Distributing space weather monitoring instruments and educational materials worldwide for IHY 2007: The AWESOME and SID project

The International Heliophysical Year (IHY) aims to advance our understanding of the fundamental processes that govern the Sun, Earth, and heliosphere. The IHY Education and Outreach Program is dedicated to inspiring the next generation of space and Earth scientists as well as spreading the knowledge, beauty, and relevance of our solar system to the people of the world. In our Space Weather Monitor project we deploy a global network of sensors to high schools and universities to provide quantitative diagnostics of solar-induced ionospheric disturbances, thunderstorm intensity, and magnetospheric activity. We bring real scientific instruments and data in a cost-effective way to students throughout the world. Instruments meet the objectives of being sensitive enough to produce research-quality data, yet inexpensive enough for placement in high schools and universities. The instruments and data have been shown to be appropriate to, and usable by, high school age and early university students. Data contributed to the Stanford data center is openly shared and partnerships between groups in different nations develop naturally. Students and teachers have direct access to scientific expertise.     

First results of operational ionospheric dynamics prediction for the Brazilian Space Weather program

It is shown the development and preliminary results of operational ionosphere dynamics prediction system for the Brazilian Space Weather program. The system is based on the Sheffield University Plasmasphere–Ionosphere Model (SUPIM), a physics-based model computer code describing the distribution of ionization within the Earth mid to equatorial latitude ionosphere and plasmasphere, during geomagnetically quiet periods. The model outputs are given in a 2-dimensional plane aligned with Earth magnetic field lines, with fixed magnetic longitude coordinate. The code was adapted to provide the output in geographical coordinates. It was made referring to the Earth’s magnetic field as an eccentric dipole, using the approximation based on International Geomagnetic Reference Field (IGRF-11). During the system operation, several simulation runs are performed at different longitudes. The original code would not be able to run all simulations serially in reasonable time. So, a parallel version for the code was developed for enhancing the performance. After preliminary tests, it was frequently observed code instability, when negative ion temperatures or concentrations prevented the code from continuing its processing. After a detailed analysis, it was verified that most of these problems occurred due to concentration estimation of simulation points located at high altitudes, typically over 4000 km of altitude. In order to force convergence, an artificial exponential decay for ion–neutral collisional frequency was used above mentioned altitudes. This approach shown no significant difference from original code output, but improved substantially the code stability. In order to make operational system even more stable, the initial altitude and initial ion concentration values used on exponential decay equation are changed when convergence is not achieved, within pre-defined values. When all code runs end, the longitude of every point is then compared with its original reference station longitude, and differences are compensated by changing the simulation point time slot, in a temporal adjustment optimization. Then, an approximate neighbor searching technique was developed to obtain the ion concentration values in a regularly spaced grid, using inverse distance weighting (IDW) interpolation. A 3D grid containing ion and electron concentrations is generated for every hour of simulated day. Its spatial resolution is 1° of latitude per 1° of longitude per 10 km of altitude. The vertical total electron content (VTEC) is calculated from the grid, and plotted in a geographic map. An important feature that was implemented in the system is the capacity of combining observational data and simulation outputs to obtain more appropriate initial conditions to the ionosphere prediction. Newtonian relaxation method was used for this data assimilation process, where ionosonde data from four different locations in South America was used to improve the system accuracy. The whole process runs every day and predicts the VTEC values for South America region with almost 24 h ahead.     

Solar magnetic feature detection and tracking for space weather monitoring

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking (SMART) algorithm relies on consecutive image differencing to remove both quiet-Sun and transient magnetic features, and region-growing techniques to group flux concentrations into classifiable features. We determine magnetic properties such as region size, total flux, flux imbalance, flux emergence rate, Schrijver’s R-value, R^∗ (a modified version of R), and Falconer’s measurement of non-potentiality. A persistence algorithm is used to associate developed active regions with emerging flux regions in previous measurements, and to track regions beyond the limb through multiple solar rotations. We find that the total number and area of magnetic regions on disk vary with the sunspot cycle. While sunspot numbers are a proxy to the solar magnetic field, SMART offers a direct diagnostic of the surface magnetic field and its variation over timescale of hours to years. SMART will form the basis of the active region extraction and tracking algorithm for the Heliophysics Integrated Observatory (HELIO).     

