• Journal of Digital Convergence
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• v.14 no.3
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• pp.209-217
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• 2016

Recently, the outdoor activities were increased in accordance with economic growth and improved quality of life. In addition, weather and outdoor activities are closely related. Currently, Outdoor Activities decisions are determined by the Korea Meteorological Administrator's forecasts and subjective experience. Therefore, we need the analysis method that can provide a basis for the decision on outdoor activities based on meteorological information. In this paper, we propose an algorithm that can analyze meteorological information to support decision-making outdoor activities. And the algorithm is based on the data mining. In addition, we have constructed a baseball game schedule with automatic weather system's observation data in the training data. We verified the improved performance of the proposed algorithm.

• Journal of Navigation and Port Research
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• v.33 no.8
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• pp.549-554
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• 2009

Wind velocity and wind direction are very important in the viewpoint of ship's safety and stability of port structure. The characteristics of wind distribution in the coast of Busan are analyzed for 10 years from 1997 to 2006 using AWS(Automatic Weather System) data. The characteristics of wind distribution of Miryang, is not affected by the land and sea breeze are also examined to understand clearly the characteristics of wind distribution in the coast of Busan. The mean wind velocity in the coast of Busan is stronger than that of Miryang. The mean wind velocitie at Youngdo and Gadukdo stations of Busan are stronger about 2.0 times than those at IlGwang, Haeundae and Daeyeon stations. The correlation a states show that the variation tendencies of monthly mean wind velocitie in the coast of Busan are very similar. The maximum monthly mean velocitie in the coast of Busan are recorded in September. This re ult is closely related to the influence of typhoon. The maximum instantaneous wind velocitie are also strong at Youngdo and Gadukdo stations and the peaks of maximum instantaneous wind $velocit^9$ are observed mainly from August to September. In the coast of Busan, the SW'ly-NNE'ly wind are prevailing in the winter and the SW'ly and NE'ly wind are predomi snt in the spring. w that the vs of wind direction in the summer and athumn are similar with those in the spring and winter, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.259-263
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• 2008

최근 기후변화로 인해 집중호우, 태풍, 폭설 등 악기상 발생이 빈번해지고 있으며, 특히 태풍은 단일 기상현상 가운데 가장 강력하며, 태풍으로 인하여 집중호우 폭풍 및 해일 등 부차적 악기상이 함께 발생하여 인명 및 경제 사회적인 피해 또한 막대하지만, 태풍으로 인한 강수량 측정은 다른 현상에 비해 정확한 측정이 어렵다. 이것은 태풍이 발생에서 소멸까지 일생의 대부분을 해상에서 보내, 육상 관측으로는 정확한 강수량 측정이 어렵기 때문이다. 그러나 위성자료를 활용하면 해상에서의 태풍 구름에 의한 강수분포를 추정할 수 있으며, 특히 구름을 투과하여 아래 내부구조 파악이 가능한 마이크로파 영역의 적외복사에너지를 이용하면 좀더 정확한 강수량 자료를 얻을 수 있을 것이다. 그러나 관측영역 확대를 위해서는 가능한 마이크로파위성자료를 합성처리하여 활용하는 것이 효과를 얻을 수 있을 것이다. 본 연구에서는 현재 기상청에서 수신하고 있는 Aqua/AMSR-E, SSM/I, TMI, QuilSCAT 등에서 산출되는 강수량을 상호 검증기법을 이용하여 합성처리 하였다. 위성자료마다 정확도와 해상도가 다른 것에 대해서는 높은 정확도에 가중치를 주고, 고해상도 자료에 맞추어 픽셀 크기를 맞추었다. 사용한 자료는 2005년$\sim$2007년 간 발생한 태풍 중에서 우리나라에 영향을 준 나비, 나리, 에위니아 등 3개 사례이며, 검증은 자동관측자료(AWS : Automatic Weather Station)자료와 일본 AWS자료(AMEDAS : Automatic Measurement Data Aquisition System) 및 미해군 연구소 발표자료를 이용하여, 시계열오차 분석 및 산포도를 분석하였다.

• Journal of Environmental Science International
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• v.25 no.11
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• pp.1589-1595
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• 2016

From December 2014 to November 2015, an automatic weather system (AWS) was installed over a wide road of Daegu to continuously measure meteorological factors and surface temperature. We investigated the effective operating period of the clean-road system using the daily maximum and minimum air and asphalt surface temperatures, with the aim of creating an optimum thermal environment. The clean-road system was installed over a part of the broad way of Dalgubul(Dalgubul-Daero) by Daegu Metropolitan City in 2011. Until now, the clean-road system has been operated from the middle of April to the end of September. We assumed that it was desirable that the clean-road system could be operated when the discomfort index was above 55. In conformity with the conditions, we concluded that the optimum operation period of the clean-road system is from the end of March to about the middle of October.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.117-120
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• 2006

