• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.221-221
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• 2022

방재성능목표란 홍수, 호우 등으로부터 재해를 예방하기 위한 방재정책 등에 적용하기 위하여 처리 가능한 시간당 강우량 및 연속강우량의 목표로, 각 지자체별로 지역특성 및 경제여건 등을 고려하여 지역별 방재성능목표를 설정한다. 지역별 방재성능목표 기준을 설정하기 위해 전국을 168개 티센망으로 분류하고 69개 지점 확률강우량을 활용하여 지방자치단체별 확률강우량을 산정하고, 지방자치단체별 티센면적 비율을 감안하여 각 지자체별 방재성능목표 설정 기준을 마련한다. 이때 확률강우량 산정에 기상청에서 제공하는 종관기상관측(ASOS) 자료를 이용하는데, 종관기상관측(ASOS, Automated Synoptic Observing System)이란 종관규모의 날씨를 파악하기 위하여 정해진 시각에 모든 관측소에서 같은 시각에 실시하는 지상관측으로, 종관규모는 일기도에 표현되어 있는 고기압이나 저기압의 공간적 크기 및 수명을 말하며, 해당 지역의 현재 기상 실시간 제공 및 기상예보에 활용한다. 그러나 ASOS 자료로 산정한 확률강우량을 토대로 설정한 지역별 방재성능목표는 지배관측소개소 및 면적 비율에 따라 강우량이 실제 해당 지역에 내린 강우량에 비해 작거나 크게 산정되어 실제 강우량을 반영하지 못하는 문제가 발생한다. 이에 지진·태풍·홍수·가뭄 등 기상현상에 따른 자연재해를 막기 위해 실시하는 지상관측인 방재성능관측(AWS, Automatic Weather System)을 1997년부터 약 510여개 지점에 설치하여 기상관측자료를 구축하고 있으나, 관측자료가 30년 미만이므로 자료의 일관성 및 신뢰도 확보 등의 문제로 이용하고 있지 않다. 실제로 ASOS 관측소와 AWS 관측소의 시간 강우량 최댓값 차이가 큼에도 불구하고 행안부는 지역별 방재성능목표 수립을 위한 강우량 산정에서 AWS 관측소의 기록은 반영하지 않고 ASOS 관측소 기록만 적용하여 실제 해당 지역의 강우량을 반영하는 방재 대책을 수립하지 못하는 실정이다. 따라서 소규모 유역 및 재해영향평가 등의 경우 인근 지역에 AWS 관측소가 있을 경우, 해당지역의 기상 특성을 대변하는 자료로 보유관측년수가 30년 이상인 AWS 자료의 적극적인 활용이 필요할 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1859-1867
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• 2021

This study investigated seasonal characteristics of the particulate matter (PM) in the atmosphere and rainwater quality in Busan, South Korea, and evaluated the seasonal effect of PM₁₀ concentration in the atmosphere on the rainwater quality using multivariate statistical analysis. The concentration of PM in the atmosphere and meteorological observations(daily precipitation amount and rainfall intensity) are obtained from automatic weather systems (AWS) by the Korea Meteorological Administration (KMA) from March 2020 to August 2020. Rainwater samples (n = 216, 13 rain events) were continuously collected from the beginning of the precipitation using the rainwater collecting device at Pukyong National University. The samples were analyzed for pH, EC (electrical conductivity), water-soluble cations(Na⁺, Mg²⁺, K⁺, Ca²⁺, and NH₄⁺), and anions(Cl^-, NO₃^-, and SO₄^2-). The concentration of PM₁₀ in the atmosphere was steadily measured before and after the precipitation with a custom-built PM sensor node. The measured data were analyzed using principal component analysis (PCA) and Pearson correlation analysis to identify relationships between the concentration of PM₁₀ in the atmosphere and rainwater quality. In spring, the daily average concentration of PM₁₀ (34.11 ㎍/m³) and PM_2.5 (19.23 ㎍/m³) in the atmosphere were relatively high, while the value of daily precipitation amount and rainfall intensity were relatively low. In addition, the concentration of PM₁₀ in the atmosphere showed a significant positive correlation with the concentration of water-soluble ions (r = 0.99) and EC (r = 0.95) and a negative correlation with the pH (r = -0.84) of rainwater samples. In summer, the daily average concentration of PM₁₀ (27.79 ㎍/m³) and PM_2.5 (17.41 ㎍/m³) in the atmosphere were relatively low, and the maximum rainfall intensity was 81.6 mm/h, recording a large amount of rain for a long time. The results indicated that there was no statistically significant correlation between the concentration of PM₁₀ in the atmosphere and rainwater quality in summer.

