• 한국정보통신학회논문지
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• 제22권7호
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• pp.935-942
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• 2018

정확한 강수량의 측정은 댐 및 하천의 운영, 농어촌 및 산림녹화, 안전관리 등 사용분야가 광범위하며, 재난재해를 대비하고 강우발생시 경제적인 효과를 얻기 위해서 필요하다. 본 연구에서는 집수형 강수량계의 성능을 분석할 수 있는 통합검증시스템에 의한 강수량계 종류별 특성시험을 실시하였다. 전도형 강수량계는 0.0041 mm, 무게식 강수량계는 0.0045 mm, 표면장력식 강수량계는 0.0039 mm으로 불확도가 산출되었으며, 강수량계의 종류 및 특성에 따른 불확도는 크게 다르지 않음을 알 수 있었다. 이러한 특성시험을 통하여 강수량계 종류에 따른 기상관측 및 수문관측 데이터의 신뢰성을 확보하고자 하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.132-132
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• 2021

Access to accurate spatial precipitation in many hydrological studies is necessary. Existence of many mountains with diverse topography in South Korea causes different spatial distribution of precipitation. Rain gauge stations show accurate precipitation information in points, but due to the limited use of rain gauge stations and the difficulty of accessing them, there is not enough accurate information in the whole area. Weather radars can provide an integrated precipitation information spatially. Despite this, weather radar data have some errors that can not provide accurate data, especially in heavy rainfall. In this study, some location-based variable like aspect, elevation, plan curvature, profile curvature, slope and distance from the sea which has most effect on rainfall was considered. Then Automatic Weather Station data was used for spatial training of variables in each event. According to this, K-fold cross-validation method was combined with Adaptive Neuro-Fuzzy Inference System. Based on this, 80% of Automatic Weather Station data was used for training and validation of model and 20% was used for testing and evaluation of model. Finally, spatial distribution of precipitation for 1×1 km resolution in Gwangdeoksan radar station was estimates. The results showed a significant decrease in RMSE and an increase in correlation with the observed amount of precipitation.

• 한국수자원학회논문집
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• 제56권7호
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• pp.461-470
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• 2023

본 연구는 겨울철 적설 관측에 사용되는 전도형 강수량계 가열 시스템의 최적 온도, 위치, 제어 방식을 도출하기 위해 수행하였다. 수수구, 외부, 내부를 가변적으로 제어 가능한 전도형 강수량계를 제작하여 실내·외 실험을 수행하였다. 실내 실험은 강수량계 가열시스템의 성능비교와 적정온도를 도출하기 위해 항온항습챔버에서 수행되었다. 이후 다설지인 대관령에 위치한 구름물리선도센터에서 실외실험을 수행하여 실내실험 결과를 검증하였다. 분석 결과, 수수구의 가열 온도는 10~30℃, 내부 가열 온도는 70℃가 최적으로 확인되었다. 또한, 측정 지연을 최소화하기 위한 가열 장치의 최적 위치는 강수량계 외부, 수수구 테두리, 수수구 수직면으로 확인되었다. 본 연구 결과는 겨울철 고체 강수 측정을 위한 강수량계 가열 시스템의 운영 조건에 대한 기초자료로 활용이 가능할 것으로 판단된다.

• 한국정보통신학회논문지
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• 제24권9호
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• pp.1215-1223
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• 2020

최근 서울 경기를 비롯한 전국에서 국지성 집중호우, 태풍 등 악천후 관련 자연재해가 증가함에 따라 이에 대한 방재 및 물관리 대책이 필요한 실정이다. 이러한 수재해를 관측하기 위해 사용되는 우량계는 지상의 강우를 연속적·직접적으로 측정할 수 있는 장점이 있는 반면, 우량계 미설치 영역에 대한 공간적인 강우 분포를 정확하게 제공할 수 없다. 이러한 문제를 해결하고자 강수의 공간분포를 측정할 수 있는 전자파 기반 센서인 전파강수계(EWRG, Electromagnetic Wave Rain Gauge)를 개발하였다. 본 논문에서는 전파강수계의 FPGA 기반 신호처리 설계 방법을 제안한다. 전파강수계의 신호처리는 크게 LFM 파형의 ADC 및 DDC와 펄스압축, 상관 계수 및 강수 파라미터 산정으로 설계하였다. 본 연구를 통해 LFM 파형과 펄스압축 신호를 이론적으로 분석하였으며, 전파강수계 신호처리 설계를 위해서 FPGA 기반의 신호처리 설계 및 검증을 수행하였다.

