• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1536-1541
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• 2018

For effective electricity consumption in urban railway station such as peak load shaving, it is important to know each electrical load pattern by various usage. The total electricity consumption in the urban railway substation is already measured in Korea, but the electricity consumption for each usage is not measured. The author proposed the deep learning method to estimate the electrical load pattern for each usage in the urban railway substation with public data such as weather data. GRU (gated recurrent unit), a variation on the LSTM (long short-term memory), was used, which aims to solve the vanishing gradient problem of standard a RNN (recursive neural networks). The optimal model was found and the estimation results with that were assessed.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.169-174
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• 2000

The analysis of irrigation water use characteristics from a pumping station is implemented. Sangjoo district was selected as a test area. Irrigation water are varied according to manners of water manager, weather change and irrigation system changes such as the repair and improvement of irrigation canal, installation of an auxiliary water sources and canal structure. From the results, average irrigation water is 1,136mm during irrigation period from 1987 to 1997 in sanjoo district. After improvement of irrigation district, irrigation water was increased 45% as average water use in this area.

• International Journal of Industrial Entomology and Biomaterials
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• v.25 no.2
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• pp.163-169
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• 2012

A decrease in pass ratio of Korean exporting pears causes several negative effects including an increase in pesticide dependency. In this study, we attempted to establish the pest forecasting management system, composed of weekly field forecasting by pear farmers, meteorological data obtained by automatic weather station (AWS), newly designed internet web page ($\underline{http://pearpest.jnu.ac.kr/}$) as information collecting and providing ground, and information providing service. The weekly field forecasting information on major pear diseases and pests was collected from the forecasting team composed of five team leaders from each pear exporting complex. Further, an abridged weather information for the prediction of an infestation of major disease (pear scab) and pest (pear psylla and scale species) was obtained from an AWS installed at Bonghwang in Naju City. Such information was then promptly uploaded on the web page and also publicized to the pear famers specializing in export. We hope this pest forecasting management system increases the pass ratio of Korean exporting pears throughout establishment of famer-oriented forecasting, inspiring famers' effort for the prevention and forecasting of diseases and pests occurring at pear orchards.

• Journal of Environmental Impact Assessment
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• v.12 no.4
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• pp.281-290
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• 2003

The influence of land-use type on surrounding temperature was studied the relationships between land-use types and the air condition analyzing AWS (Automatic Weather Station) data of Seoul from KMA (Korea Meteorological Administration). The distribution of air temperature by land-use type has been influenced by the different heating and cooling rates. The difference of heating rates depending on the land-use type was largest at 2~3hours after sunrise and the difference of cooling rates was largest from 2hours before sunset to 2hours after sunset with its maximum at sunset. The difference of cooling rates is greatest in a clear and calm weather situation and the large difference in cooling rates between the green areas and built-up area is up to $1.5^{\circ}C/h$. By season, the difference of cooling rates is largest in fall and in turn spring, winter and summer. In a cloudy or rainy day, the difference in heating and cooling rates on land-use type is not distinct but the tendency is similar to a clear day. In all seasons, the rate of difference occurrence of the daily range of temperature between the green areas and built-up area was large, especially fall. In a fall with a clear and calm day, the magnitude of the daily range of temperature between the green areas and built-up area was largest.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.620-622
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• 2018

The need for particulate matter prediction algorithms has increased as social interest in the effects of human on particulate matter increased. Many studies have proposed statistical modelling and machine learning techniques based prediction models using weather data, but it is difficult to accurately set the environment and detailed conditions of the models. In addition, there is a need to design a new prediction model for missing data in domestic weather monitoring station. In this paper, fine dust prediction is performed using multi-layer perceptron network as a previous study for particulate matter prediction. For this purpose, a prediction model is designed based on weather data of three monitoring station and the suitability of the algorithm for particulate matter prediction is evaluated through comparison with actual data.

• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.71-80
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• 2019

Daily ahead forecast is necessary for the electricity balance between load and supply due to the variability renewable energy. Numerical weather prediction is usually employed to produce the solar irradiance as well as electric power forecast for more than 12 hours forecast horizon. UM-LDAPS model is the numerical weather prediction operated by Korea Meteorological Administration and it generates the 36 hours forecast of hourly total irradiance 4 times a day. This study attempts to evaluate the model performance against the in situ measurements at 37 ground stations from January to May, 2013. Relative mean bias error, mean absolute error and root mean square error of hourly total irradiance are averaged over all ground stations as being 8.2%, 21.2% and 29.6%, respectively. The behavior of mean bias error appears to be different; positively largest in Chupoongnyeong station but negatively largest in Daegu station. The distinct contrast might be attributed to the limitation of microphysics parameterization for thick and thin clouds in the model.

• Atmosphere
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• v.24 no.2
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• pp.159-171
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• 2014

This study investigated the temporal and spatial characteristics of summertime (June-August) precipitation over Korean peninsula, using Korea Meteorological Administration (KMA)is Automated Synoptic Observing System (ASOS) data for the period of 1973-2010 and Automatic Weather System (AWS) data for the period of 1998-2010.The authors looked through climatological features of the summertime precipitation, then examined the degree of locality of the precipitation, and probable precipitation amount and its return period of 100 years (i.e., an extreme precipitation event). The amount of monthly total precipitation showed increasing trends for all the summer months during the investigated 38-year period. In particular, the increasing trends were more significant for the months of July and August. The increasing trend of July was seen to be more attributable to the increase of precipitation intensity than that of frequency, while the increasing trend of August was seen to be played more importantly by the increase of the precipitation frequency. The e-folding distance, which is calculated using the correlation of the precipitation at the reference station with those at all other stations, revealed that it is August that has the highest locality of hourly precipitation, indicating higher potential of localized heavy rainfall in August compared to other summer months. More localized precipitation was observed over the western parts of the Korean peninsula where terrain is relatively smooth. Using the 38-years long series of maximum daily and hourly precipitation as input for FARD2006 (Frequency Analysis of Rainfall Data Program 2006), it was revealed that precipitation events with either 360 mm $day^{-1}$ or 80 mm $h^{-1}$ can occur with the return period of 100 years over the Korean Peninsula.

• Journal of Environmental Impact Assessment
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• v.12 no.2
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• pp.73-86
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• 2003

In this study, we performed 8 times of water quality sampling and continuous measurement of flow to identify wastewater flow characteristics for wastewater treatment basins of Namyangju city. The field survey has been conducted 6 times in dry weather period and 2 times in wet weather period. Each survey conducted 24-hr water quality sampling in the interval of 2-hr. From the analysis of flow data and water quality data, the following conclusions can be drawn. For Namyangju-1 station, which represents residential and commercial mixed area, flow rises early in the morning before office-going hour and moves up and down within narrow range, and lasted after office-leaving hour, resulting from continuous commercial activity. In case of Namyangju-5 station representing community and Namyangju- 6 station representing residential area, the flow immediately falls down after rising early in the morning and later rises again at the office-leaving hour, and arrives at peak flows around late evening. In the analysis of wastewater characteristics for weekdays and weekends, without landuse types the flow rate of weekends is higher than that of weekdays because it reflects population, being not contributed to generate wastewater during the working hours of weekdays, stay home and produce wastewater for weekends period.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.582-587
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• 2020

Recently, disasters caused by extreme weather and the damage caused by them are increasing worldwide. The interest in disasters, such as earthquakes, typhoons, and ground subsidence, is increasing in Korea. Korea has enacted a special law based on disaster management, and has built monitoring systems for individual facility units by building precision sensors and related systems to measure the displacement status of long bridges and high-rise composite buildings. On the other hand, the application of a real-time monitoring system is insufficient for slopes, open-pit mines, small and medium structures due to weather, measurement methods, cost, and constant monitoring difficulties. In this study, the displacement monitoring method using the total station was studied and the applicability was suggested through the experiment. Through the research, the concept and operation flow of a monitoring system that can measure the displacement of the terrain or the structure using the total station was presented. The monitoring system allows the user to select the location and operation method of the equipment so that the equipment can be installed according to the site situation, and set the number of observations, the period, and the observation range of the object. Using the experiment on the monitoring system, the station was monitored with precision within 5mm, and it was suggested that the displacement of the object can be monitored using the total station. Further research will be needed to assess the applicability of monitoring to real slopes and structures.