• Title/Summary/Keyword: meteorological service

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Agricultural Climatology of Cheju Island II. Potential Evapotranspiration Based on Near-Real Time Data Measured by Automated Weather Stations (제주도의 농업기후 분석 II. 무인관측강에 의한 기상실황자료 수집 및 증발산위 계산)

  • 윤진일
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.35 no.6
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    • pp.504-511
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    • 1990
  • Weather data acquisition and potential evapotranspiration (PET) calculation procedure were investigated to support the agricultural development efforts in the mid-altitude mountainous region of Cheju Island. Automated weather stations (AWS) were installed at two points representing the east and the west of the study area. A personal computer was employed to collect the near-real time weather data from AWS through the public telephone line. Hourly data were available for solar radiation, air and soil temperature, relative humidity, wind speed and direction, and precipitation. Based on the data for the month of June 1989, daily climatic features were comparatively analyzed for the two areas and the Penman equation was used to calculate PET. Air temperature was higher by 1 to 2 degree C in the east due mainly to the higher solar radiation and partly to the Fohn effect caused by the daytime southwesterly blowing over Mt. Halla. Diurnal march of soil temperature lagged by 4 hours behind that of air temperature and the diurnal range for 10cm subsurface soil was 3 degree C. Wind was consistently stronger and a marked sea-land breeze circulation was detected in the west. Calculated PET values were higher in the east by 6% than in the west. Overall values from the east and the west of the mid-altitude mountainous region were higher by 30% than those of the coastal region, which were estimated from the Class A Pan evaporation measured by the Korea Meteorological Service Offices.

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Evolution of Agrometeorology at the Global Level (농업기상학의 역사)

  • Sivakumar, M.V.K.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.6 no.2
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    • pp.127-139
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    • 2004
  • Agricultural meteorology has advanced during the last 100 years from a descriptive to a quantitative science using physical and biological principles. The agricultural community is becoming more aware that using climate and weather information will improve their profitability and this will no doubt increase the demand for agrometeorological services. Hence it is timely that the needs and perspectives for agrometeorology in the 21$^{21}$ Century are grouped under two major headings: agrometeorological services for agricultural production and agrometeorological support systems for such services. Emphasis must be placed on the components of such support systems comprising of data, research, policies and training/education/extension. As Monteith (2000) mentioned, food supplies ultimately depend upon the skill with which farmers ran exploit the potential of good weather and minimize the impact of bad weather. Recent developments in instrumentation, data management systems, climate prediction, crop modelling, dissemination of agrometeorological information etc., provide agrometeorologists the tools necessary help the farmers improve such skills. The future for operational applications of agricultural meteorology appears bright and such applications could contribute substantially to promote sustainable agriculture and alleviate poverty.

CAgM, USDA and the National Drought Policy Commission Associated with WAMIS (농업기상웹서버관련 농업기상위원회, 농무성 및 한발정책위원회 현황)

  • Motha, Raymond P.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.6 no.2
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    • pp.140-147
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    • 2004
  • Agrometeorological information is essential in many agricultural decisions if it reaches the user in a timely and appropriate manner. Agriculture is the backbone to local, regional, and global economic development. Thus, strengthening agrometeorological application to diverse agricultural sectors will benefit economic development. This paper discusses three distinct organizational minions that all share the same need for improved information technology. The World Meteorological Organization's (WMOs) Commission for Agricultural Meteorology (CAgM) has global responsibility for improved agrometeorological services of Members to aid agricultural production and to conserve natural resources. The United States Department of Agriculture, World Agricultural Outlook Board, publishes monthly World Agricultural Supply and Demand Estimates, considered to be a benchmark for both government and industry in production and trade decisions. The National Drought Policy Commission (NDPC), created by an act of the United States Congress, formulated a national drought policy based on preparedness rather than on crisis management. All three organizations recognize the need for IT applications in agricultural meteorology and have been active in implementing this technology. The development of information technology offers new means of dissemination of agrometeorological products. World Agrometeorological Information Service (WAMIS) has taken advantage of the global Internet application to offer WMO Members a dedicated web server to host agrometeorological bulletins and training modules.

