• Journal of the Korean earth science society
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• v.26 no.7
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• pp.732-743
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• 2005

The characteristics of precipitation over South Korea from 1973 to 2002 were investigated. The synoptic patterns inducing precipitation are classified by 10 categories, according to the associated surface map analysis. The annual mean frequency of the total precipitation, its duration time and amount for 30 years are 179 times, 2.9 hours, and 7.1 mm, respectively. About $59\%$ of the total precipitation events were associated with a synoptic low. The dominant patterns are identified with respect to seasons: A synoptic mobile low pressure pattern is frequent in spring, fall, and winter, whereas low pressure embedded within the Changma and orography induced precipitation are dominant in summer and in winter. For the amount of precipitation, precipitation originated from tropical air associated with typhoon, tropical convergence, and Changma is more significant than that with other pressure patterns. The statistical elapse time reaching to 80 mm, which is the threshold amount of heavy rainfall watch at KMA, takes 12.9 hours after the onset of precipitation. The probability distribution function of the precipitation shows that the maximum probability for heavy rainfall is located at the south-coastal region of the Korean peninsula. It is also shown that the geographical distribution of the Korean peninsula plays an important role in occurrence of heavy rainfall. For example, heavy precipitation is frequently occurred at Youngdong area, when typhoon passes along the coastal region of the back borne mountains in the peninsula. The climatological classification of synoptic patterns associated with heavy rainfall over South Korea can be used to provide a guidance to operational forecast of heavy rainfall in KMA.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.63-72
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• 2018

The main function of an agricultural reservoir is to supply irrigation water to paddy rice fields in South Korea. Therefore, the operation of a reservoir is significantly affected by the phenology of paddy rice. For example, the early stage of irrigation season, a lot of irrigation water is required for transplanting rice. Therefore, water storage in the reservoir before irrigation season can be a key factor for sustainable irrigation, and it becomes more important under climate change situation. In this study, we analyzed the climate change impacts on reservoir storage rate at the beginning of irrigation period and simulated the reservoir storage, runoff, and irrigation water requirement under RCP scenarios. Frequency analysis was conducted with simulation results to analyze water supply probabilities of reservoirs. Water supply probability was lower in RCP 8.5 scenario than in RCP 4.5 scenario because of low precipitation in the non-irrigation period. Study reservoirs are classified into 5 groups by water supply probability. Reservoirs in group 5 showed more than 85 percentage probabilities to be filled up from half-filled condition during the non-irrigation period, whereas group 1 showed less than 5 percentages. In conclusion, reservoir capacity to catchment area ratio mainly affected water supply probability. If the ratio was high, reservoirs tended to have a low possibility to supply enough irrigation water amount.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.133-142
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• 2012

The objective of this study was to correct the bias of the Representative Concentration Pathways (RCP)-based future precipitation data using a quantile mapping method. This method was adopted to correct extreme values because it was designed to adjust simulated data using probability distribution function. The Generalized Extreme Value (GEV) distribution was used to fit distribution for precipitation data obtained from the Korea Meteorological Administration (KMA). The resolutions of precipitation data was 12.5 km in space and 3-hour in time. As the results of bias correction over the past 30 years (1976~2005), the annual precipitation was increased 16.3 % overall. And the results for 90 years (divided into 2011~2040, 2041~2070, 2071~2100) were that the future annual precipitation were increased 8.8 %, 9.6 %, 11.3 % respectively. It also had stronger correction effects on high value than low value. It was concluded that a quantile mapping appeared a good method of correcting extreme value.

• Journal of Wetlands Research
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• v.12 no.2
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• pp.13-23
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• 2010

According to recent researches on climate change, the global warming is obvious to increase rainfall intensity. Damage caused by extreme hydrologic events due to global change is steadily getting bigger and bigger. Recently, frequently occurring heavy rainfalls surely affect the trend of rainfall observations. Probability precipitation estimation method used in designing and planning hydrological resources assumes that rainfall data is stationary. The stationary probability precipitation estimation method could be very weak to abnormal rainfalls occurred by climate change, because stationary probability precipitation estimation method cannot reflect increasing trend of rainfall intensity. This study analyzed temporal variation of trend in rainfall time series at 51 stations which are not significant for statistical trend tests. After modeling rainfall time series with maintaining observed statistical characteristics, this study also estimated whether rainfall data is significant for the statistical trend test in near future. It was found that 13 stations among sample stations will have trend within 10 years. The results indicate that non-stationary probability precipitation estimation method must be applied to sufficiently consider increase trend of rainfall.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.87-98
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• 2022

In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

• Water for future
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• v.14 no.4
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• pp.53-72
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• 1981

