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

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.605-612
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• 2008

In this study, we estimate solar surface insolation (SSI) by using physical methods with MTSAT-1R data. SSI is regarded as crucial parameter when interpreting solar-earth energy system, climate change, and agricultural production predict application. Most of SSI estimation model mainly uses ground based-measurement such as pyranometer to tune the constructed model and to validate retrieved SSI data from optical channels. When compared estimated SSI with pyranometer measurements, there are some systemic differences between those instruments. The pyranometer data observed upward-looking hemispherical solid angle and distributed hourly measurements data which are averaged every 2 minute instantaneous observation. Whereas MTSAT-1R channels data are taken instantaneously images at fixed measurement time over scan area, and are pixel-based observation with a much smaller solid angle view. Those temporal discrepancies result from systemic differences can induce validation error. In this study, we adjust hour when estimate SSI to improve the retrieved accurate SSI.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1203-1210
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• 2020

Drought is caused by a combination of various hydrological or meteorological factor, so it is difficult to accurately assess drought event, but various drought indices have been developed to interpret them quantitatively. However, the drought indexes currently being used are calculated from the lack of a single variable, which is a problem that does not accurately determine the drought event caused by complex causes. Shortage of a single variable may not be a drought, but it is judged to be a drought. On the other hand, research on developing indices using unstructured data, which is widely used in big data analysis, is being carried out in other fields and proven to be superior. Therefore, in this study, we intend to calculate the drought index by combining unstructured data (news data) with weather and hydrologic information (rainfall and dam inflow) that are being used for the existing drought index, and to evaluate the utilization of drought interpretation through verification of the calculated drought index. The Clayton Copula function was used to calculate the joint drought index, and the parameter estimation was used by the calibration method. The analysis showed that the drought index, which combines unstructured data, properly expresses the drought period compared to the existing drought index (SPI, SDI). In addition, ROC scores were calculated higher than existing drought indices, making them more useful in drought interpretation. The joint drought index calculated in this study is considered highly useful in that it complements the analytical limits of the existing single variable drought index and provides excellent utilization of the drought index using unstructured data.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.363-374
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• 2008

Intensity-Duration-Frequency (IDF) curve that is essential to calculate rainfall quantiles for designing hydraulic structures in Korea is generally formulated by regression analysis. In this study, IDF curve derived by the cumulative distribution function ("IDF by CDF") of the proper probability distribution function (PDF) of each site is suggested, and the corresponding parameters of IDF curve are computed using genetic algorithm (GA). For this purpose, IDF by CDF and the conventional IDF derived by regression analysis ("IDF by REG") were computed for 22 Korea Meteorological Administration (KMA) rainfall recording sites. Comparisons of RMSE (root mean squared error) and RRMSE (Relative RMSE) of rainfall intensities computed from IDF by CDF and IDF by REG show that IDF by CDF is more accurate than IDF by REG. In order to accommodate the effect of the recent intensive rainfall of Korea, the rainfall intensities computed by the two IDF curves are compared with that by at-site frequency analysis using the rainfall data recorded by 2006, and the result from IDF by CDF show the better performance than that from IDF by REG. As a result, it can be said that the suggested IDF by CDF curve would be the more efficient IDF curve than that computed by regression analysis and could be applied for Korean rainfall data.

• Journal of Animal Environmental Science
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• v.2 no.1
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• pp.41-52
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• 1996

This experiment was carried out to study the effect of sprinkler and fan cooling system on the physiological parameter, milk production and milk composition for Holstein cows in hot, humid climates. Thirty cows were assigned to one of two sections of open-sided loose barn. Water nozzles of sprinkler system were spaced in line at 1.2m intervals. Forced air was provided by 85cm diameter fans at rate of 3.4㎥/sec. The results obtained from these experiments are as follows: 1. There was no significant difference in meteorological data between control and fan + sprinkler cooling system(treatment group). 2. Skin temperature and rectal temperature of the treatment group were significantly lower than those of the control group (32.96 : 39.53$^{\circ}C$ vs 34.02 : 41.21$^{\circ}C$ respectively) (P<0.05). 3. Serum cortisol concentration of the treatment group(0.90$\mu\textrm{g}$/dL) was lower than that of control group(1.44$\mu\textrm{g}$/dL)(P<0.05). 4. Milk production of cows cooled with a sprinkler and fan cooling system was significantly higher than that of no cooling system (P<0.0l). 5. Lactose, protein and solid-not-fat content of milk were not changed by the treatments. Milk fat content of the control(3.23%) was low compared with the treatment group(3.38%). Somatic cell count was reduced by 26.63% in the treatment. The results indicate that a sprinkler and fan cooling systems can provide an effective means to relieve heat stress and enhance productivity of lactating Holstein cows during hot and humid summer season.

