• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1430-1437
• /
• 2019

In this paper, we proposed a methodology for estimating rainfall intensity using a W-band FMCW automotive radar signal which is the core technology of autonomous driving car. By comparing and analyzing the results of rainfall and non-rainfall observation, we found that the reflection intensity of the automotive radar is changed with rainfall intensity. We could confirm the possibility of deriving the quantitative precipitation estimation using the methodology derived from this result. In addition it can be possible to develop a new paradigm of precipitation observation technique by observing various events together with the weather radar and the ground rainfall observation equipment.

• Atmosphere
• /
• v.25 no.4
• /
• pp.719-734
• /
• 2015

Korea is one of the country with the world's oldest meteorological observation records. Starting with first meteorological record of fog in Goguryeo in the year of 34 BC, Korea had left a great deal of quantitative observation records, from the Three Kingdoms Period to Goryeo to Joseon. During the Joseon Dynasty, with a great attention by kings, efforts were particularly made to measure rainfall in a systematic and scientific manner. In the 23rd year of King Sejong (1441), the world's first rain gauge called "Chugugi" was invented; in the following year (1442), a nationwide rainfall observation network was established. The King Sejong distributed Chugugi to 350 observation stations throughout the state, even to small towns and villages, for measuring and recording rainfall. The rainfall observation using Chugugi, initiated by King Sejong, had been in place for about 150 years, but halted during national disturbances such as Japanese invasion of Korea in 1592. Since then, the observation had been forgotten for a long time until the rainfall observation by Chugugi was resumed in the 48th year of King Yeongjo (1770). King Yeongjo adopted most of the existing observation system established by King Sejong, including the size of Chugugi and observation rules. He, however, significantly reduced the number of Chugugi observation stations to 14, and commanded the 352 local authorities such as Bu, Gun, Hyeon to conduct "Wootaek", a method of measuring how far the moisture had absorbed into the soil when it rains. Later on, six more Chugugi stations were established. If the number of stations of Chugugi and Wootaek are combined together, the total number of rainfall observation station in the late period of Joseon Dynasty was 372. The rainfall observation with Chugugi during the Joseon Dynasty is of significance and excellence in three aspects: 1) the standard size of Chugugi was so scientifically designed that it is as great as today's modern rain gauge; 2) rainfall was precisely measured, even with unit of Bun (2 mm); and 3) the observation network was distributed on a nationwide basis.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.132-134
• /
• 1999

Rainfall characteristics for designing the optimum millimeter-wave communication systems from two rainfall data set was analyzed. Two rainfall data sets were compared; one-minute rainfall rate data, one-hour synoptic observation data. Each data set has different observation method, sampling frequency. We looked for tendency and quality confluence between two data sets. We showed several results using one-minute rainfall data by millimeter-wave attenuation model. A climatological one-minute rainfall rate data set over Korean Peninsula will be made after data quality control procedure

• Journal of the Korean earth science society
• /
• v.36 no.5
• /
• pp.460-475
• /
• 2015

A number of heavy rainfall events on the Korean Peninsula are indirectly influenced by tropical cyclones (TCs) when they are located in southeastern China. In this study, a heavy rainfall case in the middle Korean region is selected to examine the influence of typhoon simulation performance on predictability of remote rainfall over Korea as well as direct rainfall over Taiwan. Four different numerical experiments are conducted using Weather Research and Forecasting (WRF) model, toggling on and off two different improvements on typhoon in the model initial condition (IC), which are TC bogussing initialization and dropwindsonde observation data assimilation (DA). The Geophysical Fluid Dynamics Laboratory TC initialization algorithm is implemented to generate the bogused vortex instead of the initial typhoon, while the airborne observation obtained from dropwindsonde is applied by WRF Three-dimensional variational data assimilation. Results show that use of both TC initialization and DA improves predictability of TC track as well as rainfall over Korea and Taiwan. Without any of IC improvement usage, the intensity of TC is underestimated during the simulation. Using TC initialization alone improves simulation of direct rainfall but not of indirect rainfall, while using DA alone has a negative impact on the TC track forecast. This study confirms that the well-suited TC simulation over southeastern China improves remote rainfall predictability over Korea as well as TC direct rainfall over Taiwan.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.2
• /
• pp.63-74
• /
• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

