• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1737-1743
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• 2008

A weather radar extracts the weather information from the return echoes which consist of scattered electromagnetic wave signals from rain, cloud and dust particles, etc. The characteristics of Doppler weather signal and ground clutter should be analyzed to extract the accurate weather information. However, the conventional symmetric weather Doppler model is somewhat inappropriate in representing various weather situations. Therefore, the improved model is suggested to describe the skewness in the Doppler spectrum model. Using the suggested model, many various weather signals can be simulated efficiently in time and spectral domain according to weather situations, operation environment and system characteristics. This simulation method may be very helpful in verifying the accuracy of the weather information extraction algorithms and developing the new system for further performance improvement.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.849-862
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• 2017

The increased frequency of meteorological disasters has been observed due to increased extreme events such as heavy rainfalls and flash floods. Numerous studies using high-resolution weather radar rainfall data have been carried out on the hydrological effects. In this study, a conditional merging technique is employed, which makes use of geostatistical methods to extract the optimal information from the observed data. In this context, three different techniques such as kriging, inverse distance weighting and spline interpolation methods are applied to conditionally merge radar and ground rainfall data. The results show that the estimated rainfall not only reproduce the spatial pattern of sub-hourly rainfall with a relatively small error, but also provide reliable temporal estimates of radar rainfall. The proposed modeling framework provides feasibility of using conditionally merged rainfall estimation at high spatio-temporal resolution in ungauged areas.

• Atmosphere
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• v.15 no.3
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• pp.155-165
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• 2005

The characteristics of six precipitation systems occurred around Cheongju in 2002 are analyzed after the convective/stratiform radar echo classification using radar reflectivity from the Meteorological Research Institute"s X-band Doppler weather radar. The Biggerstaff and Listemaa (2000) algorithm is applied for the classification and reveals a physical characteristics of the convective and stratiform rain diagnosed from the three-dimensional structure of the radar reflectivity. The area satisfying the vertical profile of radar reflectivity is well classified, while the area near the radar site and the topography-shielded area show a mis-classification. The seasonal characteristics of the precipitation system are also analyzed using the contoured frequency by altitude diagrams (CFADs). The heights of maximum reflectivity are 4 km and 5.5 km in spring and summer, respectively, and the vertical gradient of radar reflectivity from 1.5 km to the melting layer in spring is larger than in summer.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.180-180
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• 2015

Weather radar has been widely used in measuring precipitation and discharge and predicting flood risks. The radar rainfall estimate has one of the essential problems in terms of uncertainty and accuracy. Previous study analyzed radar errors to reduce its uncertainty or to improve its accuracy. Furthermore, a recent analyzed the effect of radar error on rainfall-runoff using spatial error model (SEM). SEM appropriately reproduced radar error including spatial correlation. Since the SEM does not take the time dependence into account, its time variability was not properly investigated. Therefore, in the current study, we extend the SEM including time dependence as well as spatial dependence, named after Spatial-Temporal Error Model (STEM). Radar rainfall events generated with STEM were tested so that the peak runoff from the response of a basin could be investigated according to dependent error. The Nam River basin, South Korea, was employed to illustrate the effects of STEM on runoff peak flow.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.901-906
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• 2013

Chaff is a kind of matter spreading atmosphere with the purpose of preventing aircraft from detecting by radar. The chaff is commonly composed of small aluminum pieces, metallized glass fiber, or other lightweight strips which consists of reflecting materials. The chaff usually appears on the radar images as narrow bands shape of highly reflective echoes. And the chaff echo has similar characteristics to precipitation echo, and it interrupts weather forecasting process and makes forecasting accuracy low. In this paper, the chaff echo recognizing and removing method is suggested using Bayesian network. After converting coordinates from spherical to Cartesian in UF (Universal Format) radar data file, the characteristics of echoes are extracted by spatial and temporal clustering. And using the data, as a result of spatial and temporal clustering, a classification process for analyzing is performed. Finally, the inference system using Bayesian network is applied. As a result of experiments with actual radar data in real chaff echo appearing case, it is confirmed that Bayesian network can distinguish between chaff echo and non-chaff echo.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1753-1759
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• 2009

A weather radar as one of the remote sensing devices to analyze the weather phenomena receives the return echoes which consist of scattered electromagnetic wave signals from rain, cloud and dust particles, etc. These received Doppler weather spectra are analyzed to extract the various characteristic weather information. The mean wind velocity is one of the important weather parameters which can be obtained by a weather radar ed it may be useful in the prevention of weather hazards occurred by the abrupt shift of wind in small geographical scales such as microbursts. It is usually estimated by pulse pair method which is considered to be reliable and very efficient in the computational requirement. However, there are some problems in the accurate estimation of the mean velocity if Doppler spectra of weather signals appear to be asymmetric gaussian or multi-peak spectra. Therefore, in this paper, the problems in the mean estimation of asymmetric Doppler spectra are analyzed and the improved method is suggested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.3
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• pp.533-542
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• 1994

In a Doppler weather radar, high resolution windspeed profile measurements are needed to provide reliable detection of a hazardous weather condition. For this purpose, the pulse-pair method is generally considered to be the most efficient estimator. However, this estimator has some bias errors due to asymmetric spectra and may yield meaningless results in the case of a multimodal return spectrum in this paper, bias errors were analyzed and an improved method was suggested to reduece these errors. For the case of a multimodal or seriously skewed spectrum, the modes of spectrum may provide more reliable information than the statistical mean. Therefore, the idea of a relatively simple mode estimator is also developed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1173-1179
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• 2008

Since there are very strong clutter returns in airborne and ground weather radars used for the detection of low altitude weather hazards, the reliable weather data cannot be extracted from the weak Doppler weather signal without cancellation of these strong clutter returns. However, the clutter cancellation in Doppler frequency domain is not an easy task since even the fixed clutter returns not to mention the moving clutter can have Doppler shifts due to the antenna rotation and operational environment. Therefore, it was shown in this paper a simple array antenna system can be used for the efficient clutter cancellation in the spatial domain. The weather signal, various moving and fixed clutters were modelled and simulated to prove the performance of this adaptive array system. Also, the degree of accuracy in pulse-pair estimates of a weather radar was compared and analyzed from the simulated weather data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.1999-2005
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• 2015

A wind velocity is measured in a weather radar as well as the strength of return echoes from rain clouds. These wind velocities are obtained through estimation of Doppler frequencies in return signals. This kind of Doppler frequency estimation method is called as a correlation method. It is widely used in most weather radars because of less computation time. However, it may cause serious errors if a spectrum is not symmetric. Therefore, in this paper, it is shown that the improved method using 3^rd order phase estimation model yields the more accurate estimation of the average Doppler frequency using various simulated weather data.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.813-826
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• 2018

Recently, weather radar system has been widely used for effectively monitoring near real-time weather conditions. The radar rainfall estimates are generally relies on the Z-R equation that is an indirect approximation of the empirical relationship. In this regards, the bias in the radar rainfall estimates can be affected by spatial-temporal variations in the radar profile. This study evaluates the uncertainty of the Z-R relationship while considering the rainfall types in the process of estimating the parameters of the Z-R equation in the context of stochastic approach. The radar rainfall estimates based on the Bayesian inference technique appears to be effective in terms of reduction in bias for a given season. The derived Z-R equation using Bayesian model enables us to better represent the hydrological process in the rainfall-runoff model and provide a more reliable forecast.