In this study, South Korea is divided into 5 zones and is studied about the analysis of time-regional distribution of previpitation frequency and rainfall intensity in Korea. In the previpitation frequency analysis, the basic data groups of 39 stations were selected. The diagram of previpitation frequency was drawn, and the time-regional distribution of precipitation frequency was analized. In the rainfall intensity analysis, the basic data groups of 36 stations were selected. The probable rainfall, I-D-F curve, and regression equation between 24hr. and 10min.-18hr. areal depth were obtained. The results of this study are following; 1) The precipitation class of max. recurrence probability in every season except summer was commonly (1) 1-5mm, (2) 0.1-1mm, (3) 5-10mm in order. 2) The zone of max. recurrence frequency owing to the precipitation class was zone II in precipitation frequency of below 20mm, zone IV in precipitation frequency of 30-40mm, zone I in precipitation frequency of above 70mm for a year. 3) The recurrence probability of precipitation in Korea can be represented to the equation of exponential function; $$W(x)=e^{\alpha+\beta}$$ 4) The first and third zones were expected heavy rain for the short and long duration. 5) The I.D.F. curves were drawn, and established that the time interval for the least deviation of I.D.F curve is 10~40min., 40min. -4hr., 4~24hr. 6) The regression equations of areal mean depth between 24hr. and 10min.-18hr. for each zone were obtained. 7)The probable rainfall of 36 points were calculated.

• Journal of Korea Water Resources Association
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• v.32 no.1
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• pp.3-13
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• 1999

In this study, an alternative spatial analysis method against conventional methods such as Thiessen method, Inverse Distance method, and Kriging method, named Spatial-Analysis Neural-Network (SANN) is presented. It is based on neural network modeling and provides a nonparametric mean estimator and also estimators of high order statistics such as standard deviation and skewness. In addition, it provides a decision-making tool including an estimator of posterior probability that a spatial variable at a given point will belong to various classes representing the severity of the problem of interest and a Bayesian classifier to define the boundaries of subregions belonging to the classes. In this paper, the SANN is implemented to be used for analyzing a mean annual precipitation filed and classifying the field into dry, normal, and wet subregions. For an example, the whole area of South Korea with 39 precipitation sites is applied. Then, several useful results related with the spatial variability of mean annual precipitation on South Korea were obtained such as interpolated field, standard deviation field, and probability maps. In addition, the whole South Korea was classified with dry, normal, and wet regions.

• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.889-902
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• 2011

In this study, frequency analysis using drought index had implemented for the derivation of drought severity-duration-frequency (SDF) curves to enable quantitative evaluations of past historical droughts having been occurred in Korean Peninsular. Seoul, Daejeon, Daegu, Gwangju, and Busan weather stations were selected and precipitation data during 1974~2010 (37 years) was used for the calculation of Standardized Precipitation Index (SPI) and frequency analysis. Based on the results of goodness of fit test on the probability distribution, Generalized Extreme Value (GEV) was selected as most suitable probability distribution for the drought frequency analysis using SPI. This study can suggest return periods for historical major drought events by using newrly derived SDF curves for each stations. In case of 1994~1995 droughts which had focused on southern part of Korea. SDF curves of Gwangju weather station showed 50~100 years of return period and Busan station showed 100~200 years of return period. Besides, in case of 1988~1989 droughts, SDF of Seoul weather station were appeared as having return periods of 300 years.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.101-110
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• 2017

The National Emergency Management Agency (NEMA) presented the disaster prevention performance target rainfall (DPPTR) for disaster prevention. The estimation criteria for DPPTR is a 10 year cycle. On the other hand, the target rainfall recalculated every 10 years is difficult to reflect the current change in rainfall on climate change. In this study, the probability of precipitation using the recent rainfall data was prepared and the weights according to socio-economic criteria reflecting the urban characteristics and adjusted probability rainfall criteria were applied to the results. The difference between the existing target rainfall and recalculated result was compared. The input data for the estimated probability rainfall was selected from 6 points located in the rainfall observing station of Chungcheongnam-do, Daejeon region. As a result of the estimation, in the case of upward probability precipitation weight, some similar areas were observed. On the other hand, there were a few cases of upward or downward changes within 10 mm. Considering the rainfall variability and uncertainty due to climate change, the existing target rainfall does not present the condition properly. Therefore, hydrological designers need to calculate the target rainfall, reflecting the present condition.

• Atmosphere
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• v.16 no.2
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• pp.125-139
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• 2006

Precipitation forecasts from MM5 have been verified for the period 1989-2001 over Yeongdong region to show a tendency of model forecast. We select 57 events which are related with the heavy snowfall in Yeongdong region. They are classified into three precipitation types; mountain type, cold-coastal type, and warm type. The threat score (TS), the probability of detection (POD), and the false-alarm rate (FAR) are computed for categorical verification and the mean squared error (MSE) is also computed for scalar accuracy measures. In the case of POD, warm, mountain, and cold-coastal precipitation type are 0.71, 0.69, and 0.55 in turn, respectively. In aspect of quantitative verification, mountain and cold-coastal type are relatively well matched between forecasts and observations, while for warm type MM5 tends to overestimate precipitation. There are 12 events for the POD below 0.2, mountain, cold-coastal, warm type are 2, 7, 3 events, respectively. Most of their precipitation are distributed over the East Sea nearby Yeongdong region. These events are also shown when there are no or very weak easterlies in the lower troposphere. Even in the case that we use high resolution sea surface temperature (about 18 km) for the boundary condition, there are not much changes in the wind direction to compare that with low resolution sea surface temperature (about 100 km).