• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.47-54
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• 2013

Climate change is the most direct threatening factors in sustaining agricultural productivity. It is necessary to reduce the damages from the natural hazards such as flood, drought, typhoons, and snowstorms caused by climate change. Through the vulnerability assessment to adapt the climate change, it is possible to analyze the priority, feasibility, effect of the reduction policy. For the vulnerability assessment, broad amount of weather data for each meterological station are required. Making the database management system for the meteorologic data could troubleshoot of the difficulties lie in handling and processing the weather data. In this study, we generated the meteorologic data retrieval system (MetSystem) for climate change vulnerability assessment. The user interface of MetSystem was implemented in the web-browser so as to access to a database server at any time and place, and it provides different query executions according to the criteria of meteorologic stations, temporal range, meteorologic items, statistics, and range of values, as well as the function of exporting to Excel format (*.xls). The developed system is expected that it will make it easier to try different analyses of vulnerability to natural hazards by the simple access to meteorologic database and the extensive search functions.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.134-147
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• 2015

This paper presents the applications of Kriging spatial interpolation methods for meteorologic variables, including temperature and relative humidity, in regions of Vietnam. Three types of interpolation methods are used, which are as follows: Ordinary Kriging, Universal Kriging, and Universal Kriging plus Digital Elevation model correction. The input meteorologic data was collected from 98 ground weather stations throughout Vietnam and the outputs were interpolated temperature and relative humidity gridded fields, along with their error maps. The experimental results showed that Universal Kriging plus the digital elevation model correction method outperformed the two other methods when applied to temperature. The interpolation effectiveness of Ordinary Kriging and Universal Kriging were almost the same when applied to both temperature and relative humidity.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.15-20
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• 1999

This paper presents a climate change information system that provides the data and information about climate change. The system shows the meteorologic data observed, climate change research institutes, and research programs. As the result of analyzing the meteorologic data, it also provides users with the climate change information using the graphic and multimedia data. The terminology retrieval and dictionary facility in the climate change can be useful to the users who are interested in the climate change.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1105-1115
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• 2015

Big data analysis for disaster have been recently started especially to text data such as social media. Social data usually supports for the final two stages of disaster management, which consists of four stages: prevention, preparation, response and recovery. Otherwise, big data analysis for meteorologic data can contribute to the prevention and preparation. This motivated us to review big data technologies dealing with non-text data rather than text in natural disaster area. To this end, we first explain the main keywords, big data, data mining and machine learning in sec. 2. Then we introduce the state-of-the-art machine learning techniques in meteorology-related field sec. 3. We show how the traditional machine learning techniques have been adapted for climatic data by taking into account the domain specificity. The application of these techniques in natural disaster response are then introduced (sec. 4), and we finally conclude with several future research directions.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.993-1001
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• 2015

Comparing to the other air pollutants like $SO_2$, CO, the number of exceedance of the ozone national ambient air quality standard(NAAQS) and the ozone warning increased recently in Busan. The purpose of this study is to find out the preliminary symptoms for high ozone days in Busan area. In order to find out the preliminary symptoms, the hourly ozone data at air quality monitoring stations and the hourly meterological parameters at Busan regional meteorological 2007 to 2013 were used for the analysis. Averaged daily max ozone concentration was the highest(0.055 ppm) at Noksan and Youngsuri in the ozone season from 2007 to 2013. The horizontal distributions of daily max. ozone including all stations in Busan at high ozone days(the day exceeding 0.1 ppm of ozone concentration at least one station) were classified from two to five clusters by hierarchial cluster analysis. The meteorological variables showing strong correlation with daily max. ozone were the daily mean dew point temperature, averaged total insolation, the daily mean relative humidity and the daily mean cloud amount. And the most frequent levels were $19-23^{\circ}C$ in dew point temperature, $21-24 MJ/m^2$ in total insolation on the day before, $2.6-3.0 MJ/m^2$ on the very day, 67-80% in relative humidity and 0-3 in cloud amount.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.2
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• pp.167-174
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• 2009

The AIRWARE System was developed from one of the EUREKA PROJECT E!3266-EUROENVIRON WEBAIR System. The AIRWARE can nowcast and forecast the air quality of Seoul and Gyeonggi-do regions. To nowcast and forecast concentration of pollutants, MM5, AERMOD/CAMx, and SMOKE Models were used for each meteorologic data, measured data, and emission data. All DB were constructed for 2001 year. The episode analysis and time series analysis were accomplished to analyze the AIRWARE reliability. The simulated results were very well agreed with measured result for measured pollutants and meteorological data. The developed AIRWARE system can analyze with real-time, support web-based air quality information. This information can used with policy data to manage the air quality and prepare reduction plan in air impact assessment or air environmental plan.

