• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.67-69
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• 2021

Weather radar images can be used in a variety of ways because of their high visibility in terms of visuals. In other words it has the advantage of being able to grasp the flow of weather phenomena using not only the raw data of the weather radar, but also the change characteristics between consecutive images. In particular image processing techniques are gradually expanding in the field of meteorological research, and in the case of image data having high resolution such as weather radar images it is expected to produce useful information through a new approach called image processing techniques. In this study the weather phenomena flow was calculated as a vector from the change of the weather radar image according to time interval with the optical flow method, one of the image processing techniques. The characteristics of the weather phenomena to be analyzed were derived through vector analysis resolution suitable for the scale of weather, vector interpolation in regions where no radar echo exists, and the removal of relative flow vectors to distinguish the flow of specific weather and the entire atmosphere. Through this study, it is expected that not only the use of raw data of weather radar, but also the widening of the application area of weather radar, such as the use of unique characteristics of image data, and the active use of image processing techniques in the field of meteorology in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.360-365
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• 2014

There are many types of advanced devices for weather prediction process such as weather radar, satellite, radiosonde, and other weather observation devices. Among them, the weather radar is an essential device for weather forecasting because the radar has many advantages like wide observation area, high spatial and time resolution, and so on. In order to analyze the weather radar observation result, we should know the inside structure and data. Some non-precipitation echoes exist inside of the observed radar data. And these echoes affect decreased accuracy of weather forecasting. Therefore, this paper suggests a method that could remove line-shaped non-precipitation echo from raw radar data. The line-shaped echoes are distinguished from the raw radar data and extracted their own features. These extracted data pairs are used as learning data for naive bayesian classifier. After the learning process, the constructed naive bayesian classifier is applied to real case that includes not only line-shaped echo but also other precipitation echoes. From the experiments, we confirm that the conclusion that suggested naive bayesian classifier could distinguish line-shaped echo effectively.

• Atmosphere
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• v.29 no.2
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• pp.197-211
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• 2019

The observational sensitivity of dual-polarization weather radar was quantitatively analyzed by using two different pulse widths. For this purpose, test radar scan strategy which consisted of consecutive radar scan using long (LP: $2{\mu}s$) and short (SP: $1{\mu}s$) pulses at the same elevation angle was employed. The test scan strategy was conducted at three operational S-band dual-polarization radars (KSN, JNI, and GSN) of Korea Meteorological Administration (KMA). First, the minimum detectable reflectivity (MDR) was analyzed as a function of range using large data set of reflectivity ($Z_H$) obtained from JNI and GSN radars. The MDR of LP was as much as 7~22 dB smaller than that of SP. The LP could measure $Z_H$ greater than 0 dBZ within the maximum observational range of 240 km. Secondly, polarimetric observations and the spatial extent of radar echo between two pulses were compared. The cross-polar correlation coefficient (${\rho}_{hv}$) from LP was greater than that from SP at weak reflectivity (0~20 dBZ). The ratio of $Z_H$ (> 0 dBZ) and ${\rho}_{hv}$(> 0.95) bin to total bin calculated from LP were greater than those from SP (maximum 7.1% and 13.2%). Thirdly, the frequency of $Z_H$ (FOR) during three precipitation events was analyzed. The FOR of LP was greater than that of SP, and the difference in FOR between them increased with increasing range. We conclude that the use of LP can enhance the sensitivity of polarimetric observations and is more suitable for detecting weak echoes.

• Atmosphere
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• v.30 no.4
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• pp.347-360
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• 2020

The automatic algorithm optimized for the Korean Peninsula was developed to detect and track the center of typhoon based on a geometrical method using high-resolution retrieved WISSDOM (WInd Syntheses System using DOppler Measurements) wind and reflectivity data. This algorithm analyzes the center of typhoon by detecting the geometric circular structure of the typhoon's eye in radar reflectivity and vorticity 2D field data. For optimizing the algorithm, the main factors of the algorithm were selected and the optimal thresholds were determined through sensitivity experiments for each factor. The center of typhoon was detected for 5 typhoon cases that approached or landed on Korean Peninsula. The performance was verified by comparing and analyzing from the best track of Korea Meteorological Administration (KMA). The detection rate for vorticity use was 15% higher on average than that for reflectivity use. The detection rate for vorticity use was up to 90% for DIANMU case in 2010. The difference between the detected locations and best tracks of KMA was 0.2° on average when using reflectivity and vorticity. After the optimization, the detection rate was improved overall, especially the detection rate more increased when using reflectivity than using vorticity. And the difference of location was reduced to 0.18° on average, increasing the accuracy.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.17-28
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• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1239-1249
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• 2013

According to development of weather radar, researches about observation, analysis or forecast of weather phenomena such as tornado, flash-flood etc. were encouraged by reducing frequency interferences, transmission noises, attenuations of radar signal. In contrast, there is a growing interest in the visualization and expression methods for weather radar data but weather radar manufacturers or the organs of government for weather are just busy interpreting expressed weather images projected on GIS. We propose an effective high definition weather radar information visualization method able to apply various GIS platforms to observe and take actions against rapid local weather changes effectively. In this paper, first we change information acquired from weather radar to raster or vector type high definition data structures using specific algorithms. And then, we quadrate our processed raster/vector type weather data with various GIS platforms accurately to make observers can recognize and check weather situations over exact geographical positions and elevations intuitively. Experimental results verify that our method make observers can recognize and analyze weather changes, tornados, local downpours or flash floods accurately by analyzing high definition weather radar data combined with GIS platform including detailed target locations and elevations.

• Aerospace Engineering and Technology
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• v.3 no.2
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• pp.133-140
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• 2004

In some cases, the launch vehicle is fatally affected by the change of weather condition. Thus the real time monitoring of weather condition is indispensible for successful launch campaign. This paper described general characteristics of weather radar for space center. The analysis of weather radar requirements has been carried out focusing on the transmitting power, gain of antenna, half power beam width, and minimum detectable signal.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1145-1154
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• 2014

In recent years, as frequency and intensity of severe weather disasters such as flash flood have been increasing, providing accurate and prompt information to the public is very important and needs of user-friendly monitoring/warning system are growing. This paper introduces a method that re-produces radar observations as multimedia contents and applies reproduced data to mesh-up services. In addition, a accurate GIS matching technique to help to track the exact location going on serious atmospheric phenomena is presented. The proposed method create multimedia contents having structures such as two dimensional images, vector graphics or three dimensional volume data by re-producing various radar variables obtained from a weather radar. After then, the multimedia formatted weather radar data are matched with various detailed raster or vector GIS map platform. Results of simulation test with various scenarios indicate that the display system based on the proposed method can support for users to figure out easily and intuitively routes and degrees of risk of severe weather. We expect that this technique can also help for emergency manager to interpret radar observations properly and to forecast meteorological disasters more effectively.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.350-357
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• 2022

With the recent prediction of 'Cycle 25', the importance of space weather research increases. Accordingly, the World Radiocommunication Conference (WRC)-23 has adopted Agenda Item 9.1a) and carried out sharing researches between active/passive space weather observation systems and existing services. Therefore, in this paper, in order to increase the precision of space weather environment data and secure the frequency spectrum for observation systems, the direct interference effect from the weather radar in Gosan, Jeju on the space weather observation receiver in Hallim, Jeju, and the indirect interference on the observation receiver by diffraction and scattering from the radar target have been analyzed. As a result, it can be known that the radar direction, the propagation direction diffracted and scattered from the target, and the Rradar Cross Section (RCS) of the radar target, the reception area of the space weather observation antenna, and the antenna off-boresight are important parameters for the interference effect analysis.