• Journal of Forest and Environmental Science
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• 제34권3호
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• pp.249-252
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• 2018

Climate is one of most important environmental factors on the forest ecosystem. This study was conducted to analyze the characteristics of meteorological factors in the forest area and weather stations from July 2015 to June 2016 in Cheuncheon and Hongcheon of Kangwon Province in Korea. The HOBO data logger was installed for meteorological analysis in forests area (site 1 and site 2). The meteorological data from the HOBO data logger compared with meteorological data of the weather station. The meteorological data used for the analysis was monthly mean temperature ($^{\circ}C$), monthly mean minimum temperature ($^{\circ}C$), monthly mean maximum average temperature ($^{\circ}C$), and monthly mean relative humidity (%). As a result of this study, the mean temperature ($^{\circ}C$) of forest area was relatively lower than weather station which is the outside the forest area, and the mean maximum temperature ($^{\circ}C$) of weather station was relatively higher than that of forest area. The mean relative humidity (%) was higher in forest area than weather station.

• Water Engineering Research
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• 제4권3호
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• pp.111-126
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• 2003

Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

• 한국환경과학회지
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• 제29권10호
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• pp.1003-1010
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• 2020

In this study, the necessity for a village unit Automatic Weather System (AWS) was suggested to obtain correct agricultural weather information by comparing the data of AWS of the weather station with the data of AWS installed in agricultural villages 7 km away. The comparison sites are Hyogyo-ri and Hongseong weather station. The seasonal and monthly averaged and cumulative values of data were calculated and compared. The annual time series and correlation was analyzed to determine the tendency of variation in AWS data. The average values of temperature, relative humidity and wind speed were not much different in comparison with each season. The difference in precipitation was ranged from 13.2 to 91.1 mm. The difference in monthly precipitation ranged from 1.2 to 75.4 mm. The correlation coefficient between temperature, humidity and wind speed was ranged from 0.81 to 0.99 and it of temperature was the highest. The correlation coefficient of precipitation was 0.63 and the lowest among the observed elements. Through this study, precipitation at the weather station and village unit area showed the low correlation and the difference for a quantitative comparison, while the elements excluding precipitation showed the high correlation and the similar annual variation pattern.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.132-132
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• 2021

Access to accurate spatial precipitation in many hydrological studies is necessary. Existence of many mountains with diverse topography in South Korea causes different spatial distribution of precipitation. Rain gauge stations show accurate precipitation information in points, but due to the limited use of rain gauge stations and the difficulty of accessing them, there is not enough accurate information in the whole area. Weather radars can provide an integrated precipitation information spatially. Despite this, weather radar data have some errors that can not provide accurate data, especially in heavy rainfall. In this study, some location-based variable like aspect, elevation, plan curvature, profile curvature, slope and distance from the sea which has most effect on rainfall was considered. Then Automatic Weather Station data was used for spatial training of variables in each event. According to this, K-fold cross-validation method was combined with Adaptive Neuro-Fuzzy Inference System. Based on this, 80% of Automatic Weather Station data was used for training and validation of model and 20% was used for testing and evaluation of model. Finally, spatial distribution of precipitation for 1×1 km resolution in Gwangdeoksan radar station was estimates. The results showed a significant decrease in RMSE and an increase in correlation with the observed amount of precipitation.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2013년도 추계 학술발표논문집
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• pp.60-66
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• 2013

• 한국환경과학회지
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• 제28권10호
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• pp.863-872
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• 2019

Using the Standard Precipitation Index (SPI), this study analyzed the drought characteristics of ten weather stations in Gyeongbuk, South Korea, that precipitation data over a period of 30 years. For the number of months that had a SPI of -1.0 or less, the drought occurrence index was calculated and a maximum shortage months, resilience and vulnerability in each weather station were analyzed. According to the analysis, in terms of vulnerability, the weather stations with acute short-term drought were Andong, Bonghwa, Moongyeong, and Gumi. The weather stations with acute medium-term drought were Daegu and Uljin. Finally the weather stations with acute long-term drought were Pohang, Youngdeok, and Youngju. In terms of severe drought frequency, the stations with relatively high frequency of mid-term droughts were Andong, Bonghwa, Daegu, Uiseong, Uljin, and Youngju. Gumi station had high frequency of short-term droughts. Pohang station had severe short-term ad long-term droughts. Youngdeok had severe droughts during all the terms. Based on the analysis results, it is inferred that the size of the drought should be evaluated depending on how serious vulnerability, resilience, and drought index are. Through proper evaluation of drought, it is possible to take systematic measures for the duration of the drought.

• 대기
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• 제26권2호
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• pp.277-288
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• 2016

Polar lows are intense mesoscale cyclones that mainly occur over the sea in polar regions. Owing to their small spatial scale of a diameter less than 1000 km, simulating polar lows is a challenging task. At King Sejong station in West Antartica, polar lows are often observed. Despite the recent significant climatic changes observed over West Antarctica, adequate validation of regional simulations of extreme weather events such as polar lows are rare for this region. To address this gap, simulation results from a recent version of the Polar Weather Research and Forecasting model (Polar WRF) covering Antartic Peninsula at a high horizontal resolution of 3 km are validated against near-surface meteorological observations. We selected a case of high wind speed event on 7 January 2013 recorded at Automatic Meteorological Observation Station (AMOS) in King Sejong station, Antarctica. It is revealed by in situ observations, numerical weather prediction, and reanalysis fields that the synoptic and mesoscale environment of the strong wind event was due to the passage of a strong mesoscale polar low of center pressure 950 hPa. Verifying model results from 3 km grid resolution simulation against AMOS observation showed that high skill in simulating wind speed and surface pressure with a bias of $-1.1m\;s^{-1}$ and -1.2 hPa, respectively. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation of Antartic weather systems and the near-surface meteorological instruments installed in King Sejong station can provide invaluable data for polar low studies over West Antartica.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
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• pp.109-112
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• 2006

Recently, when we conducted meteorological observations, complicated land or building around weather station has influenced on the wind distribution. So, we should understand the effect of geometry to get more accurate data. In this study, we analyze the ideal geometry whose shape is hemisphere using CFD method. And then we apply this method to real geometry. And we investigate the velocity at the location of weather station. As the results, we could find out an important relationship between geometry and flow field.

• 한국해양학회지:바다
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• 제4권2호
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• pp.155-159
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• 1999

수중음향을 이용한 풍속 측정(Weather Observation Through Ambient Noise: WOTAN) 기술을 이용하여 소형 기상관측부이를 개발하였다. 소형기상관측부이는 지상자료 수선소와 기상부이 간의 통신수단으로 휴대전화망을 채택하였다. 제작된 소형기상관측부이를 부산시 기장군 시랑리 부근 해역에 계류하여 부근에 위치한 국립수산진흥원에 설치한 지상기상관측기기에서 관측된 결과와 비교하였다. 수중음향을 이용하여 추정된 풍속을 지상에서 관측한 풍속과 비교한 결과 좋은 결과를 얻었다. 즉 풍속계에 의한 풍속과 수중음향에 의해 추정된 풍속의 rms 오차가 1 m/s 내외로 나타났다. 이 소형기상관측부이의 한가지 단점은 휴대전화의 통달거리가 짧아 육지에서 멀리 떨어진 곳에는 설치가 불가능하다는 점인데, 현재 전 세계 대양에서 통화가 가능한 위성 휴대전화망이 상용화되기 시작하여 위성 휴대전화를 이용하면 이 문제는 쉽게 해결될 수 있다고 본다.

• 한국환경과학회지
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• 제27권7호
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.