• Journal of the Korean association of regional geographers
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• v.1 no.1
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• pp.45-60
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• 1995

The purpose of this study is to classify the Korean precipitation regions on the basis of the characteristics of extratropical cyclonic precipitation. From now on, extratropical cyclone is called cyclone in short. By using factor analysis and Ward method in cluster analysis, precipitation regions on the basis of the characteristics of cyclonic precipitation are classified The principal data used in this study are daily precipitation records obtained from 60 weather stations of the Korea Meteorological Service during the ten years($1981{\sim}1990$), and weather charts published by the Japan Meteorological Agency. The results obtained in this study are summarized as follows: (1) In the factor analysis using 43 variables which have relation to the extratropical cyclonic precipitations, They are seven factors whose eigenvalues are above 1.0. This explains 86 percent of total amount. The first factor explains the characteristics of precipitation in the middle-west area and its contribution degree has the highest 10.9 percent. (2) According to the cluster analysis method of Ward, extratropical cyclonic precipitation regions are classified seven macro regions(such as Kyungki and North Youngseo, Youngdong and Ullungdo, Hoseo and South Youngseo, Honam and Northwest Chejudo, Southeast Chejudo, North Youngnam, and South Youngnam), 22 meso regions. (3) The characteristics of precipitation regions have relations to the path of cyclone, the direction of air inflow and the strike of mountain ranges. As the conclusion, the Central China Low brings much precipitation in the southern coast and southern area of Korea as moving to the northeastward. The North China Low moves eastward and brings much precipitation in the western area of the Taeback mountain ranges. The probability of extratropical cyclonic precipitation is the lowest in the inland of Yeongnam and the eastern coastal areas which belong to the rain shadow region. Namely, The seasonal and spatial characteristics of precipitation are closely associated with the path of cyclone and the direction of air inflow according to its passage, and the strike of mountain ranges.

• Economic and Environmental Geology
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• v.48 no.5
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• pp.371-377
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• 2015

Isotopic compositions of precipitation have been used to understand moisture transport in the atmosphere and interactions between precipitation and groundwater. Isotopic compositions of speleothems and ice cores, so called, ''paleoarchives'', can be utilized to interpret climate of the past and global circulation models (GCMs). The GCMs are able to explain the paleoarchives, can be validated by the precipitation isotopes. The developments of stable isotope analyzers make high-resolution isotopic studies feasible. Therefore, a high-resolution study of precipitation isotopes is needed. For this study, precipitation samples were collected for every 5 to 15 minutes, depending on precipitation rates, using an auto-sampler for precipitation isotopes near coastal area. The isotopic compositions of precipitation range from -5.7‰ (-40.1‰) to -10.8‰ (-74.3‰) for oxygen (hydrogen). The slope of ${\delta}^{18}O-{\delta}D$ diagram for the whole period is 6.8, but that of each storm is 5.1, 4.2, 7.9 and 7.7, respectively. It indicates that evaporation occurred during the first two storms, while the latter two storm did not experience any evaporation. The isotopic fractionations of precipitation has significant implications for the water cycle and high-resolution data of precipitation isotopes will be needed for the future studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

• Atmosphere
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• v.29 no.4
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• pp.343-353
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• 2019

The seasonal climatology of atmospheric rivers (ARs) and their effects on the seasonal precipitation and temperature in Korea are examined using the AR chronology obtained by a methodology based on the vertically integrated water vapor transport (IVT) in conjunction with a fine-scale gridded analysis of station precipitation and temperature. ARs are found to affect Korea most heavily in the warm season with minimal impacts in winter. This contrasts the AR effects in the western North America and the Western Europe that are affected most in winters. Significant portions of precipitation in Korea are associated with AR landfalls for all seasons; over 35% (25%) of the summer (winter) rainfall in the southern part of the Korean peninsula. The percentage of AR precipitation over Korea decreases rapidly towards the north. AR landfalls are also associated with heavier-than-normal precipitation events for all seasons. AR landfalls are associated with above-normal temperatures in Korea; the warm anomalies increase towards the north. The warm anomalies during AR landfalls are primarily related to the reduction in cold episodes as the AR landfalls in Korea are accompanied by anomalous southerlies/southwesterlies.