On the detection of anomalous seismo-ionospheric behavior in the presence of space weather stimuli for large earthquakes

Anomalous behavior of ionospheric total electron content (TEC) prior to earthquake has been observed in many studies. Evidence of such seismo-ionospheric coupling effects suggests that it is plausible to rely on TEC signatures for early earthquake warning. However, the detection of pre-earthquake TEC anomalies (PETA) has not been adopted in practice due to two pertinent issues. Firstly, the effects of space weather activity can affect TEC levels and cause anomalous behavior in the TEC. Usually arbitrary thresholds are set for space weather indices to eliminate TEC anomaly due to space weather effects. Secondly, the choice regarding moving time-window length used to characterise background variation of TEC within the statistical envelope approach has an effect on detection of PETA. While the rule-of-thumb in selecting the moving window length is to have a time window capable of capturing background variability and short-term fluctuations, the length of the time window used in the literature varies with little justification. In this study, a critical examination is conducted on the statistical envelope approach and in particular, to eliminate the effect of space weather activity without the use of arbitrary space indices to detect PETA. A two-part PETA identification procedure is proposed, consisting of wavelet analyses isolating non-earthquake TEC contributions, followed by the statistical envelope method using a moving window length standardized based on observed periodicities and statistical implications is suggested. The approach is tested on a database of 30 large earthquakes (M?≥?7.0). The proposed procedure shows that PETA can be detected prior to earthquakes at higher confidence levels without the need to separately check for space weather activity. More importantly, the procedure was able to detect PETA for studies where it was previously reported that PETA could not be detected or detected convincingly.     

On the application of Exploratory Data Analysis for characterization of space weather data sets

This paper presents an overview of the mathematical foundations for techniques in Exploratory Data Analysis (EDA) for the purpose of investigating the relationships among the numerous variables in large sets of multivariate space weather data. Specifically, we cover techniques in Principal Components Analysis (PCA) and Common Factor Analysis (CFA). These techniques are illustrated using space weather activity indices collected during the year 2002 and the corresponding noon-time hmF2 data from the International Reference Ionosphere (IRI). A CFA is used to categorize the activity indices, and a PCA is used to derive two macro-indices of activity to ascertain the strength of solar and geomagnetic activity. These macro-indices are then used to compare and contrast IRI’s noon-time hmF2 values at six different geographic stations. It was found that the correlation between hmF2 and the macro-indices more accurately represented the variation of this correlation with latitude found in previous studies than if we used an isolated conventional index, such as SSN and AE. We also found that the daily maximum value of the Polar Cap Index was dependent on both solar and geomagnetic activity, but the closely-related cross-Polar Cap Potential was solely associated with elevated levels of geomagnetic activity, which is a unique result compared to previous studies. We argue that the discrepancy can be explained by the difference in experiment designs between the two studies. This paper demonstrates the usefulness of EDA in space weather studies of large multivariate data sets.     

Coronal mass ejection detection using wavelets,curvelets and ridgelets: Applications for space weather monitoring

Coronal mass ejections (CMEs) are large-scale eruptions of plasma and magnetic field that can produce adverse space weather at Earth and other locations in the Heliosphere. Due to the intrinsic multiscale nature of features in coronagraph images, wavelet and multiscale image processing techniques are well suited to enhancing the visibility of CMEs and suppressing noise. However, wavelets are better suited to identifying point-like features, such as noise or background stars, than to enhancing the visibility of the curved form of a typical CME front. Higher order multiscale techniques, such as ridgelets and curvelets, were therefore explored to characterise the morphology (width, curvature) and kinematics (position, velocity, acceleration) of CMEs. Curvelets in particular were found to be well suited to characterising CME properties in a self-consistent manner. Curvelets are thus likely to be of benefit to autonomous monitoring of CME properties for space weather applications.     

Progress in space weather predictions and applications

The methods of today’s predictions of space weather and effects are so much more advanced and yesterday’s statistical methods are now replaced by integrated knowledge-based neuro-computing models and MHD methods. Within the ESA Space Weather Programme Study a real-time forecast service has been developed for space weather and effects. This prototype is now being implemented for specific users. Today’s applications are not only so many more but also so much more advanced and user-oriented. A scientist needs real-time predictions of a global index as input for an MHD model calculating the radiation dose for EVAs. A power company system operator needs a prediction of the local value of a geomagnetically induced current. A science tourist needs to know whether or not aurora will occur. Soon we might even be able to predict the tropospheric climate changes and weather caused by the space weather.     

