• 대기
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• 제28권1호
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• pp.85-97
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• 2018

This study evaluates the performance of the Weather Research and Forecasting (WRF) model in reproducing the present-day (1981~2005) precipitation over Far East Asia and South Korea. The WRF model is configured with 25-km horizontal resolution within the context of the COordinated Regional climate Downscaling Experiment (CORDEX) - East Asia Phase 2. The initial and lateral boundary forcing for the WRF simulation are derived from European Centre for Medium-Range Weather Forecast Interim reanalysis. According to our results, WRF model shows a reasonable performance to reproduce the features of precipitation, such as seasonal climatology, annual and inter-annual variabilities, seasonal march of monsoon rainfall and extreme precipitation. In spite of such model's ability to simulate major features of precipitation, systematic biases are found in the downscaled simulation in some sub-regions and seasons. In particular, the WRF model systematically tends to overestimate (underestimate) precipitation over Far East Asia (South Korea), and relatively large biases are evident during the summer season. In terms of inter-annual variability, WRF shows an overall smaller (larger) standard deviation in the Far East Asia (South Korea) compared to observation. In addition, WRF overestimates the frequency and amount of weak precipitation, but underestimates those of heavy precipitation. Also, the number of wet days, the precipitation intensity above the 95 percentile, and consecutive wet days (consecutive dry days) are overestimated (underestimated) over eastern (western) part of South Korea. The results of this study can be used as reference data when providing information about projections of fine-scale climate change over East Asia.

• 한국방재학회 논문집
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• 제9권6호
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• pp.99-109
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• 2009

본 연구에서는 강원도내 정확한 극치강수분포를 파악하여 최근 증가하고 있는 재해를 예방하고자 지역빈도해석 방법을 이용하여 산정한 확률강수량과 공간분석을 통하여 강원도의 강수분포를 분석하였다. 강수자료는 강원도내 기상청 관할의 66개 관측소의 자료를 사용하였다. 지역빈도해석결과 GLO 분포형이 강원도에 가장 적합한 분포형으로 나타났다. 강수분포를 지속기간별로 분석한 결과 지속기간이 증가할수록 설악동, 대관령 및 청일 일원에서 높은 확률강수량을 나타내었으며, 지속기간에 따라서 강수의 공간분포가 확연히 변화됨을 확인하였다. 또한 재현기간별로 분석한 결과 재현기간이 길어질수록 지역별 강수 특성이 강하게 나타났다. 강원도 강수분포를 공간분석한 결과 영동지방에서는 일관적으로 높은 강수량이 발생하였으나 영서지방에서는 지속기간 및 재현기간에 따라 다양한 분포를 나타내었다. 따라서 지역별 강수량의 보다 정확한 예측을 위해서는 지역빈도해석 이외에 다양한 지리 및 기상조건을 고려할 수 있는 모형에 대한 연구가 필요할 것으로 판단된다.

• 대한지리학회지
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• 제43권3호
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• pp.324-336
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• 2008

본 연구에서는 최근의 한반도 여름철 강수특성을 파악하기 위해 장기간($1958{\sim}2007$년) 관측을 수행하고 있는 기상관측소를 대상으로 강수량의 변화 경향을 시 공간적으로 분석하였다. 여름철($6{\sim}9$월) 강수량의 연변화를 분석하고 여름철을 장마와 장마 후 강수기간으로 구분하여 그 특징을 살펴보았다. 장마기간에는 남서풍과 준정체전선의 영향으로 산악지역의 풍상측에서 최대 강수량이 발생하였으며 장마 후 강수기간에는 한반도 주변의 서쪽 및 남동쪽에서 유입되는 하층순환장과 함께 태풍, 대류불안정, 저기압성 강수에 의해 주로 남해안과 영동 산간 및 해안지방에서 최대 강수량이 나타났다. 여름철($6{\sim}9$월) 강수량의 시계열 변화에서는 모든 지점에서 강수량이 증가하는 경향을 보여주었으며 이 중에서도 최근 10년이 가장 큰 증가 경향을 보였다. 일 강수량을 10년 단위로 평균하여 분석한 결과, 모든 지점에서 최근 10년에 장마 및 장마 후 강수기간의 강수량이 가장 크게 증가하는 것으로 나타났다. 지점별로 증가 경향은 차이를 보여주었는데, 강릉은 장마 후 강수기간의 강수량이 장마기간보다 더 많았으며 최근 들어 장마 후 강수기간의 강수량이 가장 크게 증가하였다. 서울과 부산의 경우는 최근 10년 동안 여름철 강수량의 두 개 최대값 사이의 강수량이 크게 증가하는 경향을 보여주었다.

