• Atmosphere
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• v.24 no.2
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• pp.159-171
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• 2014

This study investigated the temporal and spatial characteristics of summertime (June-August) precipitation over Korean peninsula, using Korea Meteorological Administration (KMA)is Automated Synoptic Observing System (ASOS) data for the period of 1973-2010 and Automatic Weather System (AWS) data for the period of 1998-2010.The authors looked through climatological features of the summertime precipitation, then examined the degree of locality of the precipitation, and probable precipitation amount and its return period of 100 years (i.e., an extreme precipitation event). The amount of monthly total precipitation showed increasing trends for all the summer months during the investigated 38-year period. In particular, the increasing trends were more significant for the months of July and August. The increasing trend of July was seen to be more attributable to the increase of precipitation intensity than that of frequency, while the increasing trend of August was seen to be played more importantly by the increase of the precipitation frequency. The e-folding distance, which is calculated using the correlation of the precipitation at the reference station with those at all other stations, revealed that it is August that has the highest locality of hourly precipitation, indicating higher potential of localized heavy rainfall in August compared to other summer months. More localized precipitation was observed over the western parts of the Korean peninsula where terrain is relatively smooth. Using the 38-years long series of maximum daily and hourly precipitation as input for FARD2006 (Frequency Analysis of Rainfall Data Program 2006), it was revealed that precipitation events with either 360 mm $day^{-1}$ or 80 mm $h^{-1}$ can occur with the return period of 100 years over the Korean Peninsula.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.41-53
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• 2008

Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3270-3278
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• 2014

Many researches has been conducted as extreme rainfall in hydrology and extreme rainfall analysis is not proper for determination of CSOs treatment capacity. In this study, runoff is calculated by tranformation from rainfall to runoff according to Interevent Time Definition. The capacity of sewage treatment plant is designed by 3 times of DWF(Dry Weather Flow) and the efficiency of present sewage treatment plant is very low becauseat at present. Also, The sewage treatment plant can not control CSOs. In this research, the pollution load is calculated by EMC(Event Mean Concentration) and pollution concetration of total runoff is a standard deciding suitablility of present sewage treatment plant. Finally, CSOs treatment capacity is determinated considering pollution load.

• Atmosphere
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• v.31 no.2
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• pp.199-214
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• 2021

A record-breaking high surface air temperature of 41.0℃ was observed on 1 August 2018 at Hongcheon, South Korea. In this study, to quantitatively determine the formation mechanism of this extremely high surface air temperature, particularly considering the contributions of the foehn and the foehnlike wind, observational data from Korea Meteorological Administration (KMA) and the Weather Research and Forecasting (WRF) model were utilized. In the backward trajectory analysis, trajectories of 100 air parcels were released from the surface over Hongcheon at 1600 LST on 1 August 2018. Among them, the 47 trajectories (38 trajectories) are tracked back above (below) heights of 1.4 km above mean sea level at 0900 LST 31 July 2018 and are defined as upper (lower) routes. Lagrangian energy budget analysis shows that for the upper routes, adiabatic heating (11.886 × 10³ J kg^-1) accounts for about 77% of the increase in the thermal energy transfer to the air parcels, while the rest (23%) is diabatic heating (3.650 × 10³ J kg^-1). On the other hand, for the lower routes, adiabatic heating (6.111 × 10³ J kg^-1) accounts for about 49% of the increase, the rest (51%) being diabatic heating (6.295 × 10³ J kg^-1). Even though the contribution of the diabatic heating to the increase in the air temperature rather varies according to the routes, the contribution of the diabatic heating should be considered. The diabatic heating is caused by direct heating associated with surface sensible heat flux and heating associated with the turbulent mixing. This mechanism is the Type 4 foehn described in Takane and Kusaka (2011). It is concluded that Type 4 foehn wind occurs and plays an important role in the extreme event on 1 August 2018.

