• Title/Summary/Keyword: G/R bias adjustment

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Adjustment of the Mean Field Rainfall Bias by Clustering Technique (레이더 자료의 군집화를 통한 Mean Field Rainfall Bias의 보정)

  • Kim, Young-Il;Kim, Tae-Soon;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.42 no.8
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    • pp.659-671
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    • 2009
  • Fuzzy c-means clustering technique is applied to improve the accuracy of G/R ratio used for rainfall estimation by radar reflectivity. G/R ratio is computed by the ground rainfall records at AWS(Automatic Weather System) sites to the radar estimated rainfall from the reflectivity of Kwangduck Mt. radar station with 100km effective range. G/R ratio is calculated by two methods: the first one uses a single G/R ratio for the entire effective range and the other two different G/R ratio for two regions that is formed by clustering analysis, and absolute relative error and root mean squared error are employed for evaluating the accuracy of radar rainfall estimation from two G/R ratios. As a result, the radar rainfall estimated by two different G/R ratio from clustering analysis is more accurate than that by a single G/R ratio for the entire range.

Hydrologic Utilization of Radar-Derived Rainfall (I) Optimal Radar Rainfall Estimation (레이더 추정강우의 수문학적 활용 (I): 최적 레이더 강우 추정)

  • Bae Deg-Hyo;Kim Jin-Hoon;Yoon Seong-Sim
    • Journal of Korea Water Resources Association
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    • v.38 no.12 s.161
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    • pp.1039-1049
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    • 2005
  • The objective of this study is to produce optimal radar-derived rainfall for hydrologic utilization. The ground clutter and beam blockage effects from Mt. Kwanak station (E.L 608m) are removed from radar reflectivities by POD analysis. The reflectivities are used to produce radar rainfall data in the form of rain rates (mm/h) by the application of the Marshall-Palmer reflectivity versus rainfall relationship. However, these radar-derived rainfall are underestimated in temporal and spatial scale compared with observed one, so it is necessary to hire a correction scheme based on the gauge-to-radar (G/R) statistical adjustment technique. The selected watershed for studying the real-time correction of radar-rainfall estimation is the Soyang dam site, which is located approximately 100km east of Kwanak radar station. The results indicate that adjusted radar rainfall with the gauge measurement have reasonal G/R ratio ranged on 0.95-1.32 and less uncertainty with that mean standard deviation of G/R ratio are decreased by $9-28\%$. Mean areal precipitation from adjusted radar rainfall are well agreed to the observed one on the Soyang River watershed. It is concluded that the real-time bias adjustment scheme is useful to estimate accurate basin-based radar rainfall for hydrologic application.

Adjustment of Radar Mean-field Bias Considering Orographic Effect (산악효과를 고려한 Mean-field bias의 보정)

  • Kim, Young-Il;Sung, Gyung-Min;Hwang, Man-Ha;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1136-1140
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    • 2009
  • 지상강우 관측망을 이용한 강우량 측정의 대안으로서 사용되는 기상 레이더를 활용한 강우량 추정의 경우, Z-R 방정식을 이용하여 반사도를 강우량으로 환산하는 방법을 일반적으로 사용한다. 이때 발생하는 각종 오차는 레이더 장비가 가지는 기계적인 오차뿐만 아니라 Z-R 방정식이 가지는 오차 등이 있으며, 이를 보정하기 위해서 레이더를 활용하여 추정된 강우량에 지상강우량계와 레이더강우량과의 비율인 G/R비를 보정하는 방법을 일반적으로 사용한다. 본 연구에서는 이와 같이 레이더 강우량을 보정하기 위해서 사용되는 G/R비를 산정하는데 미치는 지형적인 효과를 고려하기 위해서 광덕산 레이더 유효범위 100km 내(군사분계선 이북 미포함)의 지역에 대하여 군집분석을 실시하여 크게 산악지역과 평야지역으로 구분하고, 각각 구분된 지역에 대하여 G/R 비를 산정하여 초기추정 레이더 강우량에 곱하는 mean-field bias 보정을 실시하였다. 광덕산 레이더 기상관측소의 유효범위 100km 내의 2007년, 2008년 홍수기(6/21${\sim}$9/20)기간 동안 94개 Automatic Weather Station(AWS)지점에 대하여 크게 산악지역과 평야지역으로 지역화 시키는 방법은 비계층적 군집분석 기법 중 fuzzy-c mean 방법을 적용하였다. 또한 광덕산 레이더 반사도 기본 자료는 차폐영역으로 생기는 반사도 데이터 누락을 보완하기 위하여 0도와 1.5도 sweep 합성 10분단위 uf 자료를 사용하였으며, AWS와 보정이 이루어지는 레이더 격자의 크기는 최대 4km${\times}$4km로 선정하였다. 본 연구에 있어서 검증방법은 지역을 구분하기 전과 후를 AWS 실측 관측값과 절대상대오차, 평균제곱근 오차로써 비교하였다.