• Journal of the Korean earth science society
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• v.21 no.3
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• pp.287-301
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• 2000

In order to investigate the factors and processes affecting the vertical distributions of ozone, we analyzed the ozone profile data measured using ozonesonde from 1995 to 1997 at Pohang city, Korea. In the course of our study, we analyzed temporal and spatial distribution characteristics of ozone at four different heights: surface (100m), troposphere (10km), lower stratosphere (20km), and middle stratosphere (30km). Despite its proximity to a local, but major, industrial complex known as Pohang Iron and Steel Co. (POSCO), the concentrations of surface ozone in the study area were comparable to those typically observed from rural and/or unpolluted area. In addition, the findings of relative enhancement of ozone at this height, especially between spring and summer may be accounted for by the prevalence of photochemical reactions during that period of year. The temporal distribution patterns for both 10 and 20km heights were quite compatible despite large differences in their altitudes with such consistency as spring maxima and summer minima. Explanations for these phenomena may be sought by the mixed effects of various processes including: ozone transport across two heights, photochemical reaction, the formation of inversion layer, and so on. However, the temporal distribution pattern for the middle stratosphere (30km) was rather comparable to that of the surface. We also evaluated total ozone concentration of the study area using Brewer spectrophotometer. The total ozone concentration data were compared with those derived by combining the data representing stratospheric layers via Umkehr method. The results of correlation analysis showed that total ozone is negatively correlated with cloud cover but not with such parameter as UV-B. Based on our study, we conclude that areal characteristics of Pohang which represents a typical coastal area may be quite important in explaining the distribution patterns of ozone not only from surface but also from upper atmosphere.

• Atmosphere
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• v.20 no.4
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• pp.467-482
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• 2010

In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.

• Atmosphere
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• v.23 no.1
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• pp.85-92
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• 2013

We estimate atmospheric radiative heating effect of aerosols, based on AErosol RObotic NETwork (AERONET) and lidar observations and radiative transfer calculations. The column radiation model (CRM) is modified to ingest the AERONET measured variables (aerosol optical depth, single scattering albedo, and asymmetric parameter) and subsequently calculate the optical parameters at the 19 bands from the data obtained at four wavelengths. The aerosol radiative forcing at the surface and the top of the atmosphere, and atmospheric absorption on pollution (April 15, 2001) and dust (April 17~18, 2001) days are 3~4 times greater than those on clear-sky days (April 14 and 16, 2001). The atmospheric radiative heating rate (${\Delta}H$) and heating rate by aerosols (${\Delta}H_{aerosol}$) are estimated to be about $3\;K\;day^{-1}$ and $1{\sim}3\;K\;day^{-1}$ for pollution and dust aerosol layers. The sensitivity test showed that a 10% uncertainty in the single scattering albedo results in 30% uncertainties in aerosol radiative forcing at the surface and at the top of the atmosphere and 60% uncertainties in atmospheric forcing, thereby translated to about 35% uncertainties in ${\Delta}H$. This result suggests that atmospheric radiative heating is largely determined by the amount of light-absorbing aerosols.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.107-120
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• 2017

There are many wildfire risk indices worldwide, but objective comparisons between such various wildfire risk indices and surface dryness indices have not been conducted for the wildfire cases in Korea. This paper describes a sensitivity analysis on the wildfire risk indices and surface dryness indices for Korea using LDAPS(Local Analysis and Prediction System) meteorological dataset on a 1.5-km grid and MODIS(Moderate-resolution Imaging Spectroradiometer) satellite images on a 1-km grid. We analyzed the meteorology-based wildfire risk indices such as the Australian FFDI(forest fire danger index), the Canadian FFMC(fine fuel moisture code), the American HI(Haines index), and the academically presented MNI(modified Nesterov index). Also we examined the satellite-based surface dryness indices such as NDDI(normalized difference drought index) and TVDI(temperature vegetation dryness index). As a result of the comparisons between the six indices regarding 120 wildfire cases with the area damaged over 1ha during the period between January 2013 and May 2017, we found that the FFDI and FFMC showed a good predictability for most wildfire cases but the MNI and TVDI were not suitable for Korea. The NDDI can be used as a proxy parameter for wildfire risk because its average CDF(cumulative distribution function) scores were stably high irrespective of fire size. The indices tested in this paper should be carefully chosen and used in an integrated way so that they can contribute to wildfire forecasting in Korea.