• Journal of the Korean earth science society
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• v.18 no.6
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• pp.565-578
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• 1997

Clouds are usually formed by adiabatic cooling through ascending currents, radiation cooling or a mixture of warm air and cold one. Ascending currents are caused by covection currents, or they are accompanied with fronts. Thus clouds are formed through various kinds of causes and procedures. So they are various in height and shape. Form of clouds was classified on the basis of the thecriteria that L. Howard proposed in 1803. He distinguished three simple, fundamental classes-Cirrus, Cumulus, Stratus-from which the others were derived by trasition or association. And they are subdivided into 10 genera according to their height and shape. Most of the clouds are subdivided into the detailed kinds to the characteristics such as appearance or intensity of convection current. Sometimes completly different shape of cloud can be developed out of the 'mother-cloud'. In korea, the stratocumulus, altostratus and cirrus clouds frequently appear. Generally we are likely to have rain or snow from the stratus cloud forms(As, St, Sc) and rain shower or hail from the cumulus forms(Ac, Cu, Cb).

• Journal of the Korean Geographical Society
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• v.38 no.2
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• pp.173-183
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• 2003

This study aims to understand the patterns of spatial distribution of snowfall by Siberian High in the Honam region in Korea. In the Honam region, Siberian High induces snowfall dominantly. There is a huge amount of snowfall in the westward of the Noryung mountain ranges to the Wert coast in the Honam region affected by northwesterly wind directly from the Siberian High. The westward of the Noryung mountain ranges such as a heavy snowfall region has a various pattern of distribution of snowfall due to topography. The coast region has a large amount of snowfall by sea effect. And, snowfall amount is decreased from the coast to the inland plain. However, in front of mountain, snowfall is increase by reason of a forced ascending air to the mountain. In general the region where frequently appear a cumuliform cloud has a large amount of snowfall. A cumuliform cloud is frequent in the mountainous region in inland, the coast, and the inland plain in order Snowfall is intense in the coast and the mountainous region, and weak in the inland plain. In the mountainous region, a cumuliform cloud induced tv a forced ascending air by reason of topography generates snowfall mostly. This fact is the main difference with snowfall in the mountainous region and the coast region. In the result, in the Honam region, snowfall distribution and snowfall pattern are various, according to geographical climate factor such as sea and topography. The heavy snowfall region in the Honam region is divided into the coast region affected by sea effect and the mountainous region affected by topography effect.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.71-87
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• 2007

In this study, 14 heavy snow events in Yeongdong area which are local phenomena are analyzed using MODIS cloud products provided from NASA/GSFC. The clouds of Yeongdong area at observed at specific time by MODIS are classified into A, B, C Types, based on the characteristic of cloud properties: cloud top temperature, cloud optical thickness, Effective Particle Radius, and Cloud Particle Phase. The analysis of relations between cloud properties and precipitation amount for each cloud type show that there are statistically significant correlations between Cloud Optical Thickness and precipitation amount for both A and B type and also significant correlation is found between Cloud Top Temperature and precipitation amount for A type. However, for C type there is not any significant correlations between cloud properties and precipitation amount. A-type clouds are mainly lower stratus clouds with small-size droplet, which may be formed under the low level cold advection derived synoptically in the East sea. B-type clouds are developed cumuliform clouds, which are closely related to the low pressure center developing over the East sea. On the other hand, C-type clouds are likely multi-layer clouds, which make satellite observation difficult due to covering of high clouds over low level clouds directly related with Yeongdong heavy snow. It is, therefore, concluded that MODIS cloud products may be useful except the multi-layer clouds for understanding the mechanism of heavy snow and estimating the precipitation amount from satellite data in the case of Yeongdong heavy snow.

• The KIPS Transactions:PartA
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• v.16A no.5
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• pp.307-318
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• 2009

Modeling and rendering of atmospheric phenomena such as clouds is one of most difficult research themes in the field of computer graphics, mainly due to its complexity, huge volume, ubiquitousness, etc. In this paper, we represent a system for real-time modeling and rendering of clouds, mainly aiming at the computer games and flight simulation applications. Our implementation generates various kinds of clouds including cirrus, stratus, and cumulus, through intuitive real-timeuser interactions. Then, additional details are automatically attached to them, using our own methods based on meta-balls or hierarchical spherical particles. After processing multiple scattering and anisotropic scattering, resulting particles are rendered into billboards, to finally achieve real-time processing.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1631-1645
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• 2021

This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.