• Journal of Environmental Science International
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• v.24 no.4
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• pp.525-540
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• 2015

Spatial distribution of precipitation has been estimated based on the local gauge correction (LGC) with a fixed inverse distance weighting (IDW), which is not optimized in taking effective radius into account depending on the radar error. We developed an algorithm, improved local gauge correction (ILGC) which eliminates outlier in radar rainrate errors and optimize distance power for IDW. ILGC was statistically examined the hourly cumulated precipitation from weather for the heavy rain events. Adjusted radar rainfall from ILGC is improved to 50% compared with unadjusted radar rainfall. The accuracy of ILGC is higher to 7% than that of LGC, which resulted from a positive effect of the optimal algorithm on the adjustment of quantitative precipitation estimation from weather radar.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.237-249
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• 2003

Wind effects on a rain gauge can cause a significant underestimation of rainfall depths and contribute to the inconsistency in rainfall data. To revise the rainfall data requires the study about calculation of deficiency percentages of rain catch. There are few studies which reflect the variation of wind speed. in this study, the raindrop terminal velocity is quantified according to the particle size of rainfall. The model for calculating deficiency percentages of rain catch according to the particle size of rainfall is examined by experimentation. Experimentation shows that deficiency percentages of rain catch have no relationship with rainfall intensity and affected by raindrop diameter. In conclusion, the estimated deficiency percentages of rain catch coincided with the experimental results and can be used as recommended adjustment factors.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.2
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• pp.108-122
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• 1996

This study was to introduced estimation model for optimum probabilistic rainfall intensity on hydrological area. Originally, probabilistic rainfall intensity formula have been characterized different coefficient of formula and model following watersheds. But recently in korea rainfall intensity formula does not use unionize applyment standard between administration and district. And mingle use planning formula with not assumption model. Following the number of year hydrological duration adjust areal index. But, with adjusting formula applyment was without systematic conduct. This study perceive the point as following : 1) Use method of excess probability of Iwai to calculate survey rainfall intensity value. 2) And, use method of least squares to calculate areal coefficient for a unit of 157 rain gauge station. And, use areal coefficient was introduced new probabilistic rainfall intensity formula for each rain gauge station. 3) And, use new probabilistic rainfall intensity formula to adjust a unit of fourteen duration-a unit of fifteen year probabilistic rainfall intensity. 4) The above survey value compared with adjustment value. And use three theory of error(absolute mean error, squares mean error, relative error ratio) to choice optimum probabilistic rainfall intensity formula for a unit of 157 rain gauge station.

• Journal of the Korean earth science society
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• v.34 no.1
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• pp.13-27
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• 2013

Quantitative precipitation estimation (QPE) is one of the most important elements in meteorological and hydrological applications. In this study, we adjusted the QPE from an S-band weather radar based on co-kriging method using the geostatistical structure function of error distribution of radar rainrate. In order to estimate the accurate quantitative precipitation, the error of radar rainrate which is a primary variable of co-kriging was determined by the difference of rain rates from rain gauge and radar. Also, the gauge rainfield, a secondary variable of co-kriging is derived from the ordinary kriging based on raingauge network. The error distribution of radar rain rate was produced by co-kriging with the derived theoretical variogram determined by experimental variogram. The error of radar rain rate was then applied to the radar estimated precipitation field. Locally heavy rainfall case during 6-7 July 2009 is chosen to verify this study. Correlation between adjusted one-hour radar rainfall accumulation and rain gauge rainfall accumulation improved from 0.55 to 0.84 when compared to prior adjustment of radar error with the adjustment of root mean square error from 7.45 to 3.93 mm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.431-438
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• 2011

This study investigated the problem of mean-field bias correction under the assumption that the radar and rain gauge rainfall data follow the log-normal distribution. Regression curves for the average, median and mode of the radar and rain gauge rainfall were derived and evaluated for their usefulness. Additionally, these regression curves were compared with those derived under the assumption that the radar and rain gauge data follow the normal distribution. This study investigated the regression results for the Typhoon Meami occurred in 2003 as an example. As results, three regression lines with the radar rainfall as the independent variable were found to underestimate the rainfall, while those with the rain gauge rainfall as the independent variable to overestimate. Among three types of regression curves considered, the result for the average was most appropriate. However this case was found to be inferior to the regression line passing the origin under the assumption of the normal distribution with the rain gauge rainfall as its independent variable. So it was hard to conclude that the consideration of the log-normality on the correction of radar rainfall is beneficial.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.393-403
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• 2011

