The purpose of this study is to estimate rainfall around the district of Mt. Kumgang using several orographic factors where rainfall can not be measured routinely. Orographic factors used are height-reading, direction of main valley, relative relief, degree of exposure, and direction of maximum slope. The distribution of calculated rainfall around Mt. Kumgang coincides well with that of observed one and shows much rainfall in summer.

The characteristics of the anomaly level, variability and distribution of monthly mean precipitation have been investigated at 4 different weather stations on Cheju Island, Korea. The results of this study are as follows : 1) The SE area of Cheju Island turns out to be the heavy rain area from February to July than the NW area of the island. The heavy rain area migrates from the SE area to the NE area during the period from August to January. 2) The rainy season, in which monthly mean precipitation is more than 180mm, appears in Cheju City and Sungsan from June to August, in Seoguipo from April to August, and in Daejung from June to July. On the other hand, the dry season, in which monthly mean precipitation is less than 100㎜, appears in Cheju City from October to May, in Sungsan from December to February in Seoguipo from October to February, and in Daejung from October to March. 3) The variability of precipitation on Cheju Island appears high during the 'Changma' spell and it is also high in autumn, particularly in October, and appears low in March and April. 4) The frequency of the anomaly level shows maximum not only on the normal level but the lower normal level and the upper normal level in monthly precipitation. The annual frequency distribution of each anomaly level shows maximum on the normal level, and the frequency of the lower normal level is a lot higher than the lower normal level. 5) The precipitation of the summer season acts as an important variable in deciding between the dry year and the moisture year. In particular, this applies to the large precipition of June in the moisture year and the small precipitation of July and August in the dry year.

In order to determine the design precipitation, the most probable daily precipitation and annual precipitation at every spot are calculated and iso - precipitation line are drawn. Probability of precipitation and drought phenomena of each gage station are analyzied by the method of frequency analysis from the statistical conceptions. The results summarized in this study are as the follows. 1. Annual mean precipitation in kyungpook area are 1044 mm, about 115 mm less than annual mean precipitation of Korea amounts to l1S9mm, and found to regionally unequal. 2. Monthly mean rainfall of July is 242.2mm, 23.2%, August 174.2mm, 16.7%, June 115mm, 11% and September 114.2mm, 10.9% and Rainfall depth of July-August are more than 40% of annual precipition. This shows notable summer rainy weather by typoon and low pressure storm and seasonal unbalance of water supply. 3. The relation among the maximum precipi.tation per day, per two continuous days and per three contnous days are caculated and the latter is found 31.0% increased rate of the first and the last 48.2% increased rate of first. 4. Probability precipitation in Kyungpook area are shown as 9.0%(5 year), 13.3%(10 year), 17.7%(20 year), 23.1%(50 year), 27.0%(100 year) and 31.1%(200 year) increased rate of each recurrence year compared with observed average annual precipitation. 5. From annual precipitation and maximum daily rainfall data probability of precipitation and precipitation isohyetal line are derived which shown as Table 11 and Fig. 8. 6. Drought days are divided 6 class and analysed results are shown on table 12. Average occurrence time of 10-14 continuous drought days are 2.3 time per year, 15-19 days are 0.9 time per year, 20-24 days are one per six years, 30-34 days are once per nine years and over than 35days are once per 25 years.

This study evaluates the quality of surface air temperature, relative humidity, and precipitation detection observed by 22 internet of thing (IoT)-based mini-weather stations in Seoul in 2020 summer. The automatic weather station (AWS) closest to each IoT-based station is used as reference. The IoT-based observations show surface air temperature and relative humidity are about 0.2-4.0°C higher and about -1--22% lower than the AWS observations, respectively. However, they exhibit temporal variability similar to the AWS observations on both diurnal and daily time scales, with daily correlations greater than 0.90 for temperature and 0.82 for relative humidity. Given these strong linear relationships, it show that temperature and relative humidity biases can be effectively corrected by applying a simple bias correction method. For IoT-based precipitation detection, we found that precipitation conductivity value (PCV) during precipitation events is well separated from that during non-precipitation events, providing a basis for distinguishing precipitation events from non-precipitation events. When the PCV threshold is set to 250 for precipitation detection, the highest critical success index and the bias score index close to one, suitable for operational precipitation detection, are obtained. These results demonstrate that IoT-based mini-weather stations can successfully measure surface air temperature, relative humidity, and precipitation detection with appropriate bias corrections.

