverse and direct relations between geomagnetic activity and the occurrence rate of MSTIDs and midlatitude plumes, respectively, have been observed by several studies using different instruments; however, most of them focus on MSTIDs only and use only Kp to characterize geomagnetic activity. In order to understand the underlying causes of these two relations and to distinguish between MSTIDs and plumes, it is illuminating to better characterize the occurrence of MSTIDs and plumes using multiple magnetospheric state parameters. Here we statistically compare multiple geomagnetic driver and response parameters (such as Kp, AE, Dst, and solar wind parameters) with the occurrence rates of nighttime MSTIDs and plumes observed using an all ]sky imager at Arecibo Observatory (AO) between 2003 and 2008. We also present seasonal and annual variations of MSTIDs and plumes at AO. The results not only allow us to better distinguish MSTIDs and plumes, but also to shed further light on the generation mechanism and electrodynamics of these two different phenomena occurring at nighttime in the midlatitude F region.
Auroral nighttime infrared emission observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite is used to develop an empirical model of geomagnetic storm enhancements to E-region peak electron densities. The empirical model is called STORM-E and will be incorporated into the 2012 release of the International Reference Ionosphere (IRI). The proxy for characterizing the E-region response to geomagnetic forcing is NO+(v) volume emission rates (VER) derived from the TIMED/SABER 4.3 lm channel limb radiance measurements. The storm-time response of the NO+(v) 4.3 lm VER is sensitive to auroral particle precipitation. A statistical database of storm-time to climatological quiet-time ratios of SABER-observed NO+(v) 4.3 lm VER are fit to widely available geomagnetic indices using the theoretical framework of linear impulse-response theory. The STORM-E model provides a dynamic storm-time correction factor to adjust a known quiescent E-region electron density peak concentration for geomagnetic enhancements due to auroral particle precipitation. Part II of this series describes the explicit development of the empirical storm-time correction factor for E-region peak electron densities, and shows comparisons of E-region electron densities between STORM-E predictions and incoherent scatter radar measurements. In this paper, Part I of the series, the efficacy of using SABER-derived NO+(v) VER as a proxy for the E-region response to solar-geomagnetic disturbances is presented. Furthermore, a detailed description of the algorithms and methodologies used to derive NO+(v) VER from SABER 4.3 lm limb emission measurements is given. Finally, an assessment of key uncertainties in retrieving NO+(v) VER is presented
The International Space Station (ISS) orbits near the F-peak of the ionosphere (approximately 400 km altitude). Generally, satellites orbiting at this altitude would have a floating potential (FP) of approximately -1 V due to the electron temperature (Te). However, the ISS has 8 large negatively grounded 160 V solar array wings (SAW) that collect a significant electron current from the ionosphere. This current drives the ISS FP much more negative during insolation and is highly dependent on the electron density (Ne). Also, due to the size of the ISS, magnetic inductance caused by the geomagnetic field produces a delta potential up to 40 V across the truss, possibly producing positive potentials. During Extravehicular Activity (EVA) the negative FP can lead to an arcing hazard when it exceeds -45.5 V, and the positive FP can produce a DC current high enough to stimulate the astronaut's muscles and also cause a hazard. Data collected from the Floating Potential Monitoring Unit (FPMU) have shown that the probability of either of these hazards occurring during times with quiet to moderately disturbed geomagnetic activity is low enough to no longer be considered a risk. However, a study of the ionosphere Ne during severe geomagnetic storm activity has shown that the Ne can be enhanced by a factor of 6 in the ISS orbit. As a result, the ISS Safety Review Panel (SRP) requires that ionospheric conditions be monitored using the FPMU in conjunction with the ISS Plasma Interaction Model (PIM) to determine if a severe geomagnetic storm could result in a plasma environment that could produce a hazard. A 'Real-Time' plasma hazard assessment process was developed to support ISS Program real-time decision making providing constraint relief information for EVAs planning and operations. This process incorporates 'real time' ionospheric conditions, ISS solar arrays' orientation, ISS flight attitude, and where the EVA will be performed on the ISS. This assessment requires real time data that is presently provided by the FPMU including ISS floating potential, along with ionospheric Ne and Te, in order to determine the present environment. Once the present environment conditions are known to be either above, below, or near the current IRI values, the IRI is used to forecast what the environment could become in the event of a severe geomagnetic storm. If the FPMU should fail, the Space Environments team needs another source of data which is utilized to support a short-term forecast for EVAs. The IRI Real-Time Assimilative Mapping (IRTAM) model is an ionospheric model that uses real time measurements from approximately 70 digisondes to produce foF2 and hmF2 global maps in 15 minute cadence. The Boeing Space Environments team has used the IRI coefficients produced in IRTAM to calculate the Ne along the ISS orbital track. The results of the IRTAM model have been compared to FPMU measurements and show excellent agreement (figure 1). IRTAM has been identified as a potential FPMU back-up system will be used as a backup for the FPMU to support the ISS Program following completion of an FPMU/IRTAM validation campaign.