• 한국지리정보학회지
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• 제20권3호
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• pp.141-152
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• 2017

본 연구는 계측자료가 부족한 유역을 대상으로 위성강우 활용 및 위성강우의 보정방법을 통해 홍수량 추정의 기술적인 방법을 제시하는 것을 목적으로 하였다. 연구대상유역은 모로코 세부강 유역을 대상으로 하였다. 세부강 유역 홍수량 추정을 위한 모형은 IFAS(Integrated Flood Analysis System)와 GRM(Grid baed Rainfall-Runoff Model)을 이용하였다. 연구 유역에 대한 강우자료는 일일관측의 지상계측 자료와 시간계측 위성강우자료를 이용하였다. 위성강우를 이용한 홍수분석에서 일일 지상계측 강우량과 위성강우의 시간계측 자료를 합성하여 위성강우자료를 수정하였다. 지형자료는 90m 공간해상도의 Shuttle Radar Topographic Mission DEM(SRTM DEM)과, 1km 공간해상도의 Global map의 토지피복도와 US Food and Agriculture Organization(US FAO)의 Harmonized World Soil Database(HWSD) 토양도를 이용하였다. 과소추정되는 위성강우는 지상계측 자료를 활용하여 보정하였다. 수정된 위성강우를 이용한 유출분석에서는 첨두유출량이 IFAS는 $5,878{\sim}7,434m^3/s$, GRM은 $6,140{\sim}7,437m^3/s$의 유출이 발생하는 것으로 분석되었다. 그러므로 2009~2010년에 발생한 세부강 유역의 첨두홍수량은 $5,800m^3/s$에서 $7,500m^3/s$의 범위에서 발생한 것으로 추정되었다. 보정된 위성강우를 활용한 홍수량 추정결과는 두 모형 모두 유사한 홍수량을 나타내었다. 따라서 본 연구에서 제시한 위성강우의 보정기법은 계측자료가 부족한 지역의 적정 홍수량 추정에 적용될 수 있을 것으로 사료된다.

• 대기
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• 제20권2호
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• pp.131-151
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• 2010

This study establishes a conceptual model to analyze heavy rainfall events in Korea using multi-functional transport satellite-1R satellite images. Three heavy rainfall episodes in two major synoptic types, such as synoptic low (SL) type and synoptic flow convergence (SC) type, are analyzed through a conceptual model procedure which proceeds on two steps: 1) conveyer belt model analysis to detect convective area, and 2) cloud top temperature analysis from black body temperature (TBB) data to distinguish convective cloud from stratiform cloud, and eventually estimate heavy rainfall area and intensity. Major synoptic patterns causing heavy rainfall are Changma, synoptic low approach, upper level low in the SL type, and upper level low, indirect effect of typhoon, convergence of tropical air in the SC type. The relationship between rainfall and TBBs in overall well resolved areas of heavy rainfall. The SC type tended to underestimate the intensity of heavy rainfall, but the analysis with the use of water vapor channel has improved the performance. The conceptual model improved a concrete utilization of images and data of satellite, as summarizing characteristics of major synoptic type causing heavy rainfall and composing an algorism to assess the area and intensity of heavy rainfall. The further assessment with various cases is required for the operational use.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.188-188
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• 2017

Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 춘계학술대회 논문집
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• pp.117-120
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• 2006

Heavy rainfall events are occurred exceedingly various forms by a complex interaction between synoptic, dynamic and atmospheric stability. As the results, quantitative precipitation forecast is extraordinary difficult because it happens locally in a short time and has a strong spatial and temporal variations. GOES-9 imagery data provides continuous observations of the clouds in time and space at the right resolution. In this study, an power-law type algorithm(KAE: Korea auto estimator) for estimating rainfall based on the rainfall type was developed using geostationary meteorological satellite data. GOES-9 imagery and automatic weather station(AWS) measurements data were used for the classification of rainfall types and the development of estimation algorithm. Subjective and objective classification of rainfall types using GOES-9 imagery data and AWS measurements data showed that most of heavy rainfalls are occurred by the convective and mired type. Statistical analysis between AWS rainfall and GOES-IR data according to the rainfall types showed that estimation of rainfall amount using satellite data could be possible only for the convective and mixed type rainfall. The quality of KAE in estimating the rainfall amount and rainfall area is similar or slightly superior to the National Environmental Satellite Data and Information Service's auto-estimator(NESDIS AE), especially for the multi cell convective and mixed type heavy rainfalls. Also the high estimated level is denoted on the mature stage as well as decaying stages of rainfall system.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.660-663
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• 2006

Rainfall estimation is important to weather forecast, flood control, hydrological plan. The empirical and statistical methods by measured data(surface rain gauge, rainfall radar, Satellite) is commonly used for rainfall estimation. In this study, the rainfall intensity for East Asia region was estimated using the empirical relationship between SSM/I data of DMSP satellite and brightness temperature of GEOS-9(10.7${\mu}m$) with cloud types(ISCCP and MSG classification). And the empirical formula for rainfall estimation was produced by PMM (Probability Matching Method).

