• Journal of the Korean earth science society
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• v.26 no.1
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• pp.66-77
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• 2005

Aerological observation at Heuksando located in south-western part of Koran Peninsula has been started at 1 June 2003. In order to clarify the improvement of meteorological prediction quality. it is necessary to compare between aerological data observed at Gawngju and Heuksando and to make clear the influence of Heuksando data assimilation. Therefore numerical simulations were carried out with High resolution meterological prediction system based on MM5(The 5th Generation Mesoscale Model). The pattern of wind and temperature field observed at Heuksando and Gwangju are different due to land surface friction End Sensible heat flux at surface and the wind field Simulated With Gwangju and Heuksando aerological data agree well with observation wind field. Although the amount of precipitation in these experiments is underestimated. the area and starting time of precipitation around Honam province in case with Heuksando data is more reliable that without the data.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.556-572
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• 2015

This paper presents the applications of spatial interpolation and assimilation methods for satellite and ground meteorological data, including temperature, relative humidity, and precipitation in regions of Vietnam. In this work, Universal Kriging is used for spatially interpolating ground data and its interpolated results are assimilated with corresponding satellite data to anticipate better gridded data. The input meteorological data was collected from 98 ground weather stations located all over Vietnam; whereas, the satellite data consists of the MODIS Atmospheric Profiles product (MOD07), the ASTER Global Digital Elevation Map (ASTER DEM), and the Tropical Rainfall Measuring Mission (TRMM) in six years. The outputs are gridded fields of temperature, relative humidity, and precipitation. The empirical results were evaluated by using the Root mean square error (RMSE) and the mean percent error (MPE), which illustrate that Universal Kriging interpolation obtains higher accuracy than other forms of Kriging; whereas, the assimilation for precipitation gradually reduces RMSE and significantly MPE. It also reveals that the accuracy of temperature and humidity when employing assimilation that is not significantly improved because of low MODIS retrieval due to cloud contamination.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Journal of the Korean Geographical Society
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• v.51 no.1
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• pp.23-40
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• 2016

In this study, long-term changes in means and extreme events of precipitation during summer rainy period called Changma (late June~early September) are examined based on rainfall data observed by Chukwooki during Joseon Dynasty (1777~1907) and by modern rain-gauge onward (1908~2015) in Seoul, Korea. Also, characterizations of the relevant changes in synoptic climate fields in East Asia are made by the examination of the NCEP-NCAR reanalysis I data. Analyses of 239-year time series of precipitation data demonstrate that the total precipitation as well as their inter-annual variability during the entire Changma period (late June~early September) has increased in the late 20th century and onward. Notably, since the early 1990s the means and extreme events during the summer Changma period (late June~mid-July) and Changma break period (late July~early August) has significantly increased, resulting in less clear demarcations of sub-Changma periods. In this regard, comparisons of synoptic climate fields before and after the early 1990s reveal that in recent decades the subtropical high pressure has expanded in the warmer Pacific as the advection of high-latitude air masses toward East Asia was enhanced due to more active northerly wind vector around the high pressure departure core over Mongolia. Consequently, it is suggested that the enhancement of rising motions due to more active confluence of the two different air masses along the northwestern borders of the Pacific might lead to the increases of the means and extreme events of Changma precipitation in Seoul in recent decades.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.1-19
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• 2008

This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.

• Atmosphere
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• v.16 no.3
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• pp.247-257
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• 2006

The Yeong-dong heavy snowfall forecast supporting system has been developed during the last several years. In order to construct the conceptual model, we have examined the characteristics of heavy snowfalls in the Yeong-dong region classified into three precipitation patterns. This system is divided into two parts: forecast and observation. The main purpose of the forecast part is to produce value-added data and to display the geography based features reprocessing the numerical model results associated with a heavy snowfall. The forecast part consists of four submenus: synoptic fields, regional fields, precipitation and snowfall, and verification. Each offers guidance tips and data related with the prediction of heavy snowfalls, which helps weather forecasters understand better their meteorological conditions. The observation portion shows data of wind profiler and snow monitoring for application to nowcasting. The heavy snowfall forecast supporting system was applied and tested to the heavy snowfall event on 28 February 2006. In the beginning stage, this event showed the characteristics of warm precipitation pattern in the wind and surface pressure fields. However, we expected later on the weak warm precipitation pattern because the center of low pressure passing through the Straits of Korea was becoming weak. It was appeared that Gangwon Short Range Prediction System simulated a small amount of precipitation in the Yeong-dong region and this result generally agrees with the observations.

