• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.65-74
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• 2017

North Korea is one of the high vulnerable countries facing the threat of natural disaster and has experienced more frequent disasters in recent years. These disasters have significantly led to food shortages and large reductions in crop yields. In 2015, both North Korean officials and international agencies had identified the extreme drought event, the worst in one hundred years according to the North Korean government. The objective of this study was an assessment of the extreme drought events in 2014~2015, and to apply climatic drought indices for drought monitoring in North Korea. Characteristics of the extreme drought in North Korea are examined by using the weekly-based Standardized Precipitation Evapotranspiration Index (SPEI). The drought characteristics illustrated by the SPEI results are compared with a Standardized Precipitation Index (SPI) results and drought impact information to understand how these indices can explain the drought conditions within the country. These results demonstrated that the SPEI could be an effective tool to provide improved spatial and temporal drought conditions to inform management decisions for drought policy.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.137-149
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• 2015

Flood planning needs to recognize trends for extreme precipitation events. Especially, the r-year return level is a common measure for extreme events. In this paper, we present a nonstationary temporal model for precipitation return levels using a hierarchical Bayesian modeling. For intensity, we model annual maximum daily precipitation measured in Korea with a generalized extreme value (GEV). The temporal dependence among the return levels is incorporated to the model for GEV model parameters and a linear model with autoregressive error terms. We apply the proposed model to precipitation data collected from various stations in Korea from 1973 to 2011.

• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.379-394
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• 2008

Recently, extreme precipitation events beyond design capacity of hydraulic system have been occurred and this is the causes of failure of hydraulic structure for flood prevention and of severe flood damage. Therefore it is very important to understand temporal and spatial characteristics of extreme precipitation events as well as expected changes in extreme precipitation events and distributional characteristics during design period under future climate change. In this paper, climate change scenarios were used to assess the impacts of future climate change on extreme precipitation. Furthermore, analysis of future extreme precipitation characteristics and I-D-F analysis were carried out. This study used SRES B2 greenhouse gas scenario and YONU CGCM to simulate climatic conditions from 2031 to 2050 and statistical downscaling method was applied to establish weather data from each of observation sites operated by the Korean Meteorological Administration. Then quantile mapping of bias correction methods was carried out by comparing the simulated data with observations for bias correction. In addition Modified Bartlett Lewis Rectangular Pulse(MBLRP) model (Onof and Wheater, 1993; Onof 2000) and adjust method were applied to transform daily precipitation time series data into hourly time series data. Finally, rainfall intensity, duration, and frequency were calculated to draw I-D-F curve. Although there are 66 observation sites in Korea, we consider here the results from only Seoul, Daegu, Jeonju, and Gwangju sites in this paper. From the results we found that the rainfall intensity will be increased and the bigger intensity will be occurred for longer rainfall duration when we compare the climate conditions of 2030s with present conditions.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.247-253
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• 2013

It has long been known that the magnetospheric particles can precipitate into the atmosphere of the Earth. In this paper we examine such precipitation of energetic electrons using the data obtained from low-altitude polar orbiting satellite observations. We analyze the precipitating electron flux data for many periods selected from a total of 84 storm events identified for 2001-2012. The analysis includes the dependence of precipitation on the Kp index and the electron energy, for which we use three energies E1 > 30 keV, E2 > 100 keV, E3 > 300 keV. We find that the precipitation is best correlated with Kp after a time delay of < 3 hours. Most importantly, the correlation with Kp is notably tighter for lower energy than for higher energy in the sense that the lower energy precipitation flux increases more rapidly with Kp than does the higher energy precipitation flux. Based on this we suggest that the Kp index reflects excitation of a wave that is responsible for scattering of preferably lower energy electrons. The role of waves of other types should become increasingly important for higher energy, for which we suggest to rely on other indicators than Kp if one can identify such an indicator.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.247-247
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• 2015

Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

• Atmosphere
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• v.26 no.4
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• pp.509-522
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• 2016

Heavy snowfall events have occurred frequently in the Yeongdong region but understanding of these events have trouble in lack of snowfall observation in this region because it is composed of complex topography like the "Taebaek mountains" and the "East sea". These problems can be solved by quantitative precipitation estimation technique using remote sensing such as radar, satellite, etc. Two radars which are able to cover over Yeondong region were installed at Gangneung (GNG) and Gwangdeoksan (GDK). This study uses radar and water equivalent of snow cover to investigate the characteristics of radar echoes and the $Z_e-R$ relations associated with the 10 Yeongdong heavy snowfall events during the last 5 years (2010~2014). It was found that the heights which the probability of detection (POD) of snow detection by GNG radar is more than 80% are 3,000 m and 1,500 m in convective cloud and stratiform cloud, respectively. The vertical gradient of radar reflectivity is less decreased in convective cloud than stratiform cloud. However, POD by GDK radar are lower than 80% at all layers because the majority of Yeondong observational stations are more than 100 km away from GDK radar site. Furthermore, we examined $Z_e-R$ relation from the 10 events using GNG radar and compared the "a" and "b" obtained from these examinations at Sokcho (SC) and Daegwallyeong (DG). These "a" and "b" are estimated from radar echo at 500 m (SC) and 1,500 m (DG). The values of "a" differ in their stations such as SC and DG are 30~116 and 6~39, respectively. But "b" is 0.4~1.7 irrespective of stations. Moreover, the value of "a" increased with surface air temperature. Therefore, quantitative precipitation estimation in heavy snowfall events by radar echo using fixed "a" and "b" is difficult because these values changed according to those precipitation characteristics.