Moving average precipitation provides periodic precipitation patterns by solving precipitation irregularities. However, due to uncertain moving average periods, excessive data smoothing occurs, which limit the possibility to analyze groundwater levels in the short term. Nonetheless, groundwater level fluctuation can compensate these limitations as it can calculate appropriately for unit time and verify the effect of precipitation penetrated into groundwater in a short time period. In this study, the characteristics of groundwater level were evaluated using groundwater level fluctuation to compensate for limitations of groundwater level analysis using moving average precipitation. In addition, the groundwater quality was investigated using the electrical conductivity fluctuation. The study site was Hyogyo-ri, Yesan-si, Chungcheongnam-do. Four observation wells and an automated weather system were used. The correlation between groundwater level fluctuation and precipitation (Case 1) and the correlation between groundwater level and moving average precipitation (Case 3) were compared. In the analysis for 1 hour data, the correlation coefficient of Case 1 was higher than that of Case 3, and in the analysis for 1 day data, the correlation coefficient of Case 3 was higher than that of Case 1.

We examined the ocean forcing, associated with the different trends in precipitation between North and South Korea, using GPCC V2018 precipitation and OISST V2 sea surface temperature (SST) for the recent thirty years of 1982-2011. As a result of linear regression, the precipitation trends in the monsoon (June and July) and post-monsoon (August and September) seasons were different between North and South Korea, respectively, with increased and decreased trends, during the both monsoon seasons. During the monsoon season, the results of detrended correlation and composite analysis showed the opposite relationships of precipitation with SSTs in the equatorial Pacific and Arctic Oceans between North and South Korea. It was identified that large-scale atmospheric circulation linked to ENSO can differently affect the Korean Peninsula. On the other hand, during the post-monsoon season, the correlation and composite patterns across the oceans in the Northern Hemisphere were generally similar for the two Koreas. It was suggested that near the ocean of the Korean Peninsula and the land surface forcings might affect the precipitation variability during the post-monsoon season, especially in North Korea.

In this study, a high-resolution daily data set of surface weather were obtained from PRIDE(PRISMbased Dynamic downscaling Error correction) model for the period of 2000 to 2017 over South Korea. The simulation data of five RCM(Regional Climate Model) were also used which are forced by the CMIP6 participating model UK-ESM as the boundary condition under historical period (2000-2014) and SSP 5-8.5 period (2015- 2017). Here we compared the RCM data and the PRIDE data with MK-PRISM data in terms of ensemble mean and ensemble spread. Results show that the PRIDE model effectively eliminates systematic error in the RCM up to 63.0% for daily average temperature, 72.2% for daily maximum temperature, 68.2% for daily minimum temperature, and 28.7% for daily precipitation when evaluated from the RMSE perspective. Overall, the ensemble spread of the PRIDE model is significantly decreased from 1.46°C to 0.36°C for daily temperature and from 2.0 mm/day to 0.72 mm/day for daily precipitation compared to the RCM ensemble spread, indicating that the largest systematic error of the RCMs is effectively removed in the PRIDE model.

In this study, we analyzed the characteristics of climate variability in summer rainfall during Changma over three sub-sector regions (Middle, Southern, Jeju) in South Korea for the new climatological period of 1991- 2020 using observation data from 60 ASOS stations. There was a significant interannual variability in rainfall, wet days, and rainfall intensity but the long-term trend of rainfall was not significant over the three sectors in South Korea. Comparing the new climatology (P2: 1991-2020) with the old one (P1: 1981-2010), it was found that the precipitation during Changma in new climatology (P2) was enhanced in Middle sector but reduced in Southern and Jeju sectors. In P2, wet days increased only a few stations in the Middle sector but the rainfall intensity was strengthened over the 50% stations including Middle sector, south and west coast of the Southern sector. Wet days above 25, 50, 75, 95%ile rainfall during Changma in Southern and Jeju sectors all decreased in P2. Climatological change from P1 to P2 showed a large variability not only in temporal frame but also in the spatial distribution in South Korea.

