• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.53-62
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• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.

• Journal of the Korean association of regional geographers
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• v.20 no.4
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• pp.393-408
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• 2014

In this study, the spatio-temporal characteristics of summer extreme precipitation events in the Republic of Korea are examined based on the daily precipitation data observed at approximately 360 sites of both Automatic Weather Station (AWS) and Automated Synoptic Observation System (ASOS) networks by the Korea Meteorological Administration for the recent decade(2002~2011). During the summer Changma period(late June~mid July), both the frequency of extreme precipitation events exceeding 80mm of daily precipitation and their decadal maximum values are greatest at most of weather stations. In contrast, during the Changma pause period (late July~early August), these patterns are observed only in the northern regions of Geyeonggi province and western Kangwon province as such patterns are detected around Mt. Sobaek and Mt. Halla as well as in the southern regions of Geyeonggi province and western Kangwon province during the late Changma period (mid August~early September) due to north-south oscillation of the Changma front. Investigation of their regional patterns confirms that not only migration of the Changma front but also topological components in response to the advection of moistures such as elevation and aspect of major mountain ridges are detrimental to spatio-temporal patterns of extreme precipitation events. These results indicate that each local administration needs differentiated strategies to mitigate the potential damages by extreme precipitation events due to the spatiotemporal heterogeneity of their frequency and intensity during each Changma period.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.16-21
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• 2001

Regression models were obtained on the base of the correlation between Phytophthora blight incidence in red pepper and the microclimate data obtained from automated weather station (AWS) during 1997 and 1998. A computer program (PEPBLIGHT) was constructed based on the model that the R2 value is highest among regression models. This computer program uses the microclimate data from more than one AWS through the common dialogue box easy and it is able provide disease forecasting information. In addition, it could be applied far other diseases and converts the microclimate data of AWS to the input data for Statical Analysis System (SAS). PEPBLIGHT was first developed for the forecasting computer system of red pepper blight in Korea. PEPBLIGHT is operated on the MS Windows, so that it is easy to use.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.330-330
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• 2022

우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.21-31
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• 2020

Planting pine trees on the coastal dunes has been carried out along the East coast as well as West coast of South Korea. Although the artificial forestation has been regarded as a good policy that help to protect the coastal area from natural disasters, but its real effect to the landscapes is still unknown. In this study, we have installed a monitoring site with an automated weather station to study requirements for dune formation and its environmental changes in Osan beach, Yangyang-Gun, Gangwon Province. We analyzed the meteorological data collected from 2010 to 2019 and vegetational changes in the study area. As a result, the wind speed is decreased by around 30% and the pine-covered area is increased by around 300m² after planting Japanese Black Pine in 2015. At present, it seems that the eolian transport of sand particle is minimal, because the dominant winds are the westerly winds which is not landward but seaward, and because the surface roughness length is about 0.5m which is similar to that in the deciduous forest.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• Journal of Environmental Science International
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• v.23 no.5
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• pp.873-885
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• 2014

To identify the characteristics of extreme heat events and tropical nights in major cities, the correlations between automated synoptic observing station (ASOS), automatic weather station (AWS), and temperature in seven metropolitan areas were analyzed. Temperatures at ASOS were found to be useful sources of the reference temperature of each area. To set the standard for identifying dates of extreme heat events in relation to regional topography and the natural environment, the monthly and yearly frequency of extreme heat in each region was examined, based on the standards for extreme heat day (EHD), tropical night day (TND), and extreme heat and tropical night day (ETD). All three cases identified 1994 as the year with the most frequent heat waves. The frequency was low according to all three cases in 1993, 2003 and 2009. Meanwhile, the yearly rate of increase was the highest in 1994, followed by 2010 and 2004, indicating that the frequency of extreme heat changed significantly between 1993 and 1994, 2003 and 2004, and 2009 and 2010. Therefore all three indexes can be used as a standard for high temperature events. According to monthly frequency data for EHD, TND, and ETD, July and August accounted for 80% or more of the extreme heat of the entire year.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.535-544
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• 2009

Signals from the Global Positioning System(GPS) satellite are used to retrieve the integrated amount of water vapor or the precipitable water vapor(PWV) along the path between a transmitting satellite and ground-based receiver. In order to retrieve the PWV from GPS signal delay in the troposphere, the actual zenith wet delay, which can be derived by extracting the zenith total delay and subtracting the actual zenith hydrostatic delay computed using surface pressure observing, will be needed. Since it has been not co-located between GPS permanent station and automated weather station, the air-pressure on the mean sea level has been used to determine the actual zenith hydrostatic delay. The directly use of this air-pressure has been caused the dilution of precision on GPS PWV retrieval. In this study, Korean reverse sea level correction method of air-pressure was suggested for the improving of GPS PWV retrieval capability and the accuracy of water vapor estimated by GPS was evaluated through a comparison with radiosonde PWV.

• Solar Energy
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• v.11 no.3
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• pp.3-8
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• 1991

There are fifteen solar radiation measurement stations over the entire country in Korea. However, they are not capable of supplying reliable solar radiation data for remote areas including islands. The un-manned automated insolation measurement station is suitable for these areas due to the electric power shortage and the maintenance problems at these isolated areas. Our main aim in this work is to develop a solar radiation measurement system which collects and stores data by itself utilizing a PV module and a battery as power source for entire system irregardless of the environmental condition. A developed KIER's prototype system along with an independent HWS reference system has been installed at the designated remote island, Dok-do. Global solar radiation has been measured every hour for a 6-month period of time by both systems at this site. A comparison between the measured solar radiation data by each system indicates that there is an excellent agreement showing average 3.0% of an absolute error. It has been observed that the 8-month average global solar radiation was $2,330W/m^2$ day at this island. We came to the conservative conclusion that the developed KIER system is applicable for measuring solar radiation and for supplying reliable fundamental design data for solar energy utilization system at the remote areas.