This study theoretically reviewed the empirical G/R ratio by considering three regression and trend lines; the general linear regression curve, linear regression curve passing the origin, and the line passing the origin and the mass center of observed data. This review included the problem of choosing the independent variable and that of considering the zero measurements. This review result was also applied to the Typhoon Maemi in 2003 for their evaluation. Additionally, those regression and trend lines were compared using the RMSE between the corrected radar rainfall and observed rain gauge rainfall to select the most appropriate G/R ratio. Summarizing the results is as follows. First, the results of selecting the rain gauge rainfall as the independent variable were found better than the opposite case. Second, the effect of zero measurements varies depending on the structure of radar and rain gauge rainfall. Finally, the results from the comparison of three regression and trend lines shows that the slope of the regression line passing the origin with its independent variable of rain gauge rainfall would be used most appropriately for the G/R ratio, especially when the corrected radar rainfall is used for the flood analysis. The effect of zero measurements in this case was found not so significant.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.461-470
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• 2023

The purpose of this research is to derive the optimal temperature, location, and heating control system for a tipping bucket rain gauge heating system used for observing snowfall during winter. We conducted indoor and outdoor experiments by manufacturing a tipping bucket rain gauge that can be variably controlled for heating at the funnel, exterior, and interior, and indoor and outdoor. The indoor experiments involved using a temperature and humidity chamber to compare the performance and derive the appropriate temperature of the precipitation gauge heating system. Subsequently, the outdoor experiments were carried out at the Cloud Physics Observation Center located in Daeguallyeong, heavy snowfall region, to validate the findings. The analysis result was derived that the heating temperature of the funnel should be set at the 10 to 30℃, while the internal heating temperature should be 70℃. Furthermore, the optimal locations for the heating devices, which aim to minimize measurement delay, were identified as the exterior of the rain gauge, the rim of the funnel, and the vertical surface of the funnel. Our result shows that used as the basis for the operating conditions of precipitation gauge heating systems for solid precipitation measurement in winter.

• Journal of the Korean earth science society
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• v.33 no.7
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• pp.569-582
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• 2012

The heavy rainfalls caused large property damages and human casualties. For example, Changma caused 0.25 billion dollars in damages and 57 deaths and 112 missing by accompanying the torrentially convective heavy rainfall in Seoul, 2011. In addition, TY15 (Bolaven) caused a small damage by bringing a relatively small amount of rainfall and strong wind in Gwanju, 2012. The investigation and analyses of these mesoscale processes of rainfall events for different physical properties using KLAPS for weather environments of the above cases were performed. These typical and ideal meoscale systems by better and more favorable cloud systems were chosen to retrieve rain intensity from Radar and Chullian data. The quantitative rain intensities of Radar and Chullian differ greatly from the ground-based gauge values with underestimating over 50 mm/hr at the peak time of hourly maximum rain intensity about over than 85 mm/hr. However, the Radar rain intensity demonstrated approximately lower than 35 mm/hr, and the Chullian rain intensity less than 60 mm/hr for Changma in Seoul, 2011. For typhoon (TY15, Bolaven) in Gwangju, similarly, the quantitative rain intensities of Radar and Chullian differ from the ground-based gauge values. At the peak time, the hourly maximum rain intensity of ground-based gauge was more than 15 mm/hr. However, the Radar rain intensity showed lower than 5 mm/hr, and the Chullian rain intensity lower than 10 mm/hr. Regarding the above two cases of typhoon and Changma, even though Radar and Chullian rain intensities have been underestimated when compared to the ground-based rain intensity, the distributions of time scale features of both Radar and Chullian rain intensities still delineated a similar tendency of rain intensity distribution of the ground-based gauge data.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2468-2473
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• 2005

Because the rain gauges of tipping bucket type can easily use the digital signal, the rain gauges are widely used for the meteorological observation. In general, the resolution of rain gauges of tipping bucket type can be categorized by the 0.1mm, 0.5mm, and 1.0mm classes. But, the error of the tipping bucket rain gauges is made by the intensity of rainfalls and is expected to make the standard calibration method for error measurement. Thus, we developed the hardware of standard calibration facility for rain gauges by weighting measurement method and proposed the standard procedure by rainfall intensity in this study Also, we calculated the error for the rainfall intensity and obtained useful result through the proposed calibration method.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1575-1577
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• 2002

In this research we propose a method far rain rate estimation by using Doppler spectrum's data of wind profiler. The Doppler spectrum is used to calculate the wind velocity and wind direction. But in this research uses the parameters from Doppler spectrum, it calculates the rain rate. The rain rate estimation in this method will be compared to the obtained rain rate from the surface rain gauge. Two equipments are installed in the same area. The correlation coefficient between rain rate measuring method is 0.65.