• 대한원격탐사학회지
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• 제29권2호
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• pp.263-274
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• 2013

본 연구에서는 다중위성 강수자료의 수문학적 적용성을 평가하기 위하여 Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Global Satellite Mapping of Precipitation (GSMaP), Climate Prediction Center (CPC) Morphing technique(CMORPH) 등 전 지구 규모의 고해상도 다중위성 강수자료와 분포형 수문모형을 이용하여 유출모의를 수행하였다. 충주댐 유역에 대하여 2002년 1월 1일부터 2009년 12월 31일까지의 기간에 대하여 Coupled Routing and Excess Storage (CREST) 모형을 적용하였다. 분석기간은 준비기간(2002-2003년, 2006-2007년), 보정기간(2004-2005년), 그리고 검증기간(2008-2009년)으로 구분하여 모의를 수행하였다. 각 다중위성 강수자료를 지상관측자료와 비교결과, 강수의 계절적 변동특성은 잘 반영하고 있으나 연강수량합계 및 월평균강수량에서 TMPA는 과대추정을, GSMaP과 CMORPH는 과소추정하는 경향을 보여주었다. 또한 유출분석결과, TMPA를 제외한 GSMaP과 CMORPH의 충주댐 유역에 대한 수문학적 적용성이 매우 낮은 것을 알 수 있었으며, 향후 다중위성 강수자료의 활용에 앞서 통계적 보정이나 강수알고리즘에 대한 개선이 필요한 것으로 판단된다.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2004년도 임시총회 및 추계학술발표회
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• pp.147-150
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• 2004

수자원을 평가하기 위해서는 먼저 한 지점에서 측정된 강수량을 보간해야 할 필요가 있다. 이를 위하여 강수현상에 영향을 주는 지형변수를 TOVA(Topographic Variables Extraction Program)를 이용하여 고도(ELEV), 경사(SLOPE), 바다까지의 거리(SEA), 방해물(OBST), 방벽(BAR), 굴곡도(SHIELD)로 구분하고 2000.1.1부터 2002.12.31까지의 강수량 자료를 사상별로 추출하여 이들을 서로 비교 분석하였다. 결정계수로 보면 각기 강수사상마다 지형의 영향이 다르게 나타나며 ELEV와 남서방향의 SLOPE, OBST 그리고 전 방향의 SHIELD가 강수량과 관계가 깊은 것으로 나타났다. 다중회귀분석 모형은 강수량의 공간적 변동량의 96%를 설명한다.

• 한국농공학회지
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• 제12권4호
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• pp.2063-2077
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• 1970

The Purpose of this study is to give the hydrologically basic data for the development of water resources in Korea and a quantity of daily average precipitation and its frequency in a year are investigated to study the presumption which is affected to river flow. Characteristics of precipitation is poor as source of water resources compared with its efficiency. So, because of such characteristics of precipitation, river flow also is in harmony and distribution of river flow comes to the result of irregularity, that is, range of river coefficiet between the quantity of maximum river flow and others river flow is big, and it is insufficient as source of water resources. Yearly river flow being expressed by daily unit indicates the ratio(%) of distribution to total yearly river flow, and the model of hydrograph is drawn up. The gives the basis to make yearly water balance sheet. This study is not completed, yet but in forth-coming days, the water will try continuously to give more correct basis for the development of water resources according to a great deal of data.

• 한국농공학회논문집
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• 제63권6호
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• pp.49-60
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• 2021

BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.

• 한국멀티미디어학회논문지
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• 제22권5호
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• pp.588-600
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• 2019

Each year Malaria affects over 200 million people worldwide. Particularly, African continent is highly hit by this disease. According to many researches, this continent is ideal for Anopheles mosquitoes which transmit Malaria parasites to thrive. Rainfall volume is one of the major factor favoring the development of these Anopheles in the tropical Sub-Sahara Africa (SSA). However, the surveillance, monitoring and reporting of this epidemic is still poor and bureaucratic only. In our paper, we proposed a method to fast monitor and report Malaria instances by using Social Network Systems (SNS) and precipitation volume in Nigeria. We used Twitter search Application Programming Interface (API) to live-stream Twitter messages mentioning Malaria, preprocessed those Tweets and classified them into Malaria cases in Nigeria by using Support Vector Machine (SVM) classification algorithm and compared those Malaria cases with average precipitation volume. The comparison yielded a correlation of 0.75 between Malaria cases recorded by using Twitter and average precipitations in Nigeria. To ensure the certainty of our classification algorithm, we used an oversampling technique and eliminated the imbalance in our training Tweets.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• 한국농공학회논문집
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• 제64권3호
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• pp.75-83
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• 2022

Recent settlements and sinkhole openings in urban areas have caused social problems such as damage to roads and structures, fear of the public, and loss of property. Several studies have demonstrated that surface subsidence and sinkhole opening are greatly affected by rainfall and rainfall intensity in urban areas. In this paper, we analyzed the relationship with the characteristics of recorded rainfall data using the ground subsidence database reported in major cities. The correlations were found using sedimentation and precipitation data from 2010 to 2014. The duration and intensity of a given precipitation have evolved to obtain an effect on ground sedimentation rate (SR). The results show that the relationship between SR and precipitation is asymptotic and can be modeled by a hyperbolic equation. Through this study, it is possible to predict the occurrence of ground subsidence due to precipitation in advance.