• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.75-88
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• 2017

This study analyzed wind flows based on spatial and geomorphological characteristics of Daegu Metropolitan City. A three-stage analysis was performed, starting with a comparison of meteorological relationships between local wind direction (synoptic wind) and local wind flow. In the second stage the study area was subdivided into districts and suburban districts to analyze the relative change of local wind flow. In stage three, the formation of wind corridor for local wind flow, wind flow for the entire urban space, and spatial relationships between flows were verified comparatively using KLAM_21. Three results are notable, the first of which is a low correlation between synoptic wind of a region, and local wind, flow in terms of meteorology. Secondly, observations of local wind flow at five downtown districts and two suburban districts showed that there were diverse wind directions at each measurement point. This indicates that the spatial and geomorphological characteristics of areas neighboring the measurement points could affect the local wind flow. Thirdly, verifying the results analyzed using KLAM_21, compared to Atomatic Weather System(AWS) measurement data, confirmed the reliability of the numerical modelling analysis. It was determined that local wind flow in a city performs a spatial function and role in ameliorating the urban heat island phenomena. This indicates that, when an urban planning project is designed, the urban heat island phenomena could be ameliorated effectively and sustainably if local wind flow caused by immediate spatial and geomorphological characteristics is confirmed systematically and techniques are intentionally applied to connect the flows spatially within areas where urban heat islands occur.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.290-305
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• 2015

To improve the practicality of 'Early warning service about agrometeorological weather hazards' and operation efficiency to deliver site-specific about a lot of land unit possibility of weather hazard occurrence with the suitable counterplan to farmer, site-specific early warning service system that was built at the National Academy of Agricultural Science in Korea passed some of the error supplementation and service's stabilization stage during operation period for trial services from October 2014 to March 2015. Field service system covered about 470 volunteered farmer and 950 lots in Seomjin river downstream areas (part of Gwangyang-si, Hadong-gun, Gurye-gun). This system (Two track system) consists of early warning system (a lot of land unit) to inform farmer by individual text message and dispersal prior alert system that can see the jurisdiction's situation of local government. Individual text message about Seomjin river downstream that is our first study area was launched since $2^{nd}$ March 2015, and online site (http://www.agmet.kr) started business since April 2015. Service offers currently information of farm weather, farm weather hazard, nationwide weather risk and special weather alert, also our system will consistently expand the service target area and contents and improve the service quality until 2017 when our study finished. To prevent crops damage that was caused by crisis situation like farm weather and weather damage offer prior alert about agrometeorological weather harzard to volunteered farmer, thereby our study expects to help the reduction of farm's damage caused by weather derivatives.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.62.3-63
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• 2017

The Mars Atmosphere and Volatile (MAVEN) mission has been providing valuable information on the atmospheric loss of Mars since its launch in November 2013. The Neutral Gass and Ion Mass Spectrometer (NGIMS) onboard MAVEN, was developed to analyze the composition of the Martian upper atmospheric neutrals and ions depending on various space weather conditions. We investigate a variation of upper atmospheric ion densities depending on the interplanetary coronal mass ejections (ICMEs). It is known that the Mars has a very weak global magnetic field, so upper atmosphere of Mars has been strongly affected by the solar activities. Meanwhile, a strong crustal magnetic field exists on local surfaces, so they also have a compensating effect on the upper atmospheric loss outside the Mars. The weak crustal field has an influence up to 200km altitude, but on a strong field region, especially east longitude of $180^{\circ}$ and latitude of $-50^{\circ}$, they have an influence over 1,400km altitude. In this paper, we investigated which is more dominant between the crustal field effect and the ICME effect to the atmospheric loss. At 400km altitude, the ion density over the strong crustal field region did not show a significant variation despite of ICME event. However, over the other areas, the variation associated with ICME event is far more overwhelming.

• The Journal of Information Systems
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• v.29 no.3
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• pp.35-52
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• 2020