Different space weather effects in anomalies of the high and low orbital satellites

Preliminary results of the EU INTAS Project 00810, which aims to improve the methods of safeguarding satellites in the Earth’s magnetosphere from the negative effects of the space environment, are presented. Anomaly data from the “Kosmos” series satellites in the period 1971–1999 are combined in one database, together with similar information on other spacecraft. This database contains, beyond the anomaly information, various characteristics of the space weather: geomagnetic activity indices (Ap, AE and Dst), fluxes and fluences of electrons and protons at different energies, high energy cosmic ray variations and other solar, interplanetary and solar wind data. A comparative analysis of the distribution of each of these parameters relative to satellite anomalies was carried out for the total number of anomalies (about 6000 events), and separately for high (5000 events) and low (about 800 events) altitude orbit satellites. No relation was found between low and high altitude satellite anomalies. Daily numbers of satellite anomalies, averaged by a superposed epoch method around sudden storm commencements and proton event onsets for high (>1500 km) and low (<1500 km) altitude orbits revealed a big difference in a behavior. Satellites were divided on several groups according to the orbital characteristics (altitude and inclination). The relation of satellite anomalies to the environmental parameters was found to be different for various orbits that should be taken into account under developing of the anomaly frequency models.     

A 12 year comparison of MIDAS and IRI 2007 ionospheric Total Electron Content

Data assimilation in conventional meteorological applications uses measurements in conjunction with a physical model. In the case of the ionised region of the upper atmosphere, the ionosphere, assimilation techniques are much less mature. The empirical model known as the International Reference Ionosphere (IRI) could be used to augment data-sparse regions in an ionospheric now-cast and forecast system. In doing so, it is important that it does not introduce systematic biases to the result. Here, the IRI model is compared to ionospheric observations from the Global Positioning System satellites over Europe and North America. Global Positioning System data are processed into hour-to-hour monthly averages of vertical Total Electron Content using a tomographic technique. A period of twelve years, from January 1998 to December 2009, is analysed in order to capture variations over the whole solar cycle. The study shows that the IRI model underestimates Total Electron Content in the daytime at solar maximum by up to 37% compared to the monthly average of GPS tomographic images, with the greatest differences occurring at the equinox. IRI shows good agreement at other times. Errors in TEC are likely due to peak height and density inaccuracies. IRI is therefore a suitable model for specification of monthly averages of Total Electron Content and can be used to initialise a data assimilation process at times away from solar maximum. It may be necessary to correct for systematic deviations from IRI at solar maximum, and to incorporate error estimation into a data assimilation scheme.     

Influence of ionospheric perturbations in GPS time and frequency transfer

The stability of GPS time and frequency transfer is limited by the fact that GPS signals travel through the ionosphere. In high precision geodetic time transfer (i.e. based on precise modeling of code and carrier phase GPS data), the so-called ionosphere-free combination of the code and carrier phase measurements made on the two frequencies is used to remove the first-order ionospheric effect. In this paper, we investigate the impact of residual second- and third-order ionospheric effects on geodetic time transfer solutions i.e. remote atomic clock comparisons based on GPS measurements, using the ATOMIUM software developed at the Royal Observatory of Belgium (ROB). The impact of third-order ionospheric effects was shown to be negligible, while for second-order effects, the tests performed on different time links and at different epochs show a small impact of the order of some picoseconds, on a quiet day, and up to more than 10 picoseconds in case of high ionospheric activity. The geomagnetic storm of the 30th October 2003 is used to illustrate how space weather products are relevant to understand perturbations in geodetic time and frequency transfer.     

High-resolution, coupled thermosphere–ionosphere models for space weather applications

Current first-principles global models of the coupled thermosphere–ionosphere (T–I) system use grids that are too coarse to simulate the mesoscale and small-scale structures that occur in this complex system. These small-scale and mesoscale structures have a great effect on global-scale neutral and plasma distributions and have important consequences for daily space weather. In this paper, we present a new first-principles, high-resolution, T–I nested grid (TING) polar cap model that incorporates multiple nesting levels and two-way interaction. The TING model simulation of the electron densities and temperatures demonstrates the importance of high spatial resolution. It is found that both the mid-latitude electron density trough and its associated dawn electron temperature peak are more pronounced and structured in the nested grid than in the coarse grid. Using the TING model to simulate ionospheric F₂ region electron density variations with geomagnetic activity and universal time (UT) is also discussed.     

