• Atmosphere
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• v.18 no.1
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• pp.1-14
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• 2008

The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.

• Journal of Astronomy and Space Sciences
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• v.41 no.2
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• pp.121-138
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• 2024

Advances in solar-terrestrial physics are generally linked to the development of innovative new sensor technologies, affording us ever better sensitivity, higher resolution, and broader spectral response. Recent advances in low-noise InGaAs sensor technology have enabled the realization of low-light-level scientific imaging within the short-wave infrared (SWIR) region of the electromagnetic spectrum. This paper describes a new and highly sensitive ultra-wide angle imager that offers an expansion of auroral and airglow imaging capabilities into the SWIR spectral range of 900-1,700 nm. The imager has already proven successful in large-area remote sensing of mesospheric temperatures and in providing intensity maps showing the propagation and dissipation of atmospheric gravity waves and ripples. The addition of an automated filter wheel expands the range of applications of an already versatile SWIR detector. Several potential applications are proposed herein, with an emphasis on auroral science. The combined data from this type of instrument and other existing instrumentation holds a strong potential to further enhance our understanding of the geospace environment.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.237-240
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• 2015

Classical novae (CNe) are interacting binary systems whose outbursts are powered by a thermonuclear runaway in accreted material onto the surface of a white dwarf (WD). The secondary star in such systems fills its Roche lobe and material is transferred onto the WD primary star via an accretion disk. Recurrent novae (RNe) show many similarities to CNe, but have had more than one recorded outburst. RNe play an important role as one of the suspected progenitor systems of Type Ia supernovae, which are used as primary distance indicators in cosmology. Thus, it is important to investigate the nature of their central binary systems to determine the relation between the parameters of the central system and the outburst type, and finally ascertain the population of novae that might be available to give rise to the progenitors of Type Ia SNe. A low outburst amplitude is adopted as a criterion that may help distinguish RNe from CNe and was therefore used to select targets for observations from ground-based observatories including the Liverpool Telescope and the Southern African Large Telescope as well as the full-sky space-based archive of the Solar Mass Ejection Imager (SMEI). We found that at least four objects currently classified as CNe are possibly RNe candidates based on their quiescent spectra. We also searched the SMEI archive for additional outbursts of bright CNe that might otherwise have been missed but did not find a conclusive example.

• Journal of Astronomy and Space Sciences
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• v.35 no.3
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• pp.185-193
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• 2018

Jang Bogo Station (JBS), the second Korean Antarctic research station, was established in Terra Nova Bay, Antarctica ($74.62^{\circ}S$ $164.22^{\circ}E$) in February 2014 in order to expand the Korea Polar Research Institute (KOPRI) research capabilities. One of the main research areas at JBS is space environmental research. The goal of the research is to better understand the general characteristics of the polar region ionosphere and thermosphere and their responses to solar wind and the magnetosphere. Ground-based observations at JBS for upper atmospheric wind and temperature measurements using the Fabry-Perot Interferometer (FPI) began in March 2014. Ionospheric radar (VIPIR) measurements have been collected since 2015 to monitor the state of the polar ionosphere for electron density height profiles, horizontal density gradients, and ion drifts. To investigate the magnetosphere and geomagnetic field variations, a search-coil magnetometer and vector magnetometer were installed in 2017 and 2018, respectively. Since JBS is positioned in an ideal location for auroral observations, we installed an auroral all-sky imager with a color sensor in January 2018 to study substorms as well as auroras. In addition to these observations, we are also operating a proton auroral imager, airglow imager, global positioning system total electron content (GPS TEC)/scintillation monitor, and neutron monitor in collaboration with other institutes. In this article, we briefly introduce the observational activities performed at JBS and the preliminary results of these observations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.415-426
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• 2015

Solar radiation under a clear sky is a important factor in the process by which meteorological satellite images are converted into solar radiation maps, and the quality of estimations depends on the accuracy of clear sky models. Therefore, it is important to select models appropriate to the purpose of the study and the study area. In this instance, complex models were applied using Linke turbidity, including ESRA, Dumortier, and MODTRAN, in addition to simple models such as Bourges and PdBV, which consider only the solar elevation angles. The presence of cloud was identified using the Communication, Ocean, and Meteorological Satellite and the Meteorological imager (COMS MI), and reference data were then selected. In order to calculate the accuracy of the clear sky models, the concepts of RMSE and MBE were applied. The results show that Bourges and PdBV produced low RMSE values, while PdBV had relatively steady RMSE values. Also, simple models tend to underestimate global solar irradiation during spring and early summer. Conversely, in the winter season, complex methods often overestimate irradiation. In future work, the cause of overestimation and other factors will be analyzed and the clear sky models will be adjusted in order to make them suitable for the Korean Peninsula.