• Journal of Biosystems Engineering
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• v.20 no.2
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• pp.162-172
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• 1995

The ventilation in greenhouse have been important for such as adjustment of temperature, supplying of the oxygen, prevention of the overhumidity, density adjustment of $CO_2$, discharge of harmfulness gas, etc. However, the general ventilation which had been used the quantitative control method in discharge of a property of air mechanism in greenhouse, and caused mainly in waste of the heating energy and growth obstacle of the vegetable. Therefore, this study was peformed to obtain more scientific ventilation method using by analysis and measurement of the isothermal lines according to opening of window ventilation in greenhouse, and the results are summarized as follows. 1. The ventilating amount was more influenced by rather opening amount of window than the ventilating time. 2. In window ventilation, the temperature in greenhouse was mostly changed within 5 minutes after ventilating not regard to the spot of opening, after about 10 minutes temperature became to equilibrium state under the respective ventilating conditions. 3. In opening of the skylight only, isothermal lines were complicated, therefore, a tall vegetable may be possible to damage by a cold-weather from the lower central port in greenhouse. 4. Isothermal lines were a tendency to simply in opening of a side window that may be more effective ventilation in kinds of the short vegetable. 5. In conditions of internal temperature>setting temperature>external temperature, a skylight can be suitable to open 10~20cm in order to the optimum ventilation in greenhouse. 6. In conditions of internal temperature>external temperature>setting temperature, opening of all the windows or both the side windows that can be suitable in order to obtain the optimum ventilation in greenhouse. 7. An effect of ventilation was the most excellent to open of all the windows or both the side windows, and it were also found orderly excellent to open of the side window and the skylight or the skylight only, to open of the side window only. 8. Temperature was varied as the equation of T=Tc+ (To-Tc)e-at, and the ranges of (a) values were limited within 0.34~0.68. 9. A variations of humidity were similar to that of temperature, s.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.3
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• pp.374-383
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• 2010

Microwave radar can penetrate cloud cover regardless of weather conditions and can be used day and night. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. Kim et al. (2009) have measured backscattering coefficients of paddy rice using L-, C-, X-band scatterometer system with full polarization and various angles during the rice growth period and have revealed the necessity of near-continuous automatic measurement to eliminate the difficulties, inaccuracy and sparseness of data acquisitions arising from manual operation of the system. In this study, we constructed an X-band automatic scatterometer system, analyzed scattering characteristics of paddy rice from X-band scatterometer data and estimated rice growth parameter using backscattering coefficients in X-band. The system was installed inside a shelter in an experimental paddy field at the National Academy of Agricultural Science (NAAS) before rice transplanting. The scatterometer system consists of X-band antennas, HP8720D vector network analyzer, RF cables and personal computer that controls frequency, polarization and data storage. This system using automatically measures fully-polarimetric backscattering coefficients of rice crop every 10 minutes. The backscattering coefficients were calculated from the measured data at a fixed incidence angle of $45^{\circ}$ and with full polarization (HH, VV, HV, VH) by applying the radar equation and compared with rice growth data such as plant height, stem number, fresh dry weight and Leaf Area Index (LAI) that were collected at the same time of each rice growth parameter. We examined the temporal behaviour of the backscattering coefficients of the rice crop at X-band during rice growth period. The HH-, VV-polarization backscattering coefficients steadily increased toward panicle initiation stage, thereafter decreased and again increased in early-September. We analyzed the relationships between backscattering coefficients in X-band and plant parameters and predicted the rice growth parameters using backscattering coefficients. It was confirmed that X-band is sensitive to grain maturity at near harvesting season.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• International Journal of Highway Engineering
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• v.15 no.2
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• pp.19-27
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• 2013

PURPOSES : This study aims to investigate the snow-melt effects of an underground electric heater's snow-melt system via a field performance test, for evaluating the suitability of the system for use on a concrete pavement. The study also investigates the effectiveness of dynamic measures for clearing snow after snowfall events. METHODS : In order to check the field applicability, in November 2010, specimens were prepared from materials used for constructing concrete pavements, and underground electric heating meshes (HOT-mesh) were buried at depths of 50 mm and 100 mm at the site of the Incheon International Airport Construction Research Institute. Further, an automatic heating control system, including a motion sensor and pavement-temperature-controlled sensor, were installed at the site; the former sensor was intended for determining snow-melt effects of the heating control system for different snowfall intensities. Pavement snow-melt effects on snowy days from December 2010 to January 2011 were examined by managing the electric heating meshes and the heating control system. In addition, data on pavement temperature changes resulting from the use of the heating meshes and heating control system and on the dependence of the correlation between the outdoor air temperature and the time taken for the required temperature rise on the depth of the heating meshes were collected and analyzed. RESULTS : The effects of the heating control system's preheat temperature and the hot meshes buried at depths of 50 mm and 100 mm on the melting of snow for snowfalls of different intensities have been verified. From the study of the time taken for the specimen's surface temperature to increase from the preheat temperature ($0^{\circ}C$) to the reference temperature ($5{\sim}8^{\circ}C$) for different snowfall intensities, the correlation between the burial depth and outdoor air temperature has been determined to be as follows: Time=15.10+1.141Depth-6.465Temp CONCLUSIONS : The following measures are suggested. For the effective use of the electric heating mesh, it should be located under a slab it may be put to practical use by positioning it under a slab. From the management aspect, the heating control system should be adjusted according to weather conditions, that is, the snowfall intensity.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.93-98
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• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.

