• Journal of the Korean earth science society
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• v.39 no.2
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• pp.131-138
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• 2018

The purpose of this study is to improve the quantitative precipitation estimation method based on satellite brightness temperature. The non-linear equation for rainfall estimation is improved by analysing precipitation cases around the Korean peninsula in summer. Radar reflectivity is adopted the CAPPI 1.5 and CMAX composite fields that provided by the Korea Meteorological Agency (KMA). In addition, the satellite data are used infrared, water vapor and visible channel measured from meteorological imager sensor mounted on the Chollian satellite. The improved algorithm is compared with the results of the A-E method and CRR analytic function. POD, FAR and CSI are 0.67, 0.76 and 0.21, respectively. The MAE and RMSE are 2.49 and 6.18 mm/h. As the quantitative error was reduced in comparison to A-E and qualitative accuracy increased in compare with CRR, the disadvantage of both algorithms are complemented. The method of estimating precipitation through a relational expression can be used for short-term forecasting because of allowing precipitation estimation in a short time without going through complicated algorithms.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.3
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• pp.101-109
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• 2021

Wave observations using a marine X-band radar are conducted by analyzing the backscattered radar signal from sea surfaces. Wave parameters are extracted using Modulation Transfer Function obtained from 3D wave number and frequency spectra which are calculated by 3D FFT of time series of sea surface images (42 images per minute). The accuracy of estimation of the significant wave height is, therefore, critically dependent on the quality of radar images. Wave observations during Typhoon Maysak and Haishen in the summer of 2020 show large errors in the estimation of the significant wave heights. It is because of the deteriorated radar images due to raindrops falling on the sea surface. This paper presents the algorithm developed to increase the accuracy of wave heights estimation from radar images by adopting convolution neural network(CNN) which automatically classify radar images into rain and non-rain cases. Then, an algorithm for deriving the Hs is proposed by creating different ANN models and selectively applying them according to the rain or non-rain cases. The developed algorithm applied to heavy rain cases during typhoons and showed critically improved results.

• Journal of Korea Water Resources Association
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• v.55 no.9
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• pp.679-686
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• 2022

As the occurrences of flash floods have increased due to climate change, faster and more accurate precipitation observation using X-band radar has become important. Therefore, the Ministry of Environment installed two dual-pol X-band radars at Samcheok and Uljin. The radar data used in this study were obtained from two different elevation angles and composed to reduce the shielding effect. To obtain quantitative rainfall, quality control (QC), K_DP retrieval, and Hybrid Surface Rainfall (HSR) methods were sequentially applied. To improve the accuracy of the quantitative precipitation estimation (QPE) of the X-band radar, we retrieved parameters for the relationship between rainfall rate and specific differential phase, which is commonly called the R-K_DP relationship; hence, an empirical approach was developed using multiple rain gauges for those two radars. The newly suggested relationship, R = 27.4K^0.81_DP, slightly increased the correlation coefficient by 1% more than the relationship suggested by the previous study. The root mean square error significantly decreased from 3.88 mm/hr to 3.68 mm/hr, and the bias of the estimated precipitation also decreased from -1.72 mm/hr to -0.92 mm/hr for overall cases, showing the improvement of the new method.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.1-8
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• 2016

The Korea Meteorological Administration has operated the Automatic Weather Stations, of the average 13 km horizontal resolution, to observe rainfall. However, an additional RADAR network also has been operated in all-weather conditions, because AWS network could not observed rainfall over the sea. In general, the rain rate is obtained by estimating the relationship between the radar reflectivity (Z) and the rainfall (R). But this empirical relationship needs to be optimized on the rainfall over the Korean peninsula. This study was carried out to optimize the Z-R relationship in the summer of 2014 using a parallel Micro Genetic Algorithm. The optimized Z-R relationship, $Z=120R^{1.56}$, using a micro genetic algorithm was different from the various Z-R relationships that have been previously used. However, the landscape of the fitness function found in this study looked like a flat plateau. So there was a limit to the fine estimation including the complex development and decay processes of precipitation between the ground and an altitude of 1.5km.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.119-133
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• 2014

The study adopted extended Kalman filter technique in an effort to predict Z-R relationship parameter as a stable value in real-time. Toward this end, a parameter estimation model was established based on extended Kalman filter in consideration of non-linearity of Z-R relationship. A state-space model was established based on a study that was conducted by Adamowski and Muir (1989). Two parameters of Z-R relationship were set as state variables of the state-space model. As a result, a stable model where a divergence of Kalman gain and state variables are not generated was established. It is noteworthy that overestimated or underestimated parameters based on a conventional method were filtered and removed. As application of inappropriate parameters might cause physically unrealistic rain rate estimation, it can be more effective in terms of quantitative precipitation estimation. As a result of estimation on radar rainfall based on parameters predicted with the extended Kalman filter, the mean field bias correction factor turned out to be around 1.0 indicating that there was a minor difference from the gauge rain rate without the mean field bias correction. In addition, it turned out that it was possible to conduct more accurate estimation on radar rainfall compared to the conventional method.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.267-267
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• 2023