• Journal of Astronomy and Space Sciences
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• v.33 no.1
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• pp.13-19
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• 2016

In recent years, there has been renewed activity in the study of local plasma density enhancements in the low latitude F region ionosphere (low latitude plasma blobs). Satellite, all-sky airglow imager, and radar measurements have identified the characteristics of these blobs, and their coupling to Equatorial Plasma Bubbles (EPBs). New information related to blobs has also been obtained from the Communication/Navigation Outage Forecasting System (C/NOFS) satellite. In this paper, we briefly review experimental, theoretical and modeling studies related to low latitude plasma blobs.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.253-262
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• 2016

Here, we estimated daily Photosynthetically Available Radiation (PAR) from Geostationary Ocean Colour Imager (GOCI) and compared it with daily PAR derived from polar-orbiting MODIS images. GOCI-based PAR was also validated with in-situ measurements from ocean research station, Socheongcho. GOCI PAR showed similar patterns with in-situ measurements for both the clear-sky and cloudy day, whereas MODIS PAR showed irregular patterns at cloudy conditions in some areas where PAR could not be derived due to the clouds of sunglint. GOCI PAR had shown a constant difference with the in-situ measurements, which was corrected using the in-situ measurements obtained on the days of clear-sky conditions at Socheongcho station. After the corrections, GOCI PAR showed a good agreement excepting on the days with so thick cloud that the sensor was optically saturated. This study revealed that GOCI can estimate effectively the daily PAR with its advantages of acquiring data more frequently, eight times a day at an hourly interval in daytime, than other polar orbit ocean colour satellites, which can reduce the uncertainties induced by the existence and movement of the cloud and insufficient images to map the daily PAR at the seas around Korean peninsula.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1101-1117
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• 2018

The clear sky radiance (CSR) is one of the baseline products of the Himawari-8 which was launched on October, 2014. The CSR contributes to numerical weather prediction (NWP) accuracy through the data assimilation; especially water vapor channel CSR has good impact on the forecast in high level atmosphere. The focus of this study is the quality analysis of the CSR of the Himawari-8 geostationary satellite. We used the operational CSR (or clear sky brightness temperature) products in JMA (Japan Meteorological Agency) as observation data; for a background field, we employed the CSR simulated using the Radiative Transfer for TOVS (RTTOV) with the atmospheric state from the global model of KMA (Korea Meteorological Administration). We investigated data characteristics and analyzed observation minus background statistics of each channel with respect to regional and seasonal variability. Overall results for the analysis period showed that the water vapor channels (6.2, 6.9, and $7.3{\mu}m$) had a positive mean bias where as the window channels(10.4, 11.2, and $12.4{\mu}m$) had a negative mean bias. The magnitude of biases and Uncertainty result varied with the regional and the seasonal conditions, thus these should be taken into account when using CSR data. This study is helpful for the pre-processing of Himawari-8/Advanced Himawari Imager (AHI) CSR data assimilation. Furthermore, this study also can contribute to preparing for the utilization of products from the Geo-Kompsat-2A (GK-2A), which will be launched in 2018 by the National Meteorological Satellite Center (NMSC) of KMA.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.599-605
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• 2017

Accurate cloud discrimination in satellite images strongly affects accuracy of remotely sensed parameter produced using it. Especially, cloud contaminated pixel over ocean is one of the major error factors such as Sea Surface Temperature (SST), ocean color, and chlorophyll-a retrievals,so accurate cloud detection is essential process and it can lead to understand ocean circulation. However, static threshold method using real-time algorithm such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Himawari Imager (AHI) can't fully explained reflectance variability over ocean as a function of relative positions between the sun - sea surface - satellite. In this paper, we assembled a reflectance spectral library as a function of Solar Zenith Angle (SZA) and Viewing Zenith Angle (VZA) from ocean surface reflectance with clear sky condition of Advanced Himawari Imager (AHI) identified by NOAA's cloud products and spectral library is used for applying the Dynamic Time Warping (DTW) to detect cloud pixels. We compared qualitatively between AHI cloud property and our results and it showed that AHI cloud property had general tendency toward overestimation and wrongly detected clear as unknown at high SZA. We validated by visual inspection with coincident imagery and it is generally appropriate.