• Journal of Multimedia Information System
• /
• v.5 no.4
• /
• pp.245-256
• /
• 2018

This study estimated rainfall information more effectively by image signals through the information system of weather radar. Based on this, we suggest the way to estimate quantitative precipitation utilizing overlapped observation area of radars. We used the overlapped observation range of ground hyetometer observation network and radar observation network which are dense in our country. We chose the southern coast where precipitation entered from seaside is quite frequent and used Sungsan radar installed in Jeju island and Gudoksan radar installed in the southern coast area. We used the rainy season data generated in 2010 as the precipitation data. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.15-15
• /
• 2011

The radar observation system in Japan is operated by two governmental groups: Japan Meteorological Agency (JMA) and the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan. The JMA radar observation network is comprised of 20 C-band radars (with a wavelength of 5.6 cm), which cover most of the Japan Islands and observe rainfall intensity and distribution. And the MLIT's radar observation system is composed of 26 C-band radars throughout Japan. The observed radar echo from each radar unit is first modified, and then sent to the National Bureau of Synthesis Process within the MLIT. Through several steps for homogenizing observation accuracy, including distance and elevation correction, synthesized rainfall intensity maps for the entire nation of Japan are generated every 5 minutes. The MLIT has recently launched a new radar observation network system designed for flash flood observation and forecasting in small river basins within urban areas. It is called the X-band multi parameter radar network, and is distinguished by its dual polarimetric wave pulses of short length (3cm). Attenuation problems resulting from the short wave length of radar echo are strengthened by polarimetric wavelengths and very dense radar networks. Currently, the network is established within four areas. Each area is observed using 3-4 X-band radars with very fine resolution in spatial (250 m) and temporal (1 minute intervals). This study provides a series of utilization procedures for the new input data into a real-time forecasting system. First of all, the accuracy of the X-band radar observation was determined by comparing its results with the rainfall intensities as observed by ground gauge stations. It was also compared with conventional C-band radar observation. The rainfall information from the new radar network was then provided to a distributed hydrologic model to simulate river discharges. The simulated river discharges were evaluated again using the observed river discharge to estimate the applicability of the new observation network in the context of operations regarding flood forecasting. It was able to determine that the newly equipped X-band polarimetric radar network shows somewhat improved observation accuracy compared to conventional C-band radar observation. However, it has a tendency to underestimate the rainfall, and the accuracy is not always superior to that of the C-band radar. The accuracy evaluation of the X-band radar observation in this study was conducted using only limited rainfall events, and more cases should be examined for developing a broader understanding of the general behavior of the X-band radar and for improving observation accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.6
• /
• pp.783-791
• /
• 2018

The biased estimation of low density rainfall network and radar rainfall has limited application to extreme rainfall in a small area. To improve this, more rainfall information needs to be produced. In this study, we analyzed the applicability of the vehicle rainfall sensor developed and used recently. The developed rainfall sensor was attached to the vehicle to observe the rainfall according to the movement of the vehicle. The analytical method used time series and average rainfall values for observations of rainfall sensors and nearby rainfall stations. The results show that the trend of observed values according to rainfall events shows a certain pattern. It is analyzed that it is caused by various causes such as the difference between the observation position of the rainfall sensor and the nearby rainfall station, the moving speed of the vehicle, and the rainfall observation method. This result shows the possibility of rainfall observation using a rainfall sensor for a vehicle, and it is possible to observe rainfall more precisely through experiments and improvement of rainfall sensors in various conditions in the future.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.1798-1802
• /
• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation.The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall.The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

• Journal of Industrial Technology
• /
• v.27 no.A
• /
• pp.95-102
• /
• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation. The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall. The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.