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Development and Performance Evaluation of Falling-type Dried-Persimmon Weight Sorting System Utilizing Load Cell

  • Lim, Jongguk;Kim, Giyoung;Mo, Changyeun;Choi, Inchul
    • Journal of Biosystems Engineering
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    • v.40 no.4
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    • pp.327-334
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    • 2015
  • Purpose: A falling-type weight sorter equipped with a load cell was developed to sort lightweight dried persimmons. The performance of the sorter was also evaluated. Methods: The electronic weight sorter for dried persimmon comprises a feeder part, a weight-measurement part, an indicator part, a carrier cup, a discharging part, and a driving part. The weight setting and zero-point adjustment are performed digitally for the convenience of users. For the experimental trials, 228 rubber-clay specimens (representative of dried persimmons) in the weight range of 24.73~99.56 g were manufactured for use in experiments to evaluate the performance of the sorter. Results: The average error of the weight measurements from three experimental trials was 1.655%, with a bias of -0.492 g, a root-mean-square error (RMSE) of ${\pm}0.808g$, and a coefficient of determination ($R^2$ ) of 0.997. Conclusions: The load-cell-based electronic dried-persimmon weight sorter developed in this study facilitates effective, precise, and convenient sorting of dried persimmons.

Adjustment of A Simplified Satellite-Based Algorithm for Gross Primary Production Estimation Over Korea

  • Pi, Kyoung-Jin;Han, Kyung-Soo;Kim, In-Hwan;Lee, Tae-Yoon;Jo, Jae-Il
    • Korean Journal of Remote Sensing
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    • v.29 no.3
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    • pp.275-291
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    • 2013
  • Monitoring the global Gross Primary Pproduction (GPP) is relevant to understanding the global carbon cycle and evaluating the effects of interannual climate variation on food and fiber production. GPP, the flux of carbon into ecosystems via photosynthetic assimilation, is an important variable in the global carbon cycle and a key process in land surface-atmosphere interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) is one of the primary global monitoring sensors. MODIS GPP has some of the problems that have been proven in several studies. Therefore this study was to solve the regional mismatch that occurs when using the MODIS GPP global product over Korea. To solve this problem, we estimated each of the GPP component variables separately to improve the GPP estimates. We compared our GPP estimates with validation GPP data to assess their accuracy. For all sites, the correlation was close with high significance ($R^2=0.8164$, $RMSE=0.6126g{\cdot}C{\cdot}m^{-2}{\cdot}d^{-1}$, $bias=-0.0271g{\cdot}C{\cdot}m^{-2}{\cdot}d^{-1}$). We also compared our results to those of other models. The component variables tended to be either over- or under-estimated when compared to those in other studies over the Korean peninsula, although the estimated GPP was better. The results of this study will likely improve carbon cycle modeling by capturing finer patterns with an integrated method of remote sensing.