Recently, a heavy rainfall with high spatial variation occurred frequently in the Korean Peninsula. The meteorological event that occurred in Busan on 3 May 2016 is characterized by heavy rain in a limited area. In order to clarify the reason of large spatial variation associated with mountain height and location of low level jet, several numerical experiments were carried out using the dynamic meteorological Weather Research and Forecasting (WRF) model. In this case study, the raised topography of Mount Geumjeong increased a barrier effect and air uplifting due to topographic forcing on the windward side. As a result, wind speed reduced and precipitation increased. In contrast, on the downwind side, the wind speed was slightly faster and since the total amount of water vapor is limited, the precipitation on the downwind side reduced. Numerical experiments on shifting the location of the lower jet demonstrated that if the lower jet is close to the mountain, its core becomes higher due to the effect of friction. Additionally, the water vapor convergence around the mountain increased and eventually the precipitation also increased in the area near the mountain. Hence, the location information of the lower jet is an important factor for accurately predicting precipitation.

가뭄재해는 다른 재해와 다르게 광범위한 공간에 걸쳐서 충분한 강우가 발생하기 전까지 오랜 기간 동안 발생되는 특성이 있다. 위성 영상은 시공간적으로 지속적인 강수량 관측을 제공할 수 있다. 본 연구는 위성 영상 기반의 강수자료를 활용하여 기상학적 가뭄 전망 모형을 개발하였다. PERSIANN_CDR, TRMM 3B42와 GPM IMERG 영상을 활용하여 강수 자료를 구축한 뒤, 표준강수지수(SPI)를 기반으로 기상학적 가뭄을 정의 하였다. 과거의 가뭄 정보와 물리적 예측 모형 기반의 가뭄 예측 결과를 결합할 수 있는 베이지안 네트워크 기반 가뭄 예측 기법을 이용하여 확률론적 가뭄 예측 결과를 생산하였으며, 가뭄 예측결과를 가뭄 전망 의사결정 모형에 적용하여 가뭄 전망 결과를 도출하였다. 가뭄 전망 정보는 가뭄 발생, 지속, 종결, 가뭄 없음의 4단계로 구분하였다. 본 연구의 가뭄 전망 결과는 ROC 분석을 통하여 물리적 예측 모형인 다중모형 앙상블(MME)을 활용한 가뭄 전망 결과와 전망 성능을 비교하였다. 그 결과, 2∼3개월 가뭄 전망에 대한 가뭄 발생 및 지속의 단계에서는 MME 모형보다 높은 전망 성능을 보여주었다.

In this study, daily precipitation data and daily average temperature data of meteorological observatories in Daegu, Busan, Daejeon, Seoul, Mokpo, and Gwangju cities inland and offshore were analyzed by using moving average method. Were compared. Overall, summarizing changes in precipitation and temperature over the 24 seasons, precipitation and temperature in all six stations increased compared to the past 1960s. In the case of precipitation, precipitation increased at the end of July and early August, whereas precipitation in April, September and early October decreased. In the case of temperature, especially in February, the temperature increased, and in Mokpo, the temperature from August to December showed a general decline. Changes in precipitation and temperature due to seasons in the 24 seasons affect agriculture and our everyday life, and further research is needed to determine how these changes will affect agricultural water supply, crop growth and daily life. The results of this study can be useful.

본 연구에서는 미급수지역의 주요 수원인 지하수의 수위 변동 상황을 기반으로 한 미급수지역 가뭄 예보 기법 개발을 목적으로 하였다. 이를 위해 지역화된 표준지하수지수(SGI)와 표준강수지수들(SPIs)의 상관관계를 분석하였다. 관측 지하수위로부터 산정된 SGI의 자기회귀 특성 및 지속기간별 SPI와 SGI의 상관관계를 동시에 고려할 수 있는 NARX (nonlinear autoregressive exogenous model) 인공신경망 모형을 이용하여 지역별 예측모형을 구축하였다. 학습기간 동안 관측 SGI와 모델 출력 SGI의 상관계수는 0.7 이상인 곳이 전체 167개 지역별 모형 중 146개(87%)로 상관성이 높은 것으로 분석되었다. 적용기간에 대해서는 평균제곱근오차와 상관계수로 모형을 평가하였다. 본 연구를 통해 기상청에서 제공하는 59 개 관측소별 강수량 전망 값으로부터 산정된 지속기간별 SPI와 관측된 지하수위를 이용한 지역별 SGI 전망이 가능하도록 하였으며, 미급수지역의 가뭄 예‧경보를 위한 기초자료로 활용이 가능토록 하였다.

