• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.55-64
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• 2000

The Tropical Rainfall Measuring Mission(TRMM) Satellite was launched in November 1997, carving into orbit the first space-borne Precipitation Radar(PR). The main objective of the TRMM is to obtain and study multi-year science data sets of tropical and subtropical rainfall measurements. In the present investigation, the characteristics of heavy rainfall cases over Korea in 1998 and 1999 are analyzed using the TRMM/PR dat3. We compare the rainrate measured from TRMM/PR with the accumulated rainfall data for 10 minutes tv Automatic Weather System(AWS). Especially, horizontal cross-section of rainrate with height and longitude in the precipitating clouds are investigated. As a result of the comparison with GMS-5 IR1, the TRMM/PR data delineate well the rain type( i.e. convective, stratiform cloud and others), height of storm top and instantaneous rainrate in the precipitating clouds. The vertical structure with height and horizontal cross-section of rainrate along the longitude show the orographic effect on the rainfall. TRMM/PR instrument measures the rainrate below 6 ㎜/hr more than AWS rainguages and inclined to underestimate the rainrate than rainguages for the whole area.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.103-106
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• 1999

The Tropical Rainfall Measuring Mission(TRMM) is a United States-Japan project for rain measurement from space. The first spaceborne Precipitation Radar(PR) has been installed aboard the TRMM satellite. The ground based validation of the TRMM satellite observations was conducted by TRMM science team through a Global Validation Program(GVP) consisted of 10 or more ground validation sites throughout the tropics. However, TRMM radar should always be validated and assessed against reference data to be used in Korean Peninsula because the rainrates measured with satellite varies by time and space. We have analyzed errors in the comparison of rainrates measured with the TRMM/PR and the ground-based instrument i.e. Automatic Weather System(AWS) by means of statistical methods. Preliminary results show that the near surface rainrate of TRMM/PR are highly correlated with ground measurements especially for the very deep convective rain clouds, though the correlation is changed according to the type and amount of precipitating clouds. Results also show that TRMM/PR instrument is inclined to underestimate the rainrate on the whole over Korea than the AWS measurement for the cases of heavy rainfall.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.47-53
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• 2002

Ocean surface wind speed was estimated using TRMM (Tropical Rainfall Measurement Mission) TMI (TRMM Microwave/Imager) data. It is used the TRMM TMI brightness temperature and National Data Buoy Center's buoy winds speed dataset near North-America to estimate by the algorithm of the ocean surface wind speed retrieval over North America. Comparing with the buoy data by D-matrix equation, the result that RMSE, BIAS, and correlation coefficient are 2.19 $ms^{-1}$, 1.10 $ms^{-1}$, and 0.81, respectively. Therefore the estimated oceanic surface wind speed by TRMM TMI brightness temperature data show that available to ocean research over upper ocean.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.1-8
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• 2002

Comparison between the Tropical Rainfall Measuring Mission(TRMM)/Precipitation Radar(PR) and the C-band doppler radar at Cheju, Kunsan and Pusan, operated by the Korean Meteorological Administration (KMA), is conducted for validation of the surface precipitation structure, and for calibration of KMA radar instrument. Data used in validation was selected for seven rain events in the south region of about $36^{\circ}N$ and at TRMM overflight in Korea, during the summer season of 2000. Quantitatively comparing radar reflectivities from two different platforms that have different view angles, bandwidths and frequencies is a challenging task. For the comparison, the precipitation patterns are projected on the same area for TRMM PR. Through the comparison, it is realized that the reflectivity from ground-based radar is under estimated, compared to TRMM/PR observations. We discuss that is underestimation may be produced by many factors(system performance, topography, etc).

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.647-659
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• 2003

The purpose of this study is to evaluate hydrological applicability of spatially observed rainfall distribution data by the TRMM/PR (Tropical Rainfall Measuring Mission / Precipitation Radar). For this study, firstly, TRMM/PR data (Y) of the Yongdam-Dam Watershed (930.38$km^2$) was extracted and secondly, TRMM/PR data and the rainfall data (X) by AWS (Automatic Weather Station) were compared by executing a correlation analysis. As a result, the regression equations were deduced as two parts (under 60mm/day : Y = 18.55X-0.53, over 60mm/day : Y = 3.11X+51.16). SCS runoff analysis was conducted using 7 rainfall events in 1999 for Yongdam-Dam watershed and the Cheon-Cheon subwatershed for the revised TRMM/PR data. TRMM/PR data showed relative errors ranging from 19.6％ ti 45.6％, and from 11.3％ to 38.9％ for Cheon-Cheon subwatershed and Yongdam-Dam watershed, respectively, AWS data showed relative errors ranging from 0.5％ to 12.8％, and from -1.6％ to -10.3％, for Cheon-Cheon subwatershed and Yongdam-Dam watershed, respectively. Futher researches are necessary to evaluate the relationship between TRMM/PR data and AWS data for practical hydrological applications.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.319-326
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• 2002

Rainfall estimation was conducted based on TRMM-PR/VIES and GMS data. AWS rainfall data were used for various validation. General procedure is as follows; 1) Z-R relationship was made by the comparison of TRMM-PR and AWS data. 2) new algorithm was developed by the estimates from Z-R equation and TBB of VIRS. 3) rainfall was estimated through the substitution of GMS data for TBB of VIRS in the newly developed algorithm. Z-R relationship based on TRMM is $Z=303R^{0.72}$ with correlation coefficient 0.57. The newly developed algorithm is shown as correlation coefficient 0.67 and RMSE 17mm/hr. New algorithm shows the underestimating tendency in case of heavy rainfall event.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.511-525
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• 2010