Heavy rainfall events are occurred exceedingly various forms by a complex interaction between synoptic, dynamic and atmospheric stability. As the results, quantitative precipitation forecast is extraordinary difficult because it happens locally in a short time and has a strong spatial and temporal variations. GOES-9 imagery data provides continuous observations of the clouds in time and space at the right resolution. In this study, an power-law type algorithm(KAE: Korea auto estimator) for estimating rainfall based on the rainfall type was developed using geostationary meteorological satellite data. GOES-9 imagery and automatic weather station(AWS) measurements data were used for the classification of rainfall types and the development of estimation algorithm. Subjective and objective classification of rainfall types using GOES-9 imagery data and AWS measurements data showed that most of heavy rainfalls are occurred by the convective and mired type. Statistical analysis between AWS rainfall and GOES-IR data according to the rainfall types showed that estimation of rainfall amount using satellite data could be possible only for the convective and mixed type rainfall. The quality of KAE in estimating the rainfall amount and rainfall area is similar or slightly superior to the National Environmental Satellite Data and Information Service's auto-estimator(NESDIS AE), especially for the multi cell convective and mixed type heavy rainfalls. Also the high estimated level is denoted on the mature stage as well as decaying stages of rainfall system.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.3
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• pp.137-152
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• 2004

The climatological characteristics of coastal zone over the southwestern coast of Korea peninsula were investigated using the data observed by AWS (automatic weather system) and 4 buoy points. Coastal zone is climatologically defined as the region bounded by the distinct contrast of temperature gradient and wind speed across coastline. In the southwest of peninsula four cross-lines consisted of AWS aligned with each buoy were selected as Geojedo buoy line, Geomundo buoy line, Chilbaldo buoy line and Dukjukdo buoy line. Analysis on the diurnal cycle and intra-month variation, monthly mean and maximum value, the temperature gradient with distance between buoy and each station and the accumulative frequency of wind speed were applied to find out the characteristics and the range of coast zone. The maximum ranges of coastal zone vary from offshore to Sanglim (about 34 km distance from coastline) for Geojedo buoy line, to Sunchun (about 52 km) for Geo-mundo buoy line, to Jaeundo (about 27 km) for chilbaldo buoy line and to Yongin (about 65 km) for Dukjukdo buoy line. The modification of coastal zone according to synoptic flow was investigated for the onshore, off-shore and calm cases. The ranges of coastal zone are significantly changed with the distance between 65∼90 km for the case of onshore. In addition, we tried to find out the variation of the wind and temperature and the wind ratio of wind speed at ocean to land stations along Geojedo buoy line during 12∼13 Sep. 2003 affected by typhoon (MAEMI).

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.244-255
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• 2022

This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.717-726
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• 2006

In this study, we developed a rainfall forecasting model using data from radiosonde and rain gauge network and neural networks. The primary hypothesis is that if we can consider the moving direction of the rain generating weather system in forecasting rainfall, we can get more accurate results. We assume that the moving direction of the rain generating weather system is same as the wind direction at 700mb which is measured at radiosonde networks. Neural networks are consisted of 8 different modules according to 8 different wind directions. The model was verified using 350 AWS data and Pohang radiosonde data. Correlation coefficient is improved from 0.41 to 0.73 and skill score is 0.35. Statistical performance measures of the Quantitative Precipitation Forecast (QPF) model show improved output compared to that of rainfall forecasting model using only AWS data.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.397-408
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• 2004

In this study, surface temperature which was extracted from Landsat TM band 6 was compared and analyzed with the AWS(Automatic Weather System) observation data for studying urban heat environment properties with possibility of remote sensing data application. In order to verification of the distribution properties of urban surface temperature, correlation analysis between surface temperature and NDVI, the distribution properties of urban surface temperature by land use/cover patterns were carried out by GIS spatial analysis techniques. The results presented that the spatial distribution of urban surface temperature was very different depending on various land use/cover patterns of surrounding areas. Also there was the reverse linear relationship between surface temperature and NDVI. These results will be worked as one of the major factors for environmentally sustainable urban planning considering the characteristics of weather environments in the near future.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1155-1167
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• 2018

We developed a small sensor observation system (SSOS) at a relatively low cost to observe the atmospheric boundary layer. The accuracy of the SSOS sensor was compared with that of the automatic weather system (AWS) and meteorological tower at the Korea Meteorological Administration (KMA). Comparisons between SSOS sensors and KMA sensors were carried out by dividing into ground and lower atmosphere. As a result of comparing the raw data of the SSOS sensor with the raw data of AWS and the observation tower by applying the root-mean-square-error to the error, the corresponding values were within the error tolerance range (KMA meteorological reference point: humidity ${\pm}5%$, atmospheric pressure ${\pm}0.5hPa$, temperature ${\pm}0.5^{\circ}C$. In the case of humidity, even if the altitude changed, it tends to be underestimated. In the case of temperature, when the altitude rose to 40 m above the ground, the value changed from underestimation to overestimation. However, it can be confirmed that the errors are within the KMA's permissible range after correction.