• International Journal of Highway Engineering
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• v.19 no.6
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• pp.147-153
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• 2017

PURPOSES : This research aims to estimate the occurrence of hydroplaning on roads based on the road alignment types and rainfall intensity in Seoul. METHODS : Three types of data were used for estimation of hydroplaning in this study. The Inner Circulation Road (12.5 km) to the Bukbu Expressway (7.4 km) in Seoul was selected as the test road and data was collected for road information using a probe-vehicle. Precipitation was observed from Automatic Weather System in Seoul. These data were interpolated by applying Inverse Distance Weighted Methodology for hydroplaning estimation. Finally, the water depth information of the roads was observed using an RCM411 device. RESULTS : This study demonstrated that the cross slope with small-angle-tilt or vertical section with large-angle-tilt are the primary factors causing hydroplaning on the roads. The flow velocity on steep slope is high; however, large drainage lengths result in hydroplaning on the roads. CONCLUSIONS : This result can contribute towards the reduction of car accidents on rainy days. Furthermore, information regarding hydroplaning can be delivered to drivers more rapidly and precisely in the future.

• Journal of Wind Energy
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• v.14 no.3
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• pp.14-24
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• 2023

The significance of renewable energy has been on the rise, as evidenced by the 3020 renewable energy plan and the 2050 carbon neutrality strategy, which seek to advance a low-carbon economy by implementing a power supply strategy centered around renewable energy sources. This study examines the wind resources on the west coast of South Korea and confirms the potential for wind power generation in the area. Wind speed data was collected from 22 automatic weather system stations and four light house automatic weather system stations provided by the Korea Meteorological Administration to evaluate potential sites for wind farms. Weibull distribution was used to analyze the wind data and calculate wind power density. Annual energy production and capacity factors were estimated for 15-20 MW-class large wind turbines through the height correction of observed wind speeds. These findings offer valuable information for selecting wind power generation sites, predicting economic feasibility, and determining optimal equipment capacity for future wind power generation sites in the region.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.119-127
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• 2014

A very high resolution weather analysis system (VHRAS) of 50 m horizontal resolution is established based on LAPS. VHRAS utilizes the 3 hourly forecast data of the Unified Model (UM) of the Korea Meteorological Administration (KMA) with the horizontal resolution of 12 km as initial guess fields. The analysis system ingests the automatic weather station (AWS) data as input observations. The analysis system operates every hour for Seoul, Korea region in real time basis. It takes less than 10 minutes for one analysis cycle. The size of grid of the analysis domain is $800{\times}660$, respectively. The analysis results from December 2010 to February 2011 showed that the mean biases of temperature, maximum and minimum temperature were -0.07, 1.6, $0.2^{\circ}C$, respectively. The temperature in the central part of the city revealed relatively higher value than that of the surrounding mountainous areas, which showed a heat island feature. The heat island appears in zonal direction since the central city region is developed along a large river. Along the heat island, the eastern region was warmer than the western region. The warmer temperature in the western part of the heat island was caused by anthropogenic heat change in conjunction with the change of land use. This system will provide more reliable weather data and information in Seoul.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.57-66
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• 2001

This study used four theoretical models, such as two-point linear model, linear regression model, quadratic regression model and cubic regression model which are presented from The Ministry of Science and Technology, for extraction of urban surface temperature from Landsat TM band 6 image. Through correlation and regression analysis between result of four models and AWS(automatic weather station) observation data, this study could verify spatial distribution characteristic of urban surface temperature using GIS spatial analysis method. The result of analysis for surface temperature by landcover showed that the urban and the barren land belonged to the highest surface temperature class. And there was also -0.85 correlation in the result of correlation analysis between surface temperature and NDVI. In this result, the meteorological environmental characteristics wuld be regarded as one of the important factor in urban planning.

• Atmosphere
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• v.23 no.4
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• pp.413-424
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• 2013

Urban Heat Island (UHI) intensity is one of vital parameters in studying urban boundary layer meteorology as well as urban planning. Because the UHI intensity is defined as air temperature difference between urban and rural sites, an objective sites selection criterion is necessary for proper quantification of the spatial variations of the UHI intensity. This study quantified the UHI intensity and its spatial pattern, and then analyzed their connections with urban structure and metabolism in Seoul metropolitan area where many kinds of land use and land cover types coexist. In this study, screen-level temperature data in non-precipitation day conditions observed from 29 automatic weather stations (AWS) in Seoul were analyzed to delineate the characteristics of UHI. For quality control of the data, gap test, limit test, and step test based on guideline of World Meteorological Organization were conducted. After classifying all stations by their own local climatological properties, UHI intensity and diurnal temperature range (DTR) are calculated, and then their seasonal patterns are discussed. Maximum UHI intensity was $4.3^{\circ}C$ in autumn and minimum was $3.6^{\circ}C$ in spring. Maximum DTR appeared in autumn as $3.8^{\circ}C$, but minimum was $2.3^{\circ}C$ in summer. UHI intensity and DTR showed large variations with different local climate zones. Despite limited information on accuracy and exposure errors of the automatic weather stations, the observed data from AWS network represented theoretical UHI intensities with difference local climate zone in Seoul.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.5
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• pp.471-479
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• 2015

This study was conducted to make use of Korea Meteorological Administration(KMA)'s Automatic Weather Station(AWS) data to operate smart green greenhouse. A Web-based KMA AWS data receiving system using JAVA and APM_SETUP 8 on windows 7 platform was developed. The system was composed of server and client. The server program was developed by a Java application to receive weather data from the KMA every 30 minutes and to send the weather data to smart greenhouse. The client program was developed by a Java applets to receive the KMA AWS data from the server every 30 minutes through communicating with the server so that smart greenhouse could recognize the KMA AWS data as the ambient weather information. This system was evaluated by comparing with local weather data measured by Inc. Ezfarm. In case of ambient air temperature, it showed some difference between virtual data and measured data. But, the average absolute deviation of the difference has a little difference as less than 2.24℃. Therefore, the virtual weather data of the developed system was considered available as the ambient weather information of the smart greenhouse.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.346-349
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• 2018

In North-East asian countries, laver cultivation has been an important marine industry in coastal areas as well as fishery because laver (Porphyra) is nutrient-rich food and has been used in many Asian cuisines. Laver is characterized by high concentrations of fiber and minerals, a low fat content, and, in some cases, relatively high protein levels. In this paper we inplimented design of fully automatic laver harvesting, nowdays most peoples are used to collect a laver harvesting by human, it is very defficult working, due to wind, waves, and the weather conditions which is hard to stand on the ship and holding the seaweed nets it can be injurced human, this is the reason to we are developed automatic harvesting method, in this project we proposed automatic harvesting collect method which is operated without human. Mainly we design and developed automated ship, This ship is devided in to three parts frist part is supporting roller, second part is drum screener, thried part is lifting mechanism. Thise are operated with hydro pnumatic equimpment, this divice are control with micro controller. The system prototype has implemented and satisfied by the performance to realize the further level.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.479-484
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• 2020

Foreign object debris (FOD) is a generic term for all substances that may pose a threat to aircraft operations on a runway. In the past, FOD detection and collection methods using human resources were very inefficient in terms of efficiency and economics, so it is essential to develop an unmanned FOD detection system suitable for domestic use. In this paper, the fixed FOD automatic detection system and mobile FOD automatic detection system using EO camera and radar were studied and developed at the Taean airfield of Hanseo University, and fixed and mobile method were operated to confirm that automatic FOD detection in the runway of the airfield is possible regardless of illumination and weather conditions.