Rainfall intensity was estimated using the MTSAT-1R infrared channels and the microwave satellite precipitation data. Brightness temperature of geostationary satellite is matched temporal and spatial to a variety of microwave satellite(SSM/I, SSMIS, AMSU-B, AMSRE, TRMM) precipitation data. Rainfall intensity was calculated by the look -up table using relationships of MTSAT-1R brightness temperature and microwave precipitation. Estimated rainfall is verified using by precipitation of TRMM satellite(TRMM3B42) and ground rainfall as AWS from Jul. 21 2008 to Jul. 25 2008. The results of rainfall estimated TRMM 2A12(TMI) that validated by AWS and TRMM3B42 precipitation are represented highly 0.38 and 0.61 by correlation coefficient, 5.81 mm/hr and 2.44 mm/hr by RMSE, 0.79 and 0.84 by POD and 0.65 and 0.87 by PC, respectively. Overall, estimated rainfall using by microwave satellite calculated 5 mm/hr or more comparing by AWS and 5 mm/hr or more comparing by TRMM3B42 precipitation, respectively. Validation results of correlation coefficient are shown series of TRMM 2A12, AMSRE, SSM/I, AMSU-B and SSMIS.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.335-339
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• 2001

The Tropical Rainfall Measuring Mission(TRMM) Satellite was launched in November 1997, carrying into orbit the first space-borne Precipitation Radar(PR). The purpose of this study is to identify the relationship between TRMM/PR and AWS raingage data, and test the possibility to apply storm runoff prediction. Four TRMM/PR data in 1999 for Yongdam watershed was adopted and made a simple linear regression equation using AWS data. By using the equation, the storm runoff was estimated with the adjusted rainfall. TRMM/PR rainfall and runoff was overall underestimated by the carry-over effect of rainfall error and SCS-CN value selection.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.178-181
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• 2004

The Tropical Rainfall Measuring Mission (TRMM) is an US-Japan joint space mission to observe tropical and subtropical rainfall. This satellite is equipped with the world's first precipitation radar that operates at 13.8 GHz. We introduce the TRMM precipitation radar (PR) system, along with the PR data processing and analysis algorithms, and some observation results obtained by the TRMM PR. It is concluded that the TRMM PR can give quite useful rainfall data for the understanding of global climate changes, meteorology, climatology, atmospheric science, and also for the studies of satellite communication.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.5-5
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• 2015

현재 우리나라에서 지상관측장비인 AWS(Automatic Weather System)와 ASOS(Automated Synoptic Observing System)기구가 한반도내 668개 지점에서 운영되고 있다. 이러한 장비는 지상관측장비로 하나의 지점에서 측정된 기상변량들이 특정 영역의 대푯값으로 사용되어지고 있다. 기존의 다양한 지점 단위의 수문 모형에서는 지상관측소를 통한 관측값을 적용하기에 어려움 없이 적절한 결과를 도출할 수 있었다. 컴퓨터의 발달로 인하여 복잡한 물리적 현상을 공간적으로 분석할 수 있는 모형의 구동이 가능해짐에 따라서 수문 분야에서도 다양한 분포형 해석 모형이 활발하게 개발 및 적용되고 있다. 지점 관측 자료는 공간적인 연속성을 반영하지 못하는 한계로 인하여 지점 관측자료를 이용한 공간자료의 생성 기법들이 사용되어지고 있지만 자연계에서 나타나는 정확한 공간적 현상을 재현해주지 못하는 문제점이 존재한다. 이러한 지점 관측의 한계를 해결하기 위하여 공간적인 관측이 가능한 레이더와 위성관측과 같은 원격 관측 장비들이 개발되어 공간적으로 연속성을 갖는 기상변량의 취득이 가능하여졌다. TRMM 강우자료는 지구 전체를 0.25도 약 25km 공간해상도를 갖으며 3시간 간격으로 제공되고 있다. 유역단위의 수문모형에 적용하기에 TRMM 강수자료의 공간해상도는 너무 커서 직접적인 적용에 어려움이 있다. 이러한 점에서 TRMM 자료의 상세화 기법을 통하여 수문모형에 적용이 가능한 1km 이하의 고해상도 자료를 생산하는 연구들이 진행되고 있다. 이러한 상세화 방법은 최종적으로 도출하고자 하는 공간해상도를 갖는 대체 변량(지표면 온도, 고도, 식생, 해수면 기압, 상대 습도, 대기온도, 풍향 등)을 이용하여 회귀분석의 형태로 분석이 이루어지고 있다. 그러나 대체 변량을 통해 도출된 상세화된 TRMM 강우는 간접적인 추정으로 인하여 정확한 결과의 도출에는 한계가 있을 것으로 판단된다. 이러한 점에서 본 연구에서는 한반도내 지상 관측값을 공간적 자료로 변환하여 주는데 효과적으로 평가받는 PRISM 모형에 적용하여 기존 SVM 모형을 통한 TRMM 상세화 결과가 갖는 정확성을 평가해 보고 지점 관측자료의 보간 기법의 평가에 TRMM 자료를 활용하는 방안에 대해 평가해 보고자 한다.