• Atmosphere
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• v.18 no.4
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• pp.387-395
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• 2008

The impact of horizontal resolution on a regional climate model was investigated by simulating precipitation over the Korean Peninsula. As a regional climate model, the SNURCM(Seoul National University Regional Climate Model) has 21 sigma layers and includes the NCAR CLM(National Center for Atmospheric Research Community Land Model) for land-surface model, the Grell scheme for cumulus convection, the Simple Ice scheme for explicit moisture, and the MRF(Medium-Range Forecast) scheme for PBL(Planetary Boundary Layer) processing. The SNURCM was performed with 20 km resolution for Korea and 60 km resolution for East Asia during a 20-year period (1980-1999). Although the SNURCM systematically underestimated precipitation over the Korean Peninsula, the increase of model resolution simulated more precipitation in the southern region of the Korean Peninsula, and a more accurate distribution of precipitation by reflecting the effect of topography. The increase of precipitation was produced by more detailed terrain data which has a 10 minute terrain in the 20 km resolution model compared to the 30 minute terrain in the 60 km resolution model. The increase in model resolution and more detailed terrain data played an important role in generating more precipitation over the Korean Peninsula. While the high resolution model with the same terrain data resulted in increasing of precipitation over the Korean Peninsula including the adjoining sea, the difference of the terrain data resolution only influenced the precipitation distribution of the mountainous area by increasing the amount of non-convective rain. In conclusion, the regional climate model (SNURCM) with higher resolution simulated more precipitation over the Korean Peninsula by reducing the systematic underestimation of precipitation over the Korean Peninsula.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.101-112
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• 2022

Extreme precipitation events have recently become a leading cause of disasters. Thus, investigating the variability and trends of extreme precipitation is crucial to mitigate the increasing impact of such events. Spatial distribution and temporal trends in annual precipitation and four extreme precipitation indices of duration (CWD), frequency (R10 mm), intensity (Rx1day), and percentile-based threshold (R95pTOT) were analyzed using the daily precipitation data of 10 observation stations in Chungcheong province during 1974-2020. The precipitation at all observation stations, except the Boryeong station, showed nonsignificant increasing trends at 95% confidence level (CL) and increasing magnitudes from the west to east regions. The high variability in mean annual precipitation was more pronounced around the northeast and northwest regions. Similarly, there were moderate to high patterns in extreme precipitation indices around the northeast region. However, the precipitation indices of duration and frequency consistently increased from the west to east regions, while those of intensity and percentile-based threshold increased from the south to east regions. Nonsignificant increasing trends dominated in CWD, R10 mm, and Rx1day at all stations, except for R10 mm at Boeun station and Rx1day at Cheongju and Jecheon stations, which showed a significantly increasing trend. The spatial distribution of trend magnitude shows that R10 mm increased from the west to east regions. Furthermore, variations in precipitation were very strongly correlated (99% CL) with R10 mm, Rx1day, and R95pTOT at all stations, except with wR10 mm at Cheongju station, which was strongly correlated with a 95% CL.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.657-665
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• 1998

New diagnosing method o flood possibility was proposed. The method can be processed by following steps: first, decide if current available water resources are above normal or not; second, compute a consecutive period above normal; third, precipitation is accumulate through the period; fourth, daily depletion (runoff and evapotranspiration) amount is subtracted from the accumulated precipitation and remains are translated to one day's precipitation, which is called effective precipitation; and finally, effective precipitation index. the larger effective precipitation index means the higher flood possibility. This method has been applied to the flood event occurred in the central region of Korea at late July 1996 and compared with the study by Korea Water resources Association (1996). The new method is proven to be much faster in computation, and therefore much better in practical use for emergency situation than current rainfall-runoff models. It is because the new method simplifies some steps of currently used method such as parameter estimation and water level observation. It is also known that new method is more scientific than any other methods that use accumulated precipitation only as it considers the runoff depletion in time