The Influence of Asian Dust, Haze, Mist, and Fog on Hospital Visits for Airway Diseases

  • Park, Jinkyeong;Lim, Myoung Nam;Hong, Yoonki;Kim, Woo Jin
    • Tuberculosis and Respiratory Diseases
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    • v.78 no.4
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    • pp.326-335
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    • 2015
  • Background: Asian dust is known to have harmful effects on the respiratory system. Respiratory conditions are also influenced by environmental conditions regardless of the presence of pollutants. The same pollutant can have different effects on the airway when the air is dry compared with when it is humid. We investigated hospital visits for chronic obstructive pulmonary disease (COPD) and asthma in relation to the environmental conditions. Methods: We conducted a retrospective study using the Korean National Health Insurance Service claims database of patients who visited hospitals in Chuncheon between January 2006 and April 2012. Asian dust, haze, mist, and fog days were determined using reports from the Korea Meteorological Administration. Hospital visits for asthma or COPD on the index days were compared with the comparison days. We used two-way case-crossover techniques with one to two matching. Results: The mean hospital visits for asthma and COPD were $59.37{\pm}34.01$ and $10.04{\pm}6.18$ per day, respectively. Hospital visits for asthma significantly increased at lag0 and lag1 for Asian dust (relative risk [RR], 1.10; 95% confidence interval [CI], 1.01-1.19; p<0.05) and haze (RR, 1.13; 95% CI, 1.06-1.22; p<0.05), but were significantly lower on misty (RR, 0.89; 95% CI, 0.80-0.99; p<0.05) and foggy (RR, 0.89; 95% CI, 0.84-0.93; p<0.05) days than on control days. The hospital visits for COPD also significantly increased on days with Asian dust (RR, 1.29; 95% CI, 1.05-1.59; p<0.05), and were significantly lower at lag4 for foggy days, compared with days without fog (RR, 0.85; 95% CI, 0.75-0.97; p<0.05). Conclusion: Asian dust showed an association with airway diseases and had effects for several days after the exposure. In contrast to Asian dust, mist and fog, which occur in humid air conditions, showed the opposite effects on airway diseases, after adjusting to the pollutants. It would require more research to investigate the effects of various air conditions on airway diseases.

Real-time and Parallel Semantic Translation Technique for Large-Scale Streaming Sensor Data in an IoT Environment (사물인터넷 환경에서 대용량 스트리밍 센서데이터의 실시간·병렬 시맨틱 변환 기법)

  • Kwon, SoonHyun;Park, Dongwan;Bang, Hyochan;Park, Youngtack
    • Journal of KIISE
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    • v.42 no.1
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    • pp.54-67
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    • 2015
  • Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

Distribution Analysis of Land Surface Temperature about Seoul Using Landsat 8 Satellite Images and AWS Data (Landsat 8 위성영상과 AWS 데이터를 이용한 서울특별시의 지표면 온도 분포 분석)

  • Lee, Jong-Sin;Oh, Myoung-Kwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.1
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    • pp.434-439
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    • 2019
  • Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

Detection of The Real-time Weather Information from a Vehicle Black Box (차량용 블랙박스 영상에서의 실시간 기상정보 검지)

  • Kang, Ju-mi;Lee, Jaesung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.320-323
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    • 2014
  • Today is going with the advancement of intelligent transportation systems and traffic environment and helping to provide safe and convenient service through a mobile device work with the popularization of the vehicle black box. The traffic flow by a variety of causes is constantly changing, it is often unable to prepare the driver, depending on external factors can not be controlled by the power of the public, leading to a major accident. The system needs to pass the real-time weather data in the inter-operator to prevent this. The proposed detection algorithm weather information delivered real-time weather information for this paper. The weather condition is detected by using the contrast between the histogram of the motion of the wiper and the clear day algorithm. In general, the wiper is worked in extreme weather conditions that will have a value different contrast due to rain or snow. Situation was considered clear, snowy conditions, such as using it on a rainy situation. First, designated as ROI (Region Of Interest) of the minimum area that can be detected in order to reduce the amount of calculation for the wiper, the wiper, which was detected through the operation of the threshold Thresholding the brightness of the vehicle wiper. In addition, we distinguish the value of each meteorological situation by using contrast. Results was obtained to 80% for the snow conditions, a rainy situation.

