• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.441-452
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• 2004

Nowcast and forecast based on realtime data are quite essential for space weather monitoring. We have developed the web pages (http://sun.kao.re.kr) of the KAO Space Weather Monitoring system by using ION (IDL on the Net). They display latest solar and geomagnetic data, and present their expected effects on satellite, communications and ground power system. In addition, daily NOAA/SEC prediction reports on the probability of solar X-ray flares, proton events and geomagnetic storms are provided. To predict the arrival times of interplanetary shocks and CMEs, two different types of prediction models are also implemented. A work is in progress to develop web-based database of several solar and geomagnetic activities. These data are automatically downloaded to our data server in every minute, or every day using IDL and FTP programs. In this paper, we will introduce more details on the development of the KAO Space Weather Monitoring system.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.329-342
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• 2004

In this paper, we present preliminary feasibility studies on three types of solar observation payloads for future Korean Science and Technology Satellite (STSAT) programs. The three candidates are (1) an UV imaging telescope, (2) an UV spectrograph, and (3) an X-ray spectrometer. In the case of UV imaging telescope, the most important constraint seems to be the control stability of a satellite in order to obtain a reasonably good spatial resolution. Considering that the current pointing stability estimated from the data of the Far ultraviolet Imaging Spectrograph (FIMS) onboard the Korean STSAT-1, is around 1 arc minutes/sec, we think that it is hard to obtain a spatial resolution sufficient for scientific research by such an UV Imaging Telescope. For solar imaging missions, we realize that an image stabilization system, which is composed of a small guide telescope with limb sensor and a servo controller of secondary mirror, is quite essential for a very good pointing stability of about 0.1 arcsec. An UV spectrograph covering the solar full disk seems to be a good choice in that there is no risk due to poor pointing stability as well as that it can provide us with valuable UV spectral irradiance data valuable for studying their effects on the Earth's atmosphere and satellites. The heritage of the FIMS can be a great advantage of developing the UV spectrograph. Its main disadvantage is that two major missions are in operation or scheduled. Our preliminary investigations show that an X-ray spectrometer for the full disk Sun seems to be the best choice among the three candidates. The reasons are : (1) high temporal and spectral X-ray data are very essential for studying the acceleration process of energetic particles associated with solar flares, (2) we have a good heritage of X-ray detectors including a rocket-borne X-ray detector, (3) in the case of developing countries such as India and Czech, solar X-ray spectrometers were selected as their early stage satellite missions due to their poor pointing stabilities, and (4) there is no planned major mission after currently operating Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) mission. Finally, we present a preliminary design of a solar X-ray spectrometer covering soft X-ray (2 keV) to gamma ray (10 MeV).

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.