• Journal of Environmental Science International
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• v.26 no.3
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• pp.289-302
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• 2017

During the research period, error analysis of the amount of daily precipitation was performed with data obtained from 2DVD, Parsivel, and AWS, and from the results, 79 days were selected as research days. According to the results of a synoptic meteorological analysis, these days were classified into 'LP type, CF type, HE type, and TY type'. The dates showing the maximum daily precipitation amount and precipitation intensity were 'HE type and CF type', which were found to be attributed to atmospheric instability causing strong ascending flow, and leading to strong precipitation events. Of the 79 days, most days were found to be of the LP type. On July 27, 2011 the daily precipitation amount in the Korean Peninsula reached over 80 mm (HE type). The leading edge of the Northern Pacific high pressure was located over the Korean Peninsula with unstable atmospheric conditions and inflow of air with high temperature and high humidity caused ascending flow, 120 mm/h with an average precipitation intensity of over 9.57 mm/h. Considering these characteristics, precipitation in these sample dates could be classified into the convective rain type. The results of a precipitation scale distribution analysis showed that most precipitation were between 0.4-5.0 mm, and 'Rain' size precipitation was observed in most areas. On July 9, 2011, the daily precipitation amount was recorded to be over 80 mm (CF type) at the rainy season front (Jangma front) spreading across the middle Korean Peninsular. Inflow of air with high temperature and high humidity created unstable atmospheric conditions under which strong ascending air currents formed and led to convective rain type precipitation.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.763-777
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• 2002

The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• Atmosphere
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• v.32 no.2
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• pp.135-148
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• 2022

This study investigates the influence of atmospheric river (AR) on precipitation over South Korea with a focus on regional characteristics. The 42-year-long catalog of ARs, which is obtained by applying the automatic AR detection algorithm to ERA5 reanalysis data and the insitu precipitation data recorded at 56 weather stations across the country are used to quantify their relationship. Approximately 51% of the climatological annual precipitation is associated with AR. The AR-related precipitation is most pronounced in summer by approximately 58%, while only limited fraction of precipitation (26%) is AR-related in winter. The heavy precipitation (> 30 mm day^-1) is more prone to AR activity (59%) than weak precipitation (5~30 mm day^-1; 33%) in all seasons. By grouping weather stations into the four sub-regions based on orography, it is found that the contribution of AR precipitation to the total is largest in the southern coast (57%) and smallest in the eastern coast (36%). Similar regional variations in AR precipitation fractions also occur in weak precipitation events. The regional contrast between the northern and southern stations is related to the seasonal variation of AR-frequency. In addition, the regional contrast between the western and eastern stations is partly modulated by the orographic forcing. The fractional contribution of AR to heavy precipitation exceeds 50% in all seasons, but this is true only in summer along the eastern coast. This result indicates that ARs play a critical role in heavy precipitation in South Korea, thus routine monitoring of ARs is needed for improving operational hydrometeorological forecasting.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.3
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• pp.1-11
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• 2014

Recently, major cities in Korea are suffering from frequent urban flooding caused by heavy rainfall. Such urban flooding mainly occurs due to the limited design capacity of the current drainage network, which increases the vulnerability of the cities to cope with intense precipitation events brought about by climate change. In other words, it can be interpreted that runoff exceeding the design capacity of the drainage network and increased impervious surfaces in the urban cities can overburden the current drainage system and cause floods. The study presents the green roof as a sustainable solution for this issue, and suggests the pre-design using the LID controls model in SWMM to establish more specific flood prevention system. In order to conduct the computer simulation in connection with Korean climate, the study used the measured precipitation data from Cheonan Station of Korea Meteorological Administration (KMA) and the forecasted precipitation data from RCP 8.5 scenario. As a result, Extensive Green Roof System reduced the peak runoff by 53.5% with the past storm events and by 54.9% with the future storm events. The runoff efficiency was decreased to 4% and 7%. This results can be understood that Extensive Green Roof System works effectively in reducing the peak runoff instead of reducing the total stormwater runoff.