본 연구에서는 표준강수지수를 이용하여 가뭄사상을 정의하고, 가뭄심도와 부족 강수량을 대상으로 이변량 가뭄빈도해석을 수행하였다. 부족강 수량은 표준강수지수의 가뭄기준인 -1에 해당하는 강수량을 기준으로 산정하였다. 지금까지 연구에서 가뭄지수의 심도와 지속기간 이용한 빈도해석을 통한 가뭄의 평가가 주를 이루었다. 하지만 이 두 변량은 선형적인 관계가 매우 높아 각 변량에 대한 단변량 빈도해석과 비교하여 정보의 확장성은 크지 않다. 2015년 가뭄의 경우, 서울, 양평, 충주지점의 ‘가뭄심도-부족 강수량’량의 재현기간은 모두 300년 이상의 극심한 가뭄을 나타내고 있지만, ‘가뭄심도-지속기간’에서는 재현기간을 약 10년, 50년, 50년으로 평가하여 큰 차이를 나타냈다. 우기를 포함한 가뭄은 강수량 부족이 심각할지라도 가뭄심도는 가뭄을 상대적으로 낮게 평가할 수 있어 실제 가뭄의 심각성을 나타내는데 한계가 있었다. ‘가뭄심도-부족 강수량’ 빈도해석 결과는 강수량의 절대적인 부족량 정보를 함께 포함하고 있어, 가뭄에 대응하기 위한 지표로 활용성이 높을 것으로 판단된다.

최근 이상기후로 인한 집중호우 발생빈도와 이로 인한 국지적인 홍수 피해가 증가하고 있다. 이러한 점에서 홍수피해 예방측면에서 수치예보 정보 활용이 요구되고 있다. 그러나 수치예보모델은 초기 조건 및 지형적 요인으로 인해 시공간적 편의가 존재하며 실시간 예측정보로 활용하기 전에 모 형결과에 대한 편의보정이 요구된다. 본 연구에서는 관측지점 기준으로 편의 보정계수를 산정하는 과정에서 모든 관측소간의 상관성을 거리의 함 수로 고려하여 미계측지점의 편의 보정계수를 공간적으로 확장할 수 있는 Bayesian Kriging 기반 MFBC 기법을 개발하였다. 본 연구에서 개발한 방법은 미계측 유역에 대해서도 보정계수를 효과적으로 추정하는 것이 확인되었으며, 비교적 고해상도로 72시간(3일) 정도까지 예측강우 정보를 활용하는 것이 가능할 것으로 판단된다.

This study investigates the simulation skills of RegCM4 for Diurnal Variations (DV) of temperature and precipitation over South Korea according to the Lateral Boundary Conditions (LBCs) using two sets of 30-yr (1981-2010) integration with two LBCs (RG4_HG2: HadGEM2-AO and RG4_ EH6: EHCAM6). In general, RegCM4 successfully reproduces the DV of temperature irrespective of LBCs and seasons. The DV of temperature is well captured in the coastal region compared to that over inland area irrespective of LBCs and season although the magnitude of DV is underestimated. However, it fails to simulate the early morning peak of precipitation irrespective of LBCs, in particular, for summer and autumn although it captures the late afternoon peak over the inland region. And the impacts of LBCs on the simulation skills of RegCM4 for the DV of precipitation are more prominent during summer than other seasons. As a result, the simulation skill of RG4_HG2 for the DV of temperature is better than RG4_ EH6, but the simulation skill for the DV of precipitation is opposite. In general, the impacts of LBCs on the simulation skills for the DV of temperature and precipitation of RegCM4 are different according to the season, time and geographic location.

