• Atmosphere
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• v.19 no.2
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• pp.127-143
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• 2009

This study investigates characteristics of wintertime simulation conducted by METRI AGCM utilizing new radiation parameterization scheme. New radiation scheme is based on the method of Chou et al., and is utilized in the METRI AGCM recently. In order to analyze characteristics of seasonal simulation in boreal winter, hindcast dataset from 1979 to 2005 is produced in two experiments - control run (CTRL) and new model's run (RADI). Also, changes in performance skill and predictability due to implementation of new radiation scheme are examined. In the wintertime simulation, the RADI experiment tends to reduce warm bias in the upper troposphere probably due to intensification of longwave radiative cooling over the whole troposphere. The radiative cooling effect is related to weakening of longitudinal temperature gradient, leading to weaker tropospheric jet in the upper troposphere. In addition, changes in vertical thermodynamic structure have an influence on reduction of tropical precipitation. Moreover, the RADI case is less sensitive to variation of tropical sea surface temperature than the CTRL case, even though the RADI case simulates the mean climate pattern well. It implies that the RADI run does not have significant improvement in seasonal prediction point of view.

• Atmosphere
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• v.29 no.3
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• pp.257-267
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• 2019

This study is to assess the applicability of the Extreme Forecast Index (EFI) algorithm of the ECMWF seasonal forecast system to the Global Seasonal Forecasting System version 5 (GloSea5), operational seasonal forecast system of the Korea Meteorological Administration (KMA). The EFI is based on the difference between Cumulative Distribution Function (CDF) curves of the model's climate data and the current ensemble forecast distribution, which is essential to diagnose the predictability in the extreme cases. To investigate its applicability, the experiment was conducted during the heat-wave cases (the year of 1994 and 2003) and compared GloSea5 hindcast data based EFI with anomaly data of ERA-Interim. The data also used to determine quantitative estimates of Probability Of Detection (POD), False Alarm Ratio (FAR), and spatial pattern correlation. The results showed that the area of ERA-Interim indicating above 4-degree temperature corresponded to the area of EFI 0.8 and above. POD showed high ratio (0.7 and 0.9, respectively), when ERA-Interim anomaly data were the highest (on Jul. 11, 1994 (> $5^{\circ}C$) and Aug. 8, 2003 (> $7^{\circ}C$), respectively). The spatial pattern showed a high correlation in the range of 0.5~0.9. However, the correlation decreased as the lead time increased. Furthermore, the case of Korea heat wave in 2018 was conducted using GloSea5 forecast data to validate EFI showed successful prediction for two to three weeks lead time. As a result, the EFI forecasts can be used to predict the probability that an extreme weather event of interest might occur. Overall, we expected these results to be available for extreme weather forecasting.

• Journal of Astronomy and Space Sciences
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• v.33 no.2
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• pp.137-146
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• 2016

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

• Journal of Environmental Science International
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• v.24 no.11
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• pp.1371-1384
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• 2015

This study analyzes the characteristics of Western North Pacific (WNP) tropical cyclone (TC) activity and large-scale environments according to the Western Pacific (WP) teleconnection pattern in summer. In the positive WP phase, an anomalous cyclone and an anomalous anticyclone develop in the low and middle latitudes of the East Asia, respectively. As a result, southeasterlies are reinforced in the northeast area of the East Asia including Korea and Japan which facilitates the movement of TC to this area, whereas northwesterlies are reinforced in the southwest area of the East Asia including South China and Indochina Peninsula which blocks the movement of TC to this area. Due to the spatial distribution of this reinforced pressure system, TCs develop, move, and turn more to the northeast of WNP than those in the negative WP phase. Consequently, the characteristics of this TC activity in the positive WP phase are associated with the location of upper tropospheric jet further to the northeast. Meanwhile, TCs in the negative WP phase mainly move to the west from Philippines toward south China and Indochina Peninsula. Furthermore, due to the terrain effect caused by the high passage frequency of TCs in the mainland China, the intensity of TCs are weaker than those in the positive WP phase.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.3
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• pp.357-365
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• 2005

The typical patterns of surface $O_3$ pollution and their dependence on meteorology were studied in the Greater Seoul Area (GSA) during warm season (April-September) from 1998 to 2002. In order to classify the $O_3$ pollution patterns, two-stage (average linkage then k-means) clustering technique was employed based on daily maximum $O_3$ concentrations obtained from 53 monitoring sites during high $O_3$ events (118 days). The clustering technique identified four statistically distinct $O_3$ pollution patterns representing the different horizontal distributions and levels of $O_3$ in GSA. The prevailed pattern (93 days, $49.5\%$) distinctly showed the gradient of $49.5\%$ concentrations going from west to east in GSA. Very high $49.5\%$ concentrations throughout GSA (24 days, $12.8\%$) were also found as a significant pattern of severe $O_3$ pollution. In order to understand the characteristics of $O_3$ pollution patterns, the relationship between $O_3$ pollution patterns and meteorological conditions were analyzed using both synoptic charts and surface/upper air data. Each pattern was closely associated with surface wind interacted with synoptic background flow allowing to transport and accumulate $O_3$ and its precursor. In particular, the timing and inland penetration of sea-breeze were apparently found to play very important role in determining $O_3$ distributions.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.31-40
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• 2017

