• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.522-522
• /
• 2015

In this study, the effect of threshold applied to the radar rain rate on the comparison of the radar and rain gauge rain rate was theoretically examined. The result derived was also evaluated theoretically, using the Bernoulli random field, and empirically, using Mt. Kwanak weather radar data. The results are summarized as follows. (1) In the application to the Bernoulli random field, it was found that the comparison of the radar and rain gauge rain rate with threshold does not introduce any systematic bias. (2) The same results could also be derived in the application to Mt Kwanak weather radar data. In all cases with several radar bin sizes and thresholds considered, the bias was estimated to be far less than 10% of the mean of the rain gauge rain rate. (3) However, in the comparison with threshold applied to both the radar and rain gauge rain rate, the bias was estimated to be higher than 20%. That is, the systematic bias was introduced. This result indicates that the comparison with threshold applied to both the radar and rain gauge rain rate should not be used.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.334-334
• /
• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• Korean Journal of Remote Sensing
• /
• v.24 no.1
• /
• pp.17-24
• /
• 2008

Rainfall data from three different types of rain gauge system have been collected for the summertime rain event at Mokpo in the Korean peninsula. The rain gauge system considered in this paper is composed of three tipping-bucket rain gauges with 0.1, 0.2, and 0.5 mm measuring resolutions, the Optical Rain Gauge (ORG), and the PARSIVEL (PARticle SIze and VELocity). The PARSIVEL rainfall rate has been considered as the reference for comparison since it gave good resolution and performance on this event. Comparison with the PARSIVEL rainfall rate gives the results that the error and temporal variation of rainfall rate are simultaneously reduced with increasing the averaging interval of rainfall rate or decreasing the size of tipping bucket. This suggests that the estimated rainfall rate must be optimized, differently for the type of tipping-bucket rain gages, by minimizing the averaging interval of rainfall rate under the condition satisfying the given performance of rainfall rate.

• Journal of Korea Water Resources Association
• /
• v.40 no.11
• /
• pp.841-849
• /
• 2007

This study evaluated the effect of combined rainfall observation of using rain gauge and rain radar. The effect of combined observations is to be evaluated by considering the decrease of measurement error due to combined use of design orthogonal observation methods. As an example, this study evaluated the rain gauge network of the Keum river basin, and showed how the density of rain gauges could be decreased by combining the radar observation. This study applied the researches on sampling error by North and Nakamoto(1989), Yoo et al. (1996) and Yoo (1997), also the simple NFD model for representing the rainfall field. The model parameters were decided using the rainfall characteristics (correlation time and length) estimated using the data collected in the Keum River Basin by 28 rain gauges and the operation rule of radar was assumed arbitrarily. This study considered the rain gauge density criteria provided by WMO(1994) and the rain gauge density installed in the Keum river basin to decrease the rain gauge density under the condition of introducing the radar.

• Journal of Environmental Science International
• /
• v.18 no.10
• /
• pp.1115-1121
• /
• 2009

The purpose of this study is to estimate the impact of rainfall measurement according to the installation conditions of rain gauges: windbreak, grass mat, installation elevation or obstacle. Rain gauges were installed by the standards of Korea Meteorological Administration(KMA), and the rainfall measurement was conducted daily unit during two years(2007~2008). In conclusion, observed error of rain gauge did not affect whether windbreak was installed or not. If there is the obstacle around rain gauge, average error rate was increased about 3.3%: (2007year-2.49%, 2008year-4.10%). If rain gauge is located in a high place, average error rate was increased about 4.89%. Additionally, the observed error of rain gauge according to the wind speed has a positive correlation with obstacle and installation elevation and has a negative correlation with windbreak and has no affection with grass mat.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.7 no.4
• /
• pp.19-29
• /
• 2007

This study compares various ground-truth designs of radar rainfall using rain-gauge data sets from Korea Meteorological Administration (KMA), AWS and Ministry of Construction and Transportation (MOCT). These Rain-gauge data sets and the Mt. Gwanak radar rainfall data for the same period were compared, and then the differences between two observed rainfall were evaluated with respect to the amount of bias. Additionally this study investigated possible differences in bias due to different storm characteristics. The application results showed no distinct differences between biases from three rain-gauge data sets, but some differences in their statistical characteristics. In overall, the design bias from MOCT was estimated to be the smallest among the three rain-gauge data sets. Among three storm events considered, the jangma with the highest spatial intermittency showed the smallest bias.

• Journal of Korea Water Resources Association
• /
• v.39 no.2 s.163
• /
• pp.127-138
• /
• 2006

This study evaluated the effect of zero measurements of rainfall on the spatial correlation structure using the mixed distribution function. Three cases of data structures were considered at two gauge stations: only the positive measurements at both stations, the positive measurements at either one or both stations, and all the measurements including zero measurement at both stations. Also the rainfall data were categorized into the frontal, typhoon, and convective for their comparison. Hourly rainfall data from 12 rain gauge stations within the Geum river basin were analyzed to find that the rain gauge density of WMO to be good for the frontal and typhoon, but not enough for the convective storms.

• Journal of Korea Water Resources Association
• /
• v.38 no.5 s.154
• /
• pp.415-425
• /
• 2005

This study estimated the optimal rain gauge density and sub-basin size for the application of a daily rainfall-runoff analysis model called SWAT (Soil and Water Assessment Tool). Simulated rainfall data using a WGR multi-dimensional precipitation model (Waymire et al., 1984) were applied to SWAT for runoff estimation, and then the runoff error was analyzed with respect to various rain gauge density and sub-basin size. As results of the study, we could find that the optimal sub-basin size and the representative area of one rain gauge are similar to be about $80km^2$ for the Yong-Dam dam basin.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1171-1173
• /
• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• Journal of Korea Water Resources Association
• /
• v.53 no.6
• /
• pp.417-425
• /
• 2020

In order to predict and prevent hydrological disasters such as flood, it is necessary to accurately estimate rainfall. In this paper, an areal average rainfall estimation method using multiple elevation observation data of an electromagnetic wave rain gauge is presented. The small electromagnetic rain gauge system is a very small precipitation radar that operates at K-band with dual-polarization technology for very short distance observation. The areal average rainfall estimation method is based on the assumption that the variation in rainfall over the observation range is small because the observation distance and time are very short. The proposed method has been evaluated by comparing with ground instruments such as tipping-bucket rain gauges and a Parsivel. The evaluation results show that the methodology works fairly well for the rainfall events which are shown here.