최근 국지성 집중호우 및 급격한 기상변화로 인해 돌발홍수와 같은 기상재해의 발생빈도가 증가함에 따라 고해상도의 기상레이더 강수자료를 사용한 수공학 분야의 연구가 활발하게 진행되고 있다. 기상레이더 강수자료를 활용하는 목적은 기상레이더 강수자료가 제공하는 공간분포를 최대한 활용하는데 있다. 본 연구에서는 고해상도 기상레이더 강수자료의 공간적 특성을 유지하면서 지상 강수자료의 양적특성을 극대화할 수 있는 조건부 합성기법을 보간법에 따라 분석 하였다. 기상레이더 강수자료와 지상 강수자료를 조건부 합성하기 위하여 Kriging, 역거리 가중법 및 Spline 보간법을 적용하였다. 조건부 합성결과는 지상 강수패턴을 현실성 있게 재현하였으며 추가적으로 보간법에 적용되지 않은 강수자료와 모형검증을 수행한 결과 조건부 합성을 통하여 생산된 공간적 강수정보의 수문학적 활용이 가능할 것으로 판단된다.

We investigated on the proper combination of physical parameterization schemes of RegCM4.0 for the simulation of regional climate over CORDEX-East Asia Phase 2 domain. Based on the Lee(2016)’s sensitivity experiments for the four combination using two land surface schemes and two cumulus parameterization schemes during 5 years (1979-1983), we selected the two combinations (CE: CLM+Emanuel and BG: BATS+Grell). The ERA-Interim was used as lateral boundary data of RegCM4.0 for the two experiments during 25 years (1981-2005). Simulation skills of temperature were similar in the two combination of physical processes irrespective of seasons and locations. However, there were a substantial differences in the simulation skills of precipitation according to the combination of physical processes, which were better in CE than BG combination. In general, the CE combination better simulated the precipitation characteristics in July and August over South Korea than BG combination, in terms of frequency and amount of precipitation according to the intensity. The superior skills of CE in simulating precipitation over South Korea can be related to the better simulation of seasonal march of the East Asian summer monsoon including the location and intensity of the North Pacific high pressure system than BG. The results suggested that the CE combination can simulate the climate characteristics in the CORDEX East Asia Phase 2 region better than the BG combination.

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.

The disaster caused by the heavy rain results in the greatest damage Among the damages caused by the weather disaster. many previous researches actively analyzed heavy rainfall disasters. The work includes analyzing vulnerability of disaster using characteristics and size of disaster damage in local area, selecting influencing factors influencing disaster and analyzing its influence. Rainfall during the heavy rainfall disaster is concerned with regional vulnerability to rainfall. The disaster-induced rainfall averaged on scale was analyzed by classifying disaster damage scale. The damage per precipitation unit is assumed to be disaster vulnerability, and local vulnerability of disasters is analyzed and the tendency of disaster vulnerability is analyzed using a time series analysis. The total amount of rainfall during the disaster period was analyzed in a large amount of rainfall in the Seoul metropolitan area and Busan city. The analysis shows that The average rainfall per accident case is high, and the region with relatively high stability against heavy rainfall disaster is Seoul metropolitan city. Southwest regions of the Korean Peninsula are analyzed to be affected by a very small amount of precipitation. The damage analysis shows that Busan Metropolitan City and the metropolitan area are relatively safe area against disaster. The analysis of disaster vulnerability based on the precipitation during the heavy rainfall disaster provides a clear classification of vulnerability by region.

A statistical forecast model for early spring (March and April) precipitation over South Korea is developed by using multiple linear regression method. Predictors are selected among the forty five large-scale atmospheric and oceanic indices. Because the model is meant to use for real-time forecast, the predictors are chosen from the indices that have statistically significant lag correlation with observed early spring precipitation. The selected predictors of early spring precipitation are North Pacific Pattern with 6-month lead, Siberian High Index with 5-month lead and Indian Ocean Basin Mode Index with 3-month lead from March, and they are statistically independent. We applied leave-two-out cross validation. According to the regression map between these indices and synoptic circulations around Korean peninsula, these indices represent the induction of early spring rainfall by controlling East Asian jet and low level moisture flux. The regression coefficients for each training period show that three indices affects evenly at every forecast year and they show stable variability, indicating that the influence of each index does not depend on training period. The developed statistical model significantly predicted early spring precipitation over South Korea (r=0.63, p-value<0.01). Also it marks 61% of hit rate according to the three-category deterministic forecast.