Combining frequency and time domain models to forecast space weather

Space weather series incorporate several distinct components, cycles at multiple frequencies, irregular trends, and nonlinear variability. The cycles are stochastic, i.e., the amplitude varies over time. Similarly, the trend is stochastic: the slope and direction of trending change repeatedly. This study sets out a combined model using both frequency and time domain methods, in two stages. In the first stage, a frequency domain algorithm is estimated and forecasted. In the second stage, the forecast is used as an input in a neural network. The combined model also includes a term enabling the model to react inversely to large deviations between the actual values and forecast. The models are evaluated using two data sets, the hemispheric power data obtained from the Polar Orbiting Environment satellites, and the Aa geomagnetic index. All the series are at a daily resolution. Forecasting experiments are run over horizons of 1–7 days. The models are estimated using a moving window or adaptive approach. The combined model consistently achieves the most accurate results. Among single equation methods, the frequency domain model is more accurate for the geomagnetic index because it is able to capture the underlying cycles more effectively. In the hemispheric power series, the cycles are less pronounced, so that time domain methods are more accurate, except at very short horizons. Nevertheless, in both data sets, the combined model works well because the frequency domain algorithm captures cyclical behavior, while the neural net is better able to capture short-term dependence and trending.     

On one approach to space weather studies from ground based observations during 1953–2001

The cross correlation of daily values of coronal hole areas at the eastern limb of the Sun constructed from the ground based measurements of the green coronal line and daily mean cosmic ray intensities over long time periods shows asymmetry: at the maximum of their 27 day cycle, cosmic ray intensities are better correlated with coronal hole areas 66 days before than with the current value. This indicates the potential for using coronal emission data as one of the parameters for eventual prediction of the level of cosmic ray flux at neutron monitor energies.     

A statistical study of solar radio Type III bursts and space weather implication

Solar radio bursts (SRBs) are the signatures of various phenomenon that happen in the solar corona and interplanetary medium (IPM). In this article, we have studied occurrence of Type III bursts and their association with the Sunspot number. This study confirms that occurrence of Type III bursts correlate well with Sunspot number. Further, using the data obtained using e-CALLISTO network, we have investigated drift rates of isolated Type III bursts and duration of the group of Type III bursts. Since Type II, Type III and Type IV bursts are signatures of solar flares and/or CMEs, we can use the radio observations to predict space weather hazards. In this article, we have discussed two events that have caused near Earth radio blackouts. Since e-CALLISTO comprises more than 152 stations at different longitudes, we can use it to monitor the radio emissions from the solar corona 24 h a day. Such observations play a crucial role in monitoring and predicting space weather hazards within few minutes to hours of time.     

Towards a scientific understanding of the risk from extreme space weather

Like all natural hazards, space weather exhibits occasional extreme events over timescales of decades to centuries. Historical events provoked much interest, and sometimes alarm, because bright aurora becomes visible at mid-latitudes. However, they had little economic impact because the major technologies of those eras were not sensitive to space weather. This is no longer true. The widespread adoption of advanced technological infrastructures over the past 40 years has created significant sensitivity. So these events now have the potential to disrupt those infrastructures – and thus have profound economic and societal impact. However, like all extreme hazards, such events are rare, so we have limited data on which to build our understanding of the events. This limitation is uniquely serious for space weather since it is a global phenomenon. Many other natural hazards (e.g. flash floods) are highly localised, so statistically significant datasets can be assembled by combining data from independent instances of the hazard recorded over a few decades. Such datasets are the foundation on which reliable risk assessment methodologies are built. But we have a single instance of space weather so we would have to make observations for many centuries in order to build a statistically significant dataset. We show that it is not practicable to assess the risk from extreme events using simple statistical methods. Instead we must exploit our knowledge of solar-terrestrial physics to find other ways to assess these risks. We discuss three alternative approaches: (a) use of proxy data, (b) studies of other solar systems, and (c) use of physics-based modelling. We note that the proxy data approach is already well-established as a technique for assessing the long-term risk from radiation storms, but does not yet provide any means to assess the risk from severe geomagnetic storms. This latter risk is more suited to the other approaches, but significant research is needed to make progress. We need to develop and expand techniques to monitoring key space weather features in other solar systems (stellar flares, radio emissions from planetary aurorae). And to make progress in modelling severe space weather, we need to focus on the physics that controls severe geomagnetic storms, e.g. how can dayside and tail reconnection be modulated to expand the region of open flux to envelop mid-latitudes?     

Refinement of global ionospheric coefficients for GNSS applications: Methodology and results