• Atmosphere
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• v.32 no.3
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• pp.207-221
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• 2022

In Jeju, on January 23, 2016, a cold surge accompanied by heavy snowfall with the most significant amount of 12 cm was the highest record in 32 years. During this period, the temperature of 850 hPa in January was the lowest in 2016. Notably, in 2016, the average surface temperature of January on the Polar cap was the highest since 1991, and 500 hPa geopotential height also showed the highest value. With this condition, the polar vortex in the northern hemisphere meandered and expanded into the subtropics regionally, covering the Korean Peninsula with very high potential vorticity up to 7 Potential Vorticity Unit. As a result, the strong cold advection, mostly driven by a northerly wind, around the Korean Peninsula occurred at over 2𝜎. Previous studies have not addressed this extreme synoptic condition linked to polar vortex expansion due to the unprecedented Arctic warming. We suggest that the occurrence of a strong Ural blocking event after the abrupt warming of the Barents/Karas seas is a major cause of unusually strong cold advection. With a specified mesoscale model simulation with SST (Sea Surface Temperature), we also show that the warmer SST condition near the Korean Peninsula contributed to the heavy snowfall event on Jeju Island.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.101-108
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• 2017

Recently, the occurrence of landslides has been increasing over the years due to the extreme weather event. Developments of landslides monitoring technology that reduce damage caused by landslide are urgently needed. Therefore, in this study, a strain ratio sensor was developed to predict the ground behavior during the slope failure, and the change in surface ground displacement was observed as slope failed on the field model experiment. As a result, in the slope failure, the ground displacement process increases the risk of collapse as the inverse displacement approaches zero. It is closely related to the prediction of precursor. In all cases, increase in displacement and reverse speed of inverse displacement with time was observed during the slope failure, and it is very important event for monitoring collapse phenomenon of risky slopes. In the future, it can be used as disaster prevention technology to contribute in reduction of landslide damage and activation of measurement industry.

• Atmosphere
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• v.31 no.4
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• pp.433-443
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• 2021

The wind speed and wind direction in Yeongdong are one of the crucial meteorological factors for forecasting snowfall in this area. To improve the snowfall forecast in Yeongdong region, Yeongdong Extreme Snowfall-Windstorm Experiment, YES-WEX was designed. We examined the wind field variation simulated with Local Data Assimilation and Prediction System (LDAPS) using observed wind field during YES-WEX period. The simulated wind speed was overestimated over the East Sea and especially 2 to 4 times in the coastal line. The vertical wind in Yeongdong region, which is a crucial factor in the snowfall forecast, was not well simulated at the low level (850 hPa~1000 hPa) until 12 hours before the forecast. The snowfall distribution was also not accurately simulated. Three hours after the snowfall on the East Sea coast was observed, the snowfall was simulated. To improve the forecast accuracy of snowfall in Yeongdong region, it is important to understand the weather conditions using the observed and simulated data. In the future, data in the northern part of the East Sea and the mountain slope of Taebaek observed from the meteorological aircraft, ship, and drone would help in understanding the snowfall phenomenon and improving forecasts.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.279-283
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• 2008

국외를 중심으로 기존 GCM보다 해상도가 높은 Regional Climate Model(RCM)을 이용한 분석이 일부 시행되고 있으나, 국내에서는 이를 이용한 연구가 아직 미비한 실정이다. 이러한 관점에서 본 연구에서는 27km의 해상도를 갖는 기상청 RegCM3 RCM에서 도출된 기후변화 SRES 시나리오 자료를 이용하고자 한다. 수자원의 장기 거동을 강우-유출 모형으로 모사하기 위해서는 입력 자료인 일 강수자료 계열을 모의발생이 필요하며 본 연구에서는 천이확률 및 강수 모의에 이용되는 Gamma 확률분포와 같은 분포형의 매개변수들이 외부 인자 즉 기후변화 시나리오에 따라 조건부로 변동할 수 있는 CWGEN(Cross-validated Canonical Correlation Analysis-Weather Generator) 강수 모의기법을 도입하여 이용하였다. RCM 자료 그 자체는 일반적으로 시 공간적으로 왜곡되어 있어 Quantile Mapping을 통하여 수정을 하였다. 최종적으로 모의된 결과를 바탕으로 기후변화에 따른 극치사상들에 대한 정량적인 거동을 추정하고 평가하였다.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.