최근 이상기상현상과 기후변화로 인하여 국지적인 집중호우의 빈도 및 규모가 증가하고 있으며, 이로 인한 돌발 홍수 피해가 증가하고 있다. 레이더는 넓은 영역에 대해 고해상도의 강우 정보를 제공할 수 있으므로 위험기상 감시 및 실황 예측 모형의 입력자료로써 활용도가 높다. 레이더 강우량은 대기 중 강수입자에 대한 레이더 반사도와 강우강도의 Z-R 관계식으로 추정되기 때문에 강우 추정 과정에 불확실성을 내포하고 있다. 특히, 우리나라의 여름철 한반도의 집중호우는 층운형 강우와 함께 대류형 강우가 동반되는 복합적인 강우시스템에서 자주 발생하지만, 레이더 강우는 일반적으로 단일 강우시스템에 대한 고정된 Z-R 관계식으로 추정하므로, 이러한 현상에 대해 과대 추정 혹은 과소 추정이 발생한다. 본 연구에서는 집중호우에 적합한 강우를 추정하기 위해 2021년 8월 21일부터 8월 25일까지 경남 호우사례를 대상으로 층운형, 대류형, 열대형의 Z-R관계식과 반사도 조건에 따라 층운형과 적운형을 구분하여 Z-R 관계식을 적용하여 레이더 강우량 자료를 산출하였으며, 지상강우자료를 이용하여 정확도를 평가하였다. 레이더 자료 처리를 위해 Radar Software Library (RSL)를 이용하여 수평으로 1km 해상도의 1.5km CAPPI (Constant Altitude Plan Position Indicator) 자료로 변환하였다. 레이더 강우 추정의 정확도를 평가하기 위해 레이더 지점으로부터 100 km 이내에 위치하고 있는 기상관서와 자동기상관측소의 강우관측 결과와 비교·분석하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.985-996
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• 2000

In the coastal zone, to draw up short and medium range weather forecasts, mesoscale pluviogenic systems coming from the sea have to be observed in real time. These observations use remote sensing. However, satellite remote sensing is not sufficient to describe pluviogenic systems; reference to radar long distance observations is indispensable. This paper deals with the corrections, which must be made to long distance radar data if the rainfall field is to be both accurately and quantitatively defined. The error due to vertical variation in the reflectivity factor can be corrected from estimation of the mean profiles or by a climatic adjustment method. Atten-uation in the propagation can be corrected by an iterative polarimetric method. These various correc-tions permit the distance validity limits of radar data to be extended.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5B
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• pp.267-272
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• 2012

To reduce the flood risk caused by unexpected heavy rainfall, many prediction methods for flood have been developed. A major constituent of flood prediction is an accurate rainfall estimation which is an input of hydrologic models. In this study, a regional-scale weather model which can provide relatively longer lead time for flood mitigation compared to the Nowcasting based on radar system will be introduced and applied to the Chongmi river basin located in central part of South Korea. The duration of application of a regional weather model is from July 11 to July 23 in 2006. The estimated rainfall amounts were compared with observations from rain gauges (Sangkeuk, Samjook, and Sulsung). For this rainfall event at Chongmi river basin, Thomson and Kain-Frisch Schemes for microphysics and cumulus parameterization, respectively, were selected as optimal physical conditions to present rainfall fall amount in terms of Mean Absolute Relative Errors (MARE>0.45).

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1511-1514
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• 2006

본 연구에서는 현재 건설교통부에서 설치 및 운영 중에 있는 소형강우레이더의 최적화를 위해서 지상의 강우관측소 자료와 레이더 측정 자료의 실시간 보정방법을 이용하여 강우강도를 추정하였다. 본 연구에서 이용된 실시간 Z-R 관계식 적용으로 인한 강우강도 개선 정도를 파악하기 위해서 통상 일률적으로 적용되고 있는 $Z=200R^{1.6}$에 의한 강우강도 결과와 비교.분석하였으며, 지상의 강우관측소 실측 강우량과 비교함으로써 적용성을 보였다. 본 연구에서 이용된 보정방법은 강우보정에 소요되는 시간이 짧아 실시간 적용이 가능하며, 레이더 강우량의 정확한 추정으로 유역에서의 향상된 면적강우량 산출이 가능할 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.39 no.4 s.165
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• pp.347-362
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• 2006

In this study, a 2-D flood inundation model was developed to evaluate the impact of levee failure in a natural basin for flood analysis. The model was applied to analyze the inundation flow from the levee break of Gamcheon river during the typhoon Rusa on October 31 through September 1, 2002. To verify the simulated results, wide range field surveys have been performed including the collection of NGIS database, land use condition, flooded area, and flow depths. Velocity distributions and inundation depths were presented to demonstrate the robustness of the model. Model results have good agreements with the observed data in terms of flood level and flooded area. The model is able to compute maximum stage and peak discharge efficiently in channel and protected lowland. Methodology considering radar-rainfall estimation using cokriging scheme, flood-runoff and inundation analysis in this study will contribute to the establishment of the national integrated flood disaster prevention system and the river or protect lowland management system.