• 지질공학
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• 제18권1호
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• pp.1-6
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• 2008

금강유역의 관측소로부터 수집된 강우자료와 지하수위자료를 분석하고 두 자료를 비교 분석하였다. 그리고 강우사상이 지하수위에 미치는 영향분석을 추계학적 기법인 이동평균법을 사용하여 지하수위와 강우이동평균값의 상관관계를 분석하였다. 지하수위는 강우의 계절적 분포를 대체로 따르며 대체로 12월 초부터 4월 말까지 낮은 지하수위를 형성한다. 7월과 8월의 풍수기에는 상대적으로 높은 지하수위를 형성한다. 선행강우를 고려하기 위한 강우이동평균값과 지하수위의 상관관계는 자료의 길이가 최소 2년 이상인 지하수위 관측소를 먼저 선정하였다. 강우와 지하수위 관측소 pair를 선정함에 있어 강우의 비균질한 분포를 고려해서 지하수위 관측소보다 상류에 인접한 강우관측소를 선정하여 두 자료를 분석하였다. 금강유역의 여러 관측소 자료를 분석한 결과 이동평균기간이 10일에서 150일 범위의 값을 가질 때 최대상관계수를 가졌다. 상관계수값은 자료의 질이나 결측기간 또는 융설이나 다른 요인에 의해 넓은 범위의 값을 가지는데 금강유역의 경우 최대 0.8886의 값을 가진다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1171-1173
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• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• 한국농공학회논문집
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• 제62권2호
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• pp.39-52
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• 2020

A high quality, long-term, high-resolution precipitation dataset is an essential in climate analyses and global water cycles. Rainfall data from station observations are inadequate over many parts of the world, especially North Korea, due to non-existent observation networks, or limited reporting of gauge observations. As a result, satellite-based rainfall estimates have been used as an alternative as a supplement to station observations. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and global coverage. CHIRPS is a global precipitation product and is made available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. In this study, we analyze the applicability of CHIRPS data on the Korean Peninsula by supplementing the lack of precipitation data of North Korea. We compared the daily precipitation estimates from CHIRPS with 81 rain gauges across Korea using several statistical metrics in the long-term period of 1981-2017. To summarize the results, the CHIRPS product for the Korean Peninsula was shown an acceptable performance when it is used for hydrological applications based on monthly rainfall amounts. Overall, this study concludes that CHIRPS can be a valuable complement to gauge precipitation data for estimating precipitation and climate, hydrological application, for example, drought monitoring in this region.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.358-360
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• 2002

In order to find horizontal and vertical precipitation structure in Korean peninsula, we use ground-based radar, and Automatic Weather Station (AWS) data. Radar data was selected for rain events in the Pusan and Jindo in Korea, during the spring and summer season of 2002. AWS point gauge measurements are analyzed as part of spatial structure of precipitation. TRMM/PR and ground-based radar is used vertical correlation. The results showed, as expected that the correlation decreased rapidly with distance.

• 대기
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• 제25권2호
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• pp.283-294
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• 2015

For urban flash flood simulation, we need the higher resolution radar rainfall than radar rainfall of KMA, which has 10 min time and 1km spatial resolution, because the area of subbasins is almost below $1km^2$. Moreover, we have to secure the high quantitative accuracy for considering the urban hydrological model that is sensitive to rainfall input. In this study, we developed the quantitative precipitation estimation (QPE), which has 250 m spatial resolution and high accuracy using KMA AWS and SK Planet stations with Mt. Gwangdeok radar data in Seoul area. As the results, the rainfall field using KMA AWS (QPE1) is showed high smoothing effect and the rainfall field using Mt. Gwangdeok radar is lower estimated than other rainfall fields. The rainfall field using KMA AWS and SK Planet (QPE2) and conditional merged rainfall field (QPE4) has high quantitative accuracy. In addition, they have small smoothed area and well displayed the spatial variation of rainfall distribution. In particular, the quantitative accuracy of QPE4 is slightly less than QPE2, but it has been simulated well the non-homogeneity of the spatial distribution of rainfall.

• 대기
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• 제24권3호
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.