The aim of this study is to estimate net irrigation requirements for red pepper during growing period using soil moisture model. The soil moisture model based on water balance approach simulates soil moisture contents of 4 soil layers in crop root zone considering soil moisture extraction pattern. The LAMP (Land-Atmosphere Modeling Package) high resolution meteorological data provided from National Center for AgroMeteorology (NCAM) was used to simulate soil moisture as the input weather data. Study area for the LAMP data and soil moisture simulation covers $36.92^{\circ}{\sim}37.40^{\circ}$ in latitude and $127.36^{\circ}{\sim}127.94^{\circ}$ in longitude. Soil moisture was monitored using FDR (Frequency Domain Reflectometry) sensors and the data were used to validate the simulation model from May 24 to October 20 in 2016. The results showed spatially detailed soil moisture pattern under different weather conditions and soil texture. Net irrigation requirements were also different by location reflecting the spatially distributed weather condition. The average of the requirements was 470.7 mm and averages about soil texture were 466.8 mm, 482.4 mm, 456.0 mm, 481.7 mm, and 465.6 mm for clay loam, sandy loam, silty clay loam, clay, and sand respectively. This study showed spatial differences of soil moisture and the irrigation requirements of red pepper about spatially uneven weather condition and soil texture. From the results, it was demonstrated that high resolution meteorological data could provide an opportunity of spatially different crop water requirement estimation during the irrigation management.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.536-541
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• 2014

Data through meteorological radar includes ground echo, sea-clutter echo, anomalous propagation echo, clear echo and so on. Each echo is a kind of non-precipitation echoes and the characteristic of individual echoes is analyzed in order to identify with non-precipitation. Meteorological radar data is analyzed through pre-processing procedure because the data is given as big data. In this study, echo pattern classifier is designed to distinguish non-precipitation echoes from precipitation echo in meteorological radar data using RBFNNs and echo judgement module. Output performance is compared and analyzed by using both HCM clustering-based RBFNNs and FCM clustering-based RBFNNs.

• Atmosphere
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• v.25 no.4
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• pp.611-622
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• 2015

Heavy rainfall ($>30mm\;hr^{-1}$) over the Korean Peninsula is examined in order to understand thermo-dynamic characteristics of the atmosphere, using radiosonde observational data from seven upper-air observation stations during the last 17 years (1997~2013). A total of 82 heavy rainfall cases during the summer season (June-August) were selected for this study. The average values of thermo-dynamic indices of heavy rainfall events are Total Precipitable Water (TPW) = 60 mm, Convective Available Potential Energy (CAPE) = $850J\;kg^{-1}$, Convective Inhibition (CIN) = $15J\;kg^{-1}$, Storm Relative Helicity (SRH) = $160m^2s^{-2}$, and 0~3 km bulk wind shear = $5s^{-1}$. About 34% of the cases were associated with a Changma front; this pattern is more significant than other synoptic pressure patterns such as troughs (22%), migratory cyclones (15%), edges of high-pressure (12%), typhoons (11%), and low-pressure originating from Changma fronts (6%). The spatial distribution of thermo-dynamic conditions (CAPE and SRH) is similar to the range of thunderstorms over the United States, but extreme conditions (supercell thunderstorms and tornadoes) did not appear in the Korean Peninsula. Synoptic conditions, vertical buoyancy (CAPE, CIN), and wind parameters (SRH, shear) are shown to discriminate among the environments of the three types. The first type occurred with high CAPE and low wind shear by the edge of the high pressure pattern, but Second type is related to Changma front and typhoon, exhibiting low CAPE and high wind shear. The last type exhibited characteristics intermediate between the first and second types, such as moderate CAPE and wind shear near the migratory cyclone and trough.

• 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 Environmental Science International
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• v.9 no.4
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• pp.295-302
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• 2000

This study was conducted to investigate the characteristics of surface ozone concentration and occurrence of high ozone concentration using hourly ozone, nitrogen dioxide and meteorological data for 1997~1998 in Pusan coastal area. Monthly mean ozone concentration was the highest at Dongsamdong in Spring(35.4ppb), at Kwangbokdong in Fall(25.1ppb) and the lowest Dongsamdong(22.2ppb) and Kwangbokdong(16.0ppb) in Winter. Relative standard deviation indicating clearness of observation site was 0.42 at Dongsamdong and 0.49 at Kwangbokdong that is similar to urban area. The diurnal variation of ozone concentration of Dongsamdong and Kwangbokdong showed maximum at 1500~1600LST and minimum 0700~0800LST that typical pattern of ozone concentration. In ozone episode period(Sept. 10~15, 1998), diurnal change of ozone concentration was very high, and ozone concentration was related to meteorological parameters such as temperature, relative humidity, wind speed, cloud amount and radiation on a horizontal surface. During the episode days peak ozone concentrations are much higher than the normal values, wind speeds are always lower, and solar radiation is high with the exception of the September episode.