We developed the methodology for the optimal estimation of global ionospheric coefficients of the current Global Navigation Satellite Systems (GNSSs), including the eight- and ten-parameter Klobuchar-like as well as NeQuick models. The ionospheric coefficients of those correction models are calculated from two sets of globally distributed tracking stations of the International GNSS Services (IGS). Performance of the re-estimated Klobuchar-like and NeQuick coefficients are validated during 2002–2014 over the continental and oceanic areas, respectively. Over the continental areas, GPS TECs derived from 40 ground GPS receivers are selected as reference. The eight-, ten-parameter Klobuchar-like and NeQuick models can mitigate the ionospheric delay by 65.8, 67.3 and 75.0%, respectively. Over the global oceans, the independent TECs derived from Jason-1&2 altimeters are used as reference. The re-estimated ionospheric correction models can mitigate 56.1–66.7% of the delay errors. Compared to the original GPS Ionospheric Correction Algorithm (ICA), performance of those eight-, ten-parameter Klobuchar-like and NeQuick models has improved 3.4, 5.9 and 13.4% during the whole test period, respectively. The methodology developed here takes the advantage of high-quality ionospheric TECs derived from the global network of GNSS receivers. The re-estimated ionospheric coefficients can be used as precise ionospheric products to monitor and assess GNSS broadcast ionospheric parameters and to improve the performance of various single-frequency GNSS applications.     

Space weather and commercial airlines

Space weather phenomena can effect many areas of commercial airline operations including avionics, communications and GPS navigation systems. Of particular importance at present is the recently introduced EU legislation requiring the monitoring of aircrew radiation exposure, including any variations at aircraft altitudes due to solar activity. With the introduction of new ultra-long-haul “over-the-pole” routes, “more-electric” aircraft in the future, and the increasing use of satellites in the operation, the need for a better understanding of the space weather impacts on future airline operations becomes all the more compelling. This paper will present the various space weather effects, some provisional results of an ongoing 3-year study to monitor cosmic radiation in aircraft, and conclude by summarising some of the identified key operational issues, which must be addressed, with the help of the science community, if the airlines want to benefit from the availability of space weather services.     

Application of Autoscala to ionograms recorded by the VIPIR ionosonde

In November 2008, the ionosonde station at Boulder, Colorado, USA (40.0°N; 105.3°W) became the host of a new ionosonde (VIPIR, Vertical Incidence Pulsed Ionospheric Radar) developed and built by Scion Associates.     

Symmetry and asymmetry of ionospheric weather at magnetic conjugate points for two midlatitude observatories

Variations of the ionospheric weather W-index for two midlatitude observatories, namely, Grahamstown and Hermanus, and their conjugate counterpart locations in Africa are studied for a period from October 2010 to December 2011. The observatories are located in the longitude sector, which has consistent magnetic equator and geographic equator so that geomagnetic latitudes of the line of force are very close to the corresponding geographic latitudes providing opportunity to ignore the impact of the difference of the gravitational field and the geomagnetic field at the conjugate points on the ionosphere structure and dynamics. The ionosondes of Grahamstown and Hermanus provide data of the critical frequency (foF2), and Global Ionospheric Maps (GIM) provide the total electron content (TECgps) along the magnetic field line up to the conjugate point in the opposite hemisphere. The global model of the ionosphere, International Reference Ionosphere, extended to the plasmasphere altitude of 20,200 km (IRI-Plas) is used to deliver the F2 layer peak parameters from TECgps at the magnetic conjugate area. The evidence is obtained that the electron gas heated by day and cooled by night at the summer hemisphere as compared with the opposite features in the conjugate winter hemisphere testifies on a reversal of plasma fluxes along the magnetic field line by the solar terminator. The ionospheric weather W-index is derived from NmF2 (related with foF2) and TECgps data. It is found that symmetry of W-index behavior in the magnetic conjugate hemispheres is dominant for the equinoxes when plasma movement along the magnetic line of force is imposed on symmetrical background electron density and electron content. Asymmetry of the ionospheric storm effects is observed for solstices when the plasma diffuse down more slowly into the colder winter hemisphere than into the warmer summer hemisphere inducing either plasma increase (positive phase) or decrease (negative phase of W-index) in the ionospheric and plasmaspheric plasma density.     

The possibilities of polar meteorology,environmental remote sensing,communications and space weather applications from Artificial Lagrange Orbit

The ability to observe meteorological events in the polar regions of the Earth from satellite celebrated an anniversary, with the launch of TIROS-I in a pseudo-polar orbit on 1 April 1960. Yet, after 50 years, polar orbiting satellites are still the best view of the polar regions of the Earth. The luxuries of geostationary satellite orbit including rapid scan operations, feature tracking, and atmospheric motion vectors (or cloud drift winds), are enjoyed only by the middle and tropical latitudes or perhaps only cover the deep polar regions in the case of satellite derived winds from polar orbit. The prospect of a solar sailing satellite system in an Artificial Lagrange Orbit (ALO, also known as “pole sitters”) offers the opportunity for polar environmental remote sensing, communications, forecasting and space weather monitoring. While there are other orbital possibilities to achieve this goal, an ALO satellite system offers one of the best analogs to the geostationary satellite system for routine polar latitude observations.