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2013년도 추계학술대회
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• pp.46-47
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• 2013

In the satellite system design, the processes from the initial design to launch take about 5 years and the broadcasting satellite lifetime goes over 15 years. Furthermore, global warming phenomenon causes rainfall rate increasing more and more in some regions on the earth. Consequently, at the stage of the satellite link design, we need to consider the future rain attenuation over 20 years. In this paper, we investigated two time-series system models for forecasting to consider the future rainfall rate for the satellite broadcasting service. We found that rainfall rate of the future 30 years is increasing continuously.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.28-35
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• 2006

Global Flood Alert System (GFAS) is an attempt to make the best use of satellite rainfall data in flood forecasting. The project of GFAS is promoted both by Ministry of Land, Infrastructure and Transport-Japan (MLIT) and Japan Aerospace Exploration Agency (JAXA), under which Infrastructure Development Institute-Japan (IDI) has been working on the development of Internet-based information system and just launched trial run of GFAS in April 2006 on International Flood Network (IFNet) website. The function of GFAS is to connect space agencies and hydrological services/river authorities in charge of flood forecasting and warning by providing global rainfall information in maps, text data e-mails and so on which is produced from binary global rainfall data downloaded from National Aeronautics and Space Administration (NASA) website. Although the effectiveness of satellite rainfall data in flood forecasting and warning has yet to be verified, satellite rainfall is expected to play an important role to strengthen existing flood forecasting systems by diversifying hydrological data source.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.53-56
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• 2014

위성시스템설계에서는 설계과정이 초기 설계부터 위성발사까지 약 5년 정도 소요되며, 방송위성수명은 15년 이상까지 될 수 있다. 지구의 온난화 현상은 장기적으로 지구상의 강우율을 점점 증가시키는 추세이다. 이러한 강우율 변화를 포용하기 위해서는 위성링크 설계단계에서 20년 후의 강우감쇠까지 고려하여야 한다. 이 논문에서는 위성방송서비스를 위한 미래의 강우율을 고려하기 위해서 예측용 시계열 시스템 모델을 연구하였다. 이 연구를 통하여 미래 20년 동안의 강우율은 지속적으로 증가할 수 있다는 것을 밝혔다.

• 한국위성정보통신학회논문지
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• 제11권3호
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• pp.110-113
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• 2016

정지궤도 위성을 이용한 Ka대역 위성통신은 강우에 가장 취약하다. 이렇게 강우감쇠에 취약한 위성통신 링크 설계 시 좀 더 확실한 지역 강우분포와 정확한 강우감쇠 예측모델을 이용하여 계산된 강우 감쇠값을 반영하여 위성통신망의 링크버짓을 분석하여야 한다. 따라서 본 논문에서는 최근 TTA에서 분석한 국내 지역별 강우강도 분포를 활용하여 Crane 강우감쇠 예측의 지역별 강우강도와 국내 지역별 강우강도 분포를 활용하여 해당 지역의 강우감쇠를 Ka대역 주파수 특성에 맞는 Crane 강우감쇠 예측 모델을 통해 정지궤도 위성과 지상 송수신국간의 위치, 거리 및 연 시간율(%) 요인을 반영하여 분석하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.930-933
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• 2006

A new algorithm for satellite microwave rainfall retrievals over the land of Taiwan using TMI (TRMM Microwave Imager) data on board TRMM (Tropical Rainfall Measuring Mission) satellite is described in this study. The scattering index method (Grody, 1991) was accepted to develop a rainfall estimation algorithm and the measurements from Automatic Rainfall and Meteorological Telemetry System (ARMTS) were employed to evaluate the satellite rainfall retrievals. Based on the standard products of 2A25 derived from TRMM/PR data, the rainfall areas over Taiwan were divided into convective rainfall area and stratiform rainfall areas with/without bright band. The results of rainfall estimation from the division of rain type are compared with those without the division of rain type. It is shown that the mean rainfall difference for the convective rain type is reduced from -6.2mm/hr to 1.7mm/hr and for the stratiform rain type with bright band is decreased from 10.7 mm/hr to 2.1mm/hr. But it seems not significant improvement for the stratiform rain type without bright band.