• Journal of Environmental Science International
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• v.23 no.10
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• pp.1719-1729
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• 2014

This study is carried out in order to bridge the gap to understand the relationships between South Asian and East Asian monsoon systems by comparing the summer (June-September) precipitation of Nepal and South Korea. Summer monsoon precipitation data from Nepal and South Korea during 30 years (1981-2010) are used in this research to investigate the association. NCEP/NCAR reanalysis data are also used to see the nature of large scale phenomena. Statistical applications are used to analyze these data. The analyzed results show that summer monsoon precipitation is higher over Nepal ($1513.98{\pm}159.29mm\;y^{-1}$) than that of South Korea ($907.80{\pm}204.71mm\;y^{-1}$) and the wettest period in both the countries is July. However, the coefficient of variation shows that amplitude of interannual variation of summer monsoon over South Korea (22.55%) is larger in comparison to that of Nepal (10.52%). Summer monsoon precipitation of Nepal is found to be significantly correlated to that of South Korea with a correlation coefficient of 0.52 (99% confidence level). Large-scale circulations are studied to further investigate the relationship between the two countries. wind and specific humidity at 850 hPa show a strong westerly from Arabian Sea to BOB and from BOB, wind moves towards Nepal in a northwestward direction during the positive rainfall years. In case of East Asia, strong northward displacement of wind can be observed from Pacific to South Korea and strong anticyclone over the northwestern Pacific Ocean. However, during the negative rainfall years, in the South Asian region we can find weak westerly from the Arabian Sea to BOB, wind is blowing in a southerly direction from Nepal and Bangladesh to BOB.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.99-106
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• 2015

In this study, we propose Radial basis function Neural Network(RBFNN) using Recursive Weighted Least Square Estimation(RWLSE) to effectively deal with big data class meteorological radar data. In the condition part of the RBFNN, Fuzzy C-Means(FCM) clustering is used to obtain fitness values taking into account characteristics of input data, and connection weights are defined as linear polynomial function in the conclusion part. The coefficients of the polynomial function are estimated by using RWLSE in order to cope with big data. As recursive learning technique, RWLSE which is based on WLSE is carried out to efficiently process big data. This study is experimented with both widely used some Machine Learning (ML) dataset and big data obtained from meteorological radar to evaluate the performance of the proposed classifier. The meteorological radar data as big data consists of precipitation echo and non-precipitation echo, and the proposed classifier is used to efficiently classify these echoes.

• Atmosphere
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• v.30 no.1
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• pp.17-30
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• 2020

KMA performed the special observation program to provide information about severe weather and to monitor typhoon PRAPIROON using the ship which called the Gisang 1 from 29 June 2018 to 4 July 2018 (UTC). For this period, upper-air was observed 21 times with 6 hour intervals using rawinsonde in the Gisang 1. We investigated the impact of upper-air observation data from the Gisang 1 on the performance of the operational convective scale model (we called LDAPS). We conducted two experiments that used all observation data including upper-air observation data from the Gisang 1 (OPER) and without it (EXPR). For a typhoon PRAPIROON case, track forecast error of OPER was lower than EXPR until forecast 24 hours. The intensity forecast error of OPER for minimum sea level pressure was lower than EXPR until forecast 12 hours. The intensity forecast error of OPER for maximum wind speed was mostly lower than EXPR until forecast 30 hours. OPER showed good performance for typhoon forecast compared with EXPR at the early lead time. Two precipitation cases occurred in the south of the Korean peninsula due to the impact of Changma on 1 July and typhoon on 3 July. The location of main precipitation band predicted from OPER was closer to observations. As assimilating upper-air data observed in the Gisang 1 to model, it showed positive results in typhoon and precipitation cases.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.49-60
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• 2004

Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.