Shinichi Watari

Vertical wind observations with two Fabry‐Perot interferometers at Poker Flat, Alaska

Characteristics of vertical winds in the polar thermospheric region were examined using data sets generated with two types of Fabry-Perot interferometers at Poker Flat, Alaska (65.11°N, 147.42°W). The Communications Research Laboratory Fabry-Perot Interferometer (CRLFPI) simultaneously observed the O I 557.7 nm and O I 630.0 nm emissions, whereas the Geophysical Institute Scanning Doppler-Imaging Interferometer (GI-SDI) observed the O I 630.0 nm emission. The height of the O I 557.7 nm and O I 630.0 nm emissions were 100–140 and 200–240 km, respectively. The data were obtained from October 1998 to February 1999, and our findings were as follows: (1) Observations of the O I 630.0 nm emission showed that upward (downward) vertical winds were often present when bright aurora existed equatorward (poleward) of the observatory. This is consistent with previous studies [Crickmore et al., 1991; Innis et al., 1996, 1997]. (2) Comparison of vertical winds estimated from two different wavelengths (557.7 and 630.0 nm) showed that vertical winds were often observed simultaneously at both wavelengths, as reported by Price et al. [1995]. However, the vertical winds observed at different heights sometimes had different features when thin but bright aurora passed over the observatory. A similar observation was reported by Ishii et al. [1999]. (3) Vertical winds were often observed along with divergence and rotation of the horizontal wind field. Some vertical winds not associated with active aurora may be driven by the divergence in the horizontal wind.

The solar drivers of geomagnetic disturbances during solar minimum

Recurrent high speed solar wind from coronal holes still existed around the solar minimum. Their effect on geomagnetic disturbances seems to be weak during this period. High speed solar wind sometimes overlapped with disturbances in association with coronal mass ejections (CMEs). However, a large number of geomagnetic disturbances (Dst ≤ −50 nT) were associated with CMEs even around the solar minimum of the cycle 22. The CME on 6 January 1997 was associated with the soft X-ray active region, in which there was no sunspot group and low flare activity. This region was located in the south of the recurrent coronal hole from the north pole. The observed solar wind showed a strong compression between the CME and the high speed solar wind as a result. The solar source of the CME on 6 January produced another geoeffective CME after approximately 27 days.

Latitudinal variations of solar flux dependence in the topside plasma density: comparison between IRI model and observations

Abstract The solar flux variations of plasma density in the topside ionosphere around 1000 km altitude at lower and higher latitudes are compared using the satellite data and the International Reference Ionosphere (IRI) model. The modeled profiles show rather stronger dependence on the solar activity at higher latitudes than at lower latitudes. These strong latitudinal variations are not seen in the observed data. Comparison with ISS-b data has shown that the IRI model gives systematically greater topside electron density at higher latitude. In an average sense the IRI model overestimates the high latitude electron density at 1100 km altitude by about a factor of 5 than the observations during high solar activity periods.

Estimation of geomagnetically induced currents based on the measurement data of a transformer in a Japanese power network and geoelectric field observations

Geomagnetically induced currents (GICs) have the potential to cause electric power blackouts. Hence, it is important to study the effects of GICs produced by intense geomagnetic storms. The measurements of GICs were conducted at the Memanbetsu substation, Hokkaido, between December 2005 and March 2008. We obtain the complementary cumulative distribution function (CCDF) of the measured GICs and the empirical equation to estimate GICs using the GIC data and geoelectric field observation data. GICs associated with the past intense geomagnetic storms, e.g., the March 13–15 storm and the October 29–30, 2003 storm, are estimated.

Solar Flare Prediction Model with Three Machine-learning Algorithms using Ultraviolet Brightening and Vector Magnetograms

We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 h. Machine learning is used to devise algorithms that can learn from and make decisions on a huge amount of data. We used solar observation data during the period 2010-2015, such as vector magnetogram, ultraviolet (UV) emission, and soft X-ray emission taken by the Solar Dynamics Observatory and the Geostationary Operational Environmental Satellite. We detected active regions from the full-disk magnetogram, from which 60 features were extracted with their time differentials, including magnetic neutral lines, the current helicity, the UV brightening, and the flare history. After standardizing the feature database, we fully shuffled and randomly separated it into two for training and testing. To investigate which algorithm is best for flare prediction, we compared three machine learning algorithms: the support vector machine (SVM), k-nearest neighbors (k-NN), and extremely randomized trees (ERT). The prediction score, the true skill statistic (TSS), was higher than 0.9 with a fully shuffled dataset, which is higher than that for human forecasts. It was found that k-NN has the highest performance among the three algorithms. The ranking of the feature importance showed that the previous flare activity is most effective, followed by the length of magnetic neutral lines, the unsigned magnetic flux, the area of UV brightening, and the time differentials of features over 24 h, all of which are strongly correlated with the flux emergence dynamics in an active region.