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.269-274
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• 2024

High-quality precipitation data are crucial for various industries, including disaster prevention. In South Korea, long-term high-quality data are collected through numerous ground observation stations. However, data between these stations are reprocessed into a grid format using interpolation methods, which may not perfectly match actual precipitation. A prime example of real-time observational grid data globally is the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) from National Aeronautics and Space Administration (NASA), while in South Korea, ground radar data are more commonly used. GPM and ground radar data exhibit distinct differences due to their respective processing methods. This study aims to analyze the characteristics of GPM and Constant Altitude Plan Position Indicator(CAPPI),representative real-time grid data, by comparing them with ground-observed precipitation data. The study period spans from 2021 to 2022, focusing on hourly data from Automated Synoptic Observing System (ASOS) sites in South Korea. The GPM data tend to underestimate precipitation compared to ASOS data, while CAPPI shows errors in estimating low precipitation amounts. Through this comparative analysis, the study anticipates identifying key considerations for utilizing these data in various applied fields, such as recalculating design rainfall, thereby aiding researchers in improving prediction accuracy by using appropriate data.

• Journal of Ecology and Environment
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• v.42 no.2
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• pp.77-84
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• 2018

Background: For understanding and evaluating a more realistic and accurate assessment of ecosystem carbon balance related with environmental change or difference, it is necessary to analyze the various interrelationships between soil respiration and environmental factors. However, the soil temperature is mainly used for gap filling and estimation of soil respiration (Rs) under environmental change. Under the fact that changes in precipitation patterns due to climate change are expected, the effects of soil moisture content (SMC) on soil respiration have not been well studied relative to soil temperature. In this study, we attempt to analyze relationship between precipitation and soil respiration in temperate deciduous broad-leaved forest for 2 years in Gwangneung. Results: The average soil temperature (Ts) measured at a depth of 5 cm during the full study period was $12.0^{\circ}C$. The minimum value for monthly Ts was $-0.4^{\circ}C$ in February 2015 and $2.0^{\circ}C$ in January 2016. The maximum monthly Ts was $23.6^{\circ}C$ in August in both years. In 2015, annual precipitation was 823.4 mm and it was 1003.8 mm in 2016. The amount of precipitation increased by 21.9% in 2016 compared to 2015, but in 2015, it rained for 8 days more than in 2016. In 2015, the pattern of low precipitation was continuously shown, and there was a long dry period as well as a period of concentrated precipitation in 2016. 473.7 mm of precipitation, which accounted for about 51.8% of the precipitation during study period, was concentrated during summer (June to August) in 2016. The maximum values of daily Rs in both years were observed on the day when precipitation of 20 mm or more. From this, the maximum Rs value in 2015 was $784.3mg\;CO_2\;m^{-2}\;h^{-1}$ in July when 26.8 mm of daily precipitation was measured. The maximum was $913.6mg\;CO_2\;m^{-2}\;h^{-1}$ in August in 2016, when 23.8 mm of daily precipitation was measured. Rs on a rainy day was 1.5~1.6 times higher than it without precipitation. Consequently, the annual Rs in 2016 was about 12% higher than it was in 2015. It was shown a result of a 14% increase in summer precipitation from 2015. Conclusions: In this study, it was concluded that the precipitation pattern has a great effect on soil respiration. We confirmed that short-term but intense precipitation suppressed soil respiration due to a rapid increase in soil moisture, while sustained and adequate precipitation activated Rs. In especially, it is very important role on Rs in potential activating period such as summer high temperature season. Therefore, the accuracy of the calculated values by functional equation can be improved by considering the precipitation in addition to the soil temperature applied as the main factor for long-term prediction of soil respiration. In addition to this, we believe that the accuracy can be further improved by introducing an estimation equation based on seasonal temperature and soil moisture.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1260-1264
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• 2009

Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.