• Journal of IKEEE
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• v.25 no.1
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• pp.109-115
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• 2021

In this paper, the fine dust detecting terminal which can transmit data in real time was developed. The terminal used a wide spreading LTE network and was powered by solarcell and battery for easy installation and independent operation, because it did not need the wired power grid or wired communication network. The data showed the possibility of forecasting fine dust changes by analyzing with the data from public meteorologic data. The developed terminal will be helpful for predicting and analyse fine dust's more precise flow and effect on environment with an easy installation on any places.

• Ocean and Polar Research
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• v.31 no.4
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• pp.401-414
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• 2009

Yellow Sea Buoy (YSB) was moored in the center of the Yellow Sea at 35$^{\circ}$51'36"N, 124$^{\circ}$34'42"E, on 12 September 2007. YSB is a large buoy of 10 m diameter, and as such is more durable against collision by ships and less likely to be lost or removed by fishing nets compared to small ordinary buoys of 2.3 m diameter. YSB is equipped with 12 kinds of oceanic and meteorologic instruments, and transfers its realtime observation data to KORDI through ORBCOMM system every 1 hour. Data on ocean winds, air temperature, air pressure, and sea temperature appear to be accurate, while water property sensors (AAQ1183), which are sensitive to fouling, are producing errors. YSB (2007), Ieodo ocean research station (2003), and Gageocho ocean research station, which was completed in October 2009, will establish the 2 degrees interval by latitude in the Yellow Sea, and they will contribute though the 'Operational Oceanography System' as the important realtime observation network.

• Korean Journal of Medicinal Crop Science
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• v.28 no.3
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• pp.221-228
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• 2020

Background: Angelica gigas Nakai, that belong to the Umbelliferae family, is one of the traditional medicinal plants in Korea. Its roots have been used to treat gynecological diseases. In this study, growth characteristics and index components were compared with the forest microclimate at several forest sites. Methods and Results: A. gigas was planted in three climatic zones according to the temperature (southern temperature zone - Hamyang, central temperature zone - Bonghwa, and northern temperature zone - Jeongseon) and growth characteristics were investigated in comparison with the forest microclimate. Our results indicated that the root diameter and length, and fresh and dry weight were the highest in Jeongseon. The total content of decursin was the highest in Jeongseon (9.52%), followed by those in Hamyang (8.07%) and Bonghwa (7.48%), respectively. Additionally, the yield of decursin (1.39 g) was the highest in Jeongseon. Conclusions: The yield and index components were influenced by the microclimate in the forests, and it was assumed that high altitude and low temperature affected the increase in growth and index components. These results will be useful as basic data to study the correlation among environmental conditions, growth, and index components.

• Journal of environmental and Sanitary engineering
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• v.7 no.2
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• pp.141-152
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• 1992

Simple correlation analysis, factor analysis, and multi-verite analysis have been performed to analyze the relationship between air pollution and meteorological factors for air pollution and meteorological data measured at Kwanghwamun in Seoul during the period of one year (January 1990" December 1990). As a result of simple correlation and factor analysis, $SO_2$, TSP and CO concentrations have shown high negative correlation with temperature and among these indicating that these are related with pollutants emission trend based upon heating fuel usage. Ozone has a good correlation with solar radiation and relative humidity to have a closed relation with $0_3$ generation reaction mechanism. The result of multi-variate correlation analysis shows that the concentration of $SO_2$ and CO are adequate for correlation model with ambient temperature and wind speed and 0$_{3}$ concentrations are adequate for that with solar radiation and wind speed. $SO_2$ and CO levels are considered to be affected first of all by heating fuel usage as a emission source and wind speed as a dispersion effect. The $SO_2$ concentration in the condition that the temperature fall below zero is explained by multiplicative model with wind speed, only one variable.