Soft X-ray Solar Activities Associated with Interplanetary Magnetic Flux Ropes

We studied the soft X-ray solar events that could be associated with the interplanetary magnetic flux ropes observed by the WIND satellite during 1995 through 1998. The timings of the launches of the magnetic flux ropes from the Sun were estimated using flux rope speeds derived by the fitting of a cylindrical model. In the reasonable time window, soft X-ray solar signatures were found in approximately 70% of the flux ropes. Parameters (e.g., axis direction, strength of magnetic field, radius, and helicity) of the magnetic flux ropes obtained by the model fitting were compared with the characteristics of the corresponding soft X-ray events observed by Yohkoh. According to the result of the comparison, the magnetic flux ropes with strong magnetic fields or high speeds were observed in association with higher soft X-ray solar activities.

Prediction of the electron flux environment in geosynchronous orbit using a neural network technique

In this study, a neural network technique is adopted to predict the electron flux in a geosynchronous orbit using several items of solar wind data obtained by ACE spacecraft and magnetic variations observed on the ground as input parameters. Parameter tuning for the back-propagation learning method is attempted for the feed-forward neural network. As a result, the prediction using the combined data of solar wind and ground magnetic data shows a highest prediction efficiency of 0.61, which is enough to adapt to the actual use of the space environment prediction.

3-D visualization of the IRI model

The International Reference Ionosphere (IRI) model has been in use as a standard model of the ionosphere. We developed a system of 3-D visualization of the electron density calculated by the IRI model. This should help us to understand the global condition of the ionosphere. It will be useful not only for research but also for education. We used two visualization methods: surface and volume rendering. Volume rendering can express more detailed structures than surface rendering.

High-speed streams from coronal holes and coronal mass ejections around the solar minimum of cycle 22

Abstract The soft X-ray telescope on board Yohkoh enables continuous observations of coronal holes and disturbances in the solar corona. Although there were recurrent high-speed streams emanated from the coronal holes around the solar minimum of cycle 22, their effect on geomagnetic disturbances seems to be weak during this period. A half of geomagnetic disturbances ( Dst≧−50 nT ) were associated with coronal mass ejections (CMEs). Several geomagnetic disturbances associated with both high-speed streams and CMEs had large magnitude and long duration.

Extremely Severe Space Weather and Geomagnetically Induced Currents in Regions with Locally Heterogeneous Ground Resistivity

© 2016 Fujita et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Large geomagnetically induced currents (GICs) triggered by extreme space weather events are now regarded as one of the serious natural threats to the modern electrified society. The risk is described in detail in High-Impact, Low-Frequency Event Risk, A Jointly-Commissioned Summary Report of the North American Electric Reliability Corporation and the US Department of Energy’s November 2009 Workshop, June 2010. For example, the March 13–14, 1989 storm caused a large-scale blackout affecting about 6 million people in Quebec, Canada, and resulting in substantial economic losses in Canada and the USA (Bolduc 2002). Therefore, European and North American nations have invested in GIC research such as the “Solar Shield project” in the USA (Pulkkinen et al. 2009, 2015a). In 2015, the Japanese government (Ministry of Economy, Trade and Industry, METI) acknowledged the importance of GIC research in Japan. After reviewing the serious damages caused by the 2011 Tohoku-Oki earthquake, METI recognized the potential risk to the electric power grid posed by extreme space weather. During extreme events, GICs can be concerning even in midand low-latitude countries and have become a global issue. From the scientific and technological aspect, GIC studies are interdisciplinary and include research in Earth’s electromagnetism, magnetospheric and ionospheric physics, interplanetary physics, and solar physics. The GIC is determined by the geomagnetically induced electric field (GIE) and the DC characteristics of the electric power grid. GIEs are controlled by magnetic variations in the ground and the Earth’s resistivity. Ground magnetic variations are composed of magnetic variations caused by magnetospheric and ionospheric disturbances and by currents induced in the ground. The magnetospheric disturbances in turn are driven by coronal mass ejections and other solar disturbances transmitted through interplanetary space. Furthermore, the effective application of a GIC study (e.g., disaster mitigation) requires assessment of how large and how often severe GICs occur in a specific area. Thus, the frequency of severe space weather events also needs to be characterized. At the same time, the heterogeneous distribution of the ground resistivity is important to assess local enhancements of the GIE. Scientists try to understand extreme space weather and predict a realistic GIC, and this special issue of 19 papers publishes recent research achievements about extremely severe space weather and the GIC in the realistic heterogeneous ground resistivity structure. The influence of the heterogeneous resistivity structure is important for the reproduction of realistic GIEs and GICs from magnetic storm data. Ten papers in this collection address this topic. The influence of the heterogeneous resistivity structure to GIEs is investigated using the geoelectric data obtained continuously at Japanese magnetic observatories (Fujii et al. 2015). Love and Swidinsky (2015) also discuss the geoelectric data from the Kakioka Magnetic Observatory based on a twolayer lithosphere model. Goto (2015) calculates the GIE in the coastal zone with a strong spatial gradient in the resistivity and in the seafloor region with a homogeneous resistivity structure. Alekseev et al. (2015) construct the heterogeneous resistivity structure in the Earth, which is important for the evaluation of the GIEs. Pulkkinen et al. (2015b) demonstrate that the GIEs also can be locally enhanced when the source structure is highly heterogeneous. Next, realistic reproduction of GIEs and Open Access