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Mountain Meteorology Data for Forest Disaster Prevention and Forest Management (산림재해 방지와 산림관리를 위한 산악기상정보)

  • Keunchang, Jang;Sunghyun, Min;Inhye, Kim;Junghwa, Chun;Myoungsoo, Won
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.4
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    • pp.346-352
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    • 2022
  • Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.

DNN Model for Calculation of UV Index at The Location of User Using Solar Object Information and Sunlight Characteristics (태양객체 정보 및 태양광 특성을 이용하여 사용자 위치의 자외선 지수를 산출하는 DNN 모델)

  • Ga, Deog-hyun;Oh, Seung-Taek;Lim, Jae-Hyun
    • Journal of Internet Computing and Services
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    • v.23 no.2
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    • pp.29-35
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    • 2022
  • UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

Assessment of the long-term hydrologic impacts on the ungaged Tumen River basin by using satellite and global LSM based on data and SWAT model (위성 및 광역지표모형 기반 자료와 SWAT 모형을 이용한 미계측 두만강 유역의 장기 수문영향 평가)

  • Cho, Younghyun;Ahn, Yoon Ho;Park, Sang Young;Park, Jin Hyeog
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.94-94
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    • 2020
  • 최근 정부의 신북방정책 추진에 따라 수자원분야에서는 동북아지역 국제 공유하천을 중심의 물 정보 및 연구협력 기회 확보와 지정학적 특성을 고려한 지역 현안해결 중심의 연구가 재조명 되고 있다. 두만강은 이러한 동북아의 중심에 위치하고 있으며, 중국, 북한, 러이사의 국경을 따라 흐르며 지역 수자원의 대부분을 공급하는 국제하천이다. 또한, 지난 2018년 5월에는 하구유역이 람사르(Ramsar) 습지로 승인됨에 따라 철새 등을 포함한 생태가치의 중요성도 크게 증가하였다. 하지만 이 지역은 유역의 지정학적 민감성과 접근이 제한된 관측 정보들로 인해 그 수자원·환경 효용성을 정확하게 파악할 수 없을 뿐만 아니라, 최근 기후변화에 따른 영향으로 홍수, 가뭄 등의 수재해와 수질오염 등의 문제가 발생하고 있어 가용한 기술기반의 직·간접적 접근을 통한 장기수문 및 환경변화 등에 대한 분석과 관리방안 수립 등의 연구가 필요하다. 본 연구에서는 이러한 미계측 두만강 유역을 대상으로 우선, 가용한 위성자료 및 광역지표모형(MERRA-2) 기반 NASA POWER(Prediction of Worldwide Energy Resource) 수문기상 자료와 SWAT(Soil and Water Assessment Tool) 모형을 활용하여 장기 수문영향을 평가하고자 한다. SWAT 모형은 전 지구적으로 활용 가능한 격자 해상도 약 30m의 위성기반 수치표고모형(DEM), 광역 토양도, 지역 토지이용도 자료를 활용하여 두만강 유역을 전체 19개 소유역 및 18개 하도, 138개 HRUs의 수문분석 단위로 구축하였으며, 모의는 미국 NOAA NCDC(National Climate Data Center) 및 중국 CMDC(China Meteorological Data Service Center)의 주요 관측지점에서 선별한 총 13개소의 위치에 대해 재분석된 기후/기상자료들(NASA POWER 강수, 기온, 풍속, 상대습도 및 일사량)을 적용, 1990년에서 2019년까지의 30개년도 연속자료를 구축활용 하였다. 한편, 모형의 검·보정은 앞서 언급한 관측 자료의 부재로 과거 문헌 등을 통해 파악할 수 있는 연 단위 수자원 총량 등을 활용해 진행코자한다. 아울러, 향후는 최근 활용 가능한 장기 위성관측 강수량을 적용, 재분석 자료 결과와의 비교를 통해 상호 분석 오류를 줄여나갈 수 있을 것으로도 판단된다.

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