Purpose Local governments in each region actively hold local festivals for the purpose of promoting the region and revitalizing the local economy. Existing studies related to local festivals have been actively conducted in tourism and related academic fields. Empirical studies to understand the effects of latent variables on local festivals and studies to analyze the regional economic impacts of festivals occupy a large proportion. Despite of practical need, since few researches have been conducted to predict the number of visitors, one of the criteria for evaluating the performance of local festivals, this study developed a model for predicting the number of visitors through various observed variables using a machine learning algorithm and derived its implications. Design/methodology/approach For a total of 593 festivals held in 2018, 6 variables related to the region considering population size, administrative division, and accessibility, and 15 variables related to the festival such as the degree of publicity and word of mouth, invitation singer, weather and budget were set for the training data in machine learning algorithm. Since the number of visitors is a continuous numerical data, random forest, Adaboost, and linear regression that can perform regression analysis among the machine learning algorithms were used. Findings This study confirmed that a prediction of the number of visitors to local festivals is possible using a machine learning algorithm, and the possibility of using machine learning in research in the tourism and related academic fields, including the study of local festivals, was captured. From a practical point of view, the model developed in this study is used to predict the number of visitors to the festival to be held in the future, so that the festival can be evaluated in advance and the demand for related facilities, etc. can be utilized. In addition, the RReliefF rank result can be used. Considering this, it will be possible to improve the existing local festivals or refer to the planning of a new festival.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.2
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• pp.119-125
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• 2008

The aim of this study was to determine the characteristics of wave transformation in the shallow water of the Nakdong River estuary due to variations in air pressure, air temperature, wind speed, and wind direction. We analyzed the correlation between weather factors and wind waves in offshore regions near Geoje Island and the Nakdong River estuary in April and May 2007. The weather and wind wave data were obtained from the automatic ocean observation buoy near Geoje Island operated by the Korean Meteorological Administration (KMA). For the estuary region, the wind wave information was the result of field observations, and weather data were obtained from the Busan Meteorological Station. Field observations of water waves in April and May showed that the maximum wave height decreased by about 2.2 m. M oreover, wave height decreased significantly by about 1.3 m due to the reduction in wave energy caused by the water waves propagating from Geoje buoy to the Nakdong River estuary. We conclude that offshore or wind waves coming into the Nakdong River estuary showed considerable height variation due to the prevailing weather conditions, especially wind speed and direction. In particular, headwinds tended to decrease the wave size in inverse proportion to the wind speed.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.55-70
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• 2001

It was unusual crop weather for 1998 and 1999 compared with normal in Korea. The consecutive days of the optimum ripening period for rice plant that had daily mean temperature 21~23$^{\circ}C$ for 40 days after flowering, increased with long anomalies in 1998~99. The air temperature during ripening period was much higher than the optimum temperature and lower sunshine hour than norm in the local adaptability tests of newly developed rice lines during those years. In response of rice cultivation to warming and cloudy weather during crop season, the yield shall be decreased. Most scientists agree that the rate of heating is accelerating and temperature change could become increasingly disruptive. Weather patterns should also become more erratic. Agrometeorologists could be analyzed yearly variations of temperature, sunshine hour and rainfall pattern focused on transient agroclimate change for last a decade. Rice agronomists could be established taking advantage of real time agricultural meteorology information system for fertilization, irrigation, pest control and harvest. Also they could be analyzed the characteristics of flowering response of the recommended and newly bred rice cultivars for suitable cropping plan such as cultural patterns and sowing or transplanting date. Rice breeders should be deeply considered introducing the characteristics of basic vegetative type of flowering response like Togil rices as prospective rice cultivars corresponding to global warming because of the rices needed higher temperature at ripening stage than japonica rices, photoperiod-sensitive and thermo-sensitive ecotypes.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.439-439
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• 2015

The temporal and spatial relationship of the weather elements such as rainfall and temperature is closely linked to the streamflow simulation, especially, to the flood forecasting problems. For the study area, Imjin river basin, which has the specific characteristics in geography with river cross operation between North and South Korea, the meteorological information in the northern area is totally deficiency, lead to the inaccuracy of streamflow estimation. In the paper, this problem is solved by using the combination of global (such as soil moisture content, land use) and local hydrologic components data such as weather data (precipitation, evapotranspiration, humidity, etc.) for the model-driven runoff (surface flow, lateral flow and groundwater flow) data in each subbasin. To compute the streamflow in Imjin river basin, this study is applied the hydrologic model SURR (Sejong Univ. Rainfall-Runoff) which is the continuous rainfall-runoff model used physical foundations, originally based on Storage Function Model (SFM) to simulate the intercourse of the soil properties, weather factors and flow value. The result indicates the spatial variation in the runoff response of the different subbasins influenced by the input data. The dependancy of runoff simulation accuracy depending on the qualities of input data and model parameters is suggested in this study. The southern region with the dense of gauges and the adequate data shows the good results of the simulated discharge. Eventually, the application of SURR model in Imjin riverbasin gives the accurate consequence in simulation, and become the subsequent runoff for prediction in the future process.