• 한국도로학회논문집
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• 제14권4호
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• pp.141-148
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• 2012

PURPOSES : This study demonstrates the need for the collection of road weather information in order to perform efficient snow removal works during the winter season. Snow removal operations are usually dependent upon weather information obtained from the Automatic Weather Station provided by the Korea Meteorological Administration. However, there are some difference between road weather and weather forecasts in their scope. This is because general weather forecasts are focused on macroscopic standpoints rather than microscopic perspectives. METHODS : In this study, the relationship between snow removal works and historical weather forecasts are properly analyzed to prove the importance of road weather information. We collected both weather data and snow removal works during winter season at "A" regional offices in Gangwon areas. RESULTS : Results showed that the validation of weather forecasts for snow removal works were depended on the height difference between AWS location and its neighboring roadway. CONCLUSIONS : Namely, it appears that road weather information should be collected where AWS location and its neighboring roadway have relatively big difference in their heights.

• 응용통계연구
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• 제22권1호
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• pp.221-235
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• 2009

This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.

• 한국물환경학회지
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• 제32권3호
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• pp.310-317
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• 2016

It has been a big problem to estimate rainfall for the studies of mud-debris flows because the estimated rainfall from the nearest AWS (Automatic Weather Station) can tend to be quite inaccurate at individual sites. This study attempts to improve this problem through accurate rainfall depth estimation by applying an artificial neural network with radar rainfall data. For this, three models were made according to utilizing methodologies of rainfall data. The first model uses the nearest rainfall, observing the site from an ungauged site. The second uses only radar rainfall data and the third model integrates the above two models using both radar and observed rainfall at the sites around the ungauged site. This methodology was applied to the metropolitan area in Korea. It appeared as though the third model improved rainfall estimations by the largest margin. Therefore, the proposed methodology can be applied to forecast mud-debris flows in ungageed sites.

• 산업기술연구
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• 제31권A호
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• pp.119-122
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• 2011

AWS (Automated Weather Station) wind data was used to predict the annual energy production of Gangwon wind farm having a total capacity of 98 MW in Korea. Two common wind energy prediction programs, WAsP and WindSim were used. Predictions were made for three consecutive years of 2007, 2008 and 2009 and the results were compared with the actual annual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from both prediction programs were close to the actual energy productions and the errors were within 10%.

• 한국측량학회지
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• 제30권6_1호
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• pp.567-574
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• 2012

최근 영상감시시장은 공공부문과 민간보안부문 등에서 CCTV 수요확대로 큰 성장세를 보이고 있다. 공공부문과 민간보안부분에 CCTV의 활용은 확대되고 있으나, 재난 재해분야에 CCTV의 활용은 아직까지 미흡한 것이 현실이다. 본 연구에서는 재난 재해 상황 변화를 감시자의 눈으로 담아내는 CCTV의 역할을 재조명하여 상습적으로 내수침수가 발생하고 있는 강남역 일대를 중심으로 재난원인분석을 위한 사례분석을 수행하였다. 먼저, 강남역 일대의 주요 침수지점에 대한 CCTV영상자료를 수집하고 영상 분석 및 현장조사를 통해 강우발생에 따른 침수시간과 침수심을 산정하였다. 또한 과거침수이력과 AWS(Automatic Weather System)강우자료를 이용하여 강우분석을 수행하였다. 강우분석결과와 CCTV영상에서 추출한 침수시간과 침수심 정보의 비교분석을 통해 과거 침수이력을 바탕으로 한 강남역 침수발생 강우량과 대응방안을 제시하였다. 이 결과는 상습침수지역인 강남역의 침수피해를 상당히 절감할 수 있을 것으로 판단된다.

• 한국농림기상학회지
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• 제20권1호
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• pp.117-126
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• 2018

본 연구는 품질평가 등급이 우수한 4개 기관에서 운영하고 있는 990개의 AWS 중에서 고도가 200m 이상인 산악지역에 분포하고 있는 산악기상관측소의 공간분포 특성과 연도별 공간변화를 분석하였다. 공간분포특성 분석을 위해 2012년부터 2016년까지 203개의 산악기상관측망을 대상으로 유클리디안 거리 분석, 최근 린지수 분석, 커널밀도 분석 방법으로 공간분석을 수행하였다. 평균거리 분석 결과, 2012년(3개 기관)은 29.0km, 2012년(4개 기관) 26.6km, 2013년 21.9km, 2014년 16.9km, 2015년 14.3km, 2016년은 12.6km로 2012년부터 2016년까지 16.4km가 감소하는 효과를 보였다. 최근린지수는 0.666632~0.811237였으며, 군집화 범위인 Z-score 검정 결과는 -4.372239~-5.145115, 통계적으로는 P-value(P<0.01)로 매우 유의하면서 산악기상관측망이 군집화 형태로 분포하는 것으로 나타났다. 커널밀도 분석 결과, 2012년은 129,719ha/1개소, 2013년 90,917ha/1개소, 2014년 71,342ha/1개소, 2015년 58,875ha/1개소로, 2016년은 50,914ha/1개소로 2012년부터 2016년까지 169,399ha/1개소가 감소하면서 산악기상관측망 공간분포 밀도가 높아진 결과를 보였다. 따라서 백두대간 일부 지역과 경북 내륙, 경남북서부 지역을 대상으로 최적의 입지에 산악기상관측망을 확충하는 것이 필요하다고 사료된다.

• International Journal of Industrial Entomology and Biomaterials
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• 제25권2호
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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.

• 환경영향평가
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• 제12권4호
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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.

• 한국농림기상학회지
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• 제3권2호
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• pp.121-125
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• 2001

농업기상정보서비스는 농촌진흥청 정보화 기술개발 사업의 일환으로 개발되었다. 이 사업은 전국의 농업기상자동관측장비(Automatic Weather Station; AWS)를 전산망에 통합하여 전국 농업기상관측망을 구축하고, 농업기상정보의 수집, 저장을 체계화하는 한편, 이를 이용하여 농업인, 정책결정자, 연구원 등에게 필요한 형태로 농업기상정보를 제공하기 위한 목적으로 수행되었다.(중략)

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.397-404
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• 2000

A total of 65 rain gauges with Automatic Weather Station(AWS) were used to regional analysis of precipitation. Nine cluster regions were identified using geographical locations, maximum, mean, standard deviation of 1 day maximum rainfalls, mean annual precipitation and rainfall of rainy season in Korea. The mean annual precipitation, geographical locations, and the synoptic generating mechanisms were used to identify th five climatological homogeneous regions in Korea. Number of final regions by mean annual precipitation and cluster methods divided into five regions in Korea.