• Atmosphere
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• v.15 no.4
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• pp.191-202
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• 2005

This study was conducted to estimate how vertically high and horizontally long a sea breeze occurred around Gangneung of the Korean peninsula would be reached to an inland. Geographically, gangneung is located on the center of the east coast shaping an arc, and a coastal line around gangneung has a form extending northwestward and southeastward, respectively. Therefore, an inflow of the northerly has similar effects of the sea breeze since a deep valley of Daegwallyeong, which is one of main ridges of the Taebaek mountains, not only reaches northeastward up to this region but also plays the part of the steering gear changing a wind direction from northerly to easterly, this is, the wind from sea. First of all, the study had defined the sea breeze as a wind blown from NNE to ESE, clockwise. And then, we analyzed characteristics of the sea breeze occurred around gangneung in view of the maximum wind speed and the wind direction for October 1st, 2003 through September 30th, 2004, the upper air database for May through June of 2004, and the wind vector database of AWS (Automatic Weather System). All meteorological information is collected at the weather station of gangneung and by the AWS which is being scattered around this region. Finally, the study figures out that how horizontally long a sea breeze would be reached depends on a level of the easterly inflow. At the first step of the inflow of the sea breeze, the wind from NNW blows into this region by keeping up the speed $3m{\cdot}s^{-1}$, and effects of the northerly are dominated with time and the wind at the inland blows out southwestward cause of the surface friction at the next step. On the other hand, there is no change of wind direction in the inflow at Daegwallyeong because a surface friction of there is smaller than around gangneung, relatively. In other word, the easterly blows toward Daegwallyeong. However, the wind speed is not higher than that of the coast around gangneung.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.155-169
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• 2016

In this study, we developed a multi-sensor blending short-term rainfall forecasting technique using radar and satellite data during extreme rainfall occurrences in Busan and Gyeongnam region in August 2014. The Tropical Z-R relationship ($Z=32R^{1.65}$) has applied as a optimal radar Z-R relation, which is confirmed that the accuracy is improved during 20mm/h heavy rainfall. In addition, the multi-sensor blending technique has applied using radar and COMS (Communication, Ocean and Meteorological Satellite) data for quantitative precipitation estimation. The very-short-term rainfall forecasting performance was improved in 60 mm/h or more of the strong heavy rainfall events by multi-sensor blending. AWS (Automatic Weather System) and MAPLE data were used for verification of rainfall prediction accuracy. The results have ensured about 50% or more in accuracy of heavy rainfall prediction for 1-hour before rainfall prediction, which are correlations of 10-minute lead time have 0.80 to 0.53, and root mean square errors have 3.99 mm/h to 6.43 mm/h. Through this study, utilizing of multi-sensor blending techniques using radar and satellite data are possible to provide that would be more reliable very-short-term rainfall forecasting data. Further we need ongoing case studies and prediction and estimation of quantitative precipitation by multi-sensor blending is required as well as improving the satellite rainfall estimation algorithm.

• Journal of Environmental Science International
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• v.17 no.9
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• pp.1053-1068
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• 2008

This study aims to produce fundamental database for Environment Impact Assessment by monitoring vertical structure of the atmosphere due to the mountain valley wind in spring season. For this, we observed surface and upper meteorological elements in Sangin-dong, Daegu using the rawinsonde and automatic weather system(AWS). In Sangin-dong, the weather condition was largely affected by mountains when compared to city center. The air temperature was low during the night time and day break, and similar to that of city center during the day time. Relative humidity also showed similar trend; high during the night time and day break and similar to that of city center during the day time. Solar radiation was higher than the city, and the daily maximum temperature was observed later than the city. The synoptic wind during the measurement period was west wind. But during the day time, the west wind was joined by the prevailing wind to become stronger than the night time. During the night time and daybreak, the impact of mountain wind lowered the overall temperature, showing strong geographical influence. The vertical structure of the atmosphere in Dalbi valley, Sangin-dong had a sharp change in air temperature, relative humidity, potential temperature and equivalent potential temperature when measured at the upper part of the mixing layer height. The mixing depth was formed at maximum 1896m above the ground, and in the night time, the inversion layer was formed by radiational cooling and cold mountain wind.