• Water for future
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• v.18 no.1
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• pp.23-25
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• 1985

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.1-21
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• 2013

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.693-706
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• 2020

For ten meteorological observatories running an automated synoptic observing system (ASOS), we classified the observation environments into five classes based on the World Meteorological Organization (WMO) classification guidelines. Obstacles (such as topography and buildings) and land-cover types were the main factors in evaluating the observation environments for the sunshine duration, air-temperature, and surface wind. We used the digital maps of topography, buildings, and land-cover types. The observation environment of the sunshine duration was most affected by the surrounding buildings when the solar altitude angle was low around the sunrise and sunset. The air-temperature observation environment was determined based on not only the solar altitude angle but the distance between the heat/water source and ASOS. There was no water source around the ASOSs considered in this study. Heat sources located near some ASOSs were not large enough to affect the observation environment. We evaluated the surface wind observation environment based on the roughness length around the ASOS and the distance between surrounding buildings and the ASOS. Most ASOSs lay at a higher altitude than the surroundings and the roughness lengths around the ASOSs were small enough to satisfy the condition for the best level.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.11a
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• pp.45-46
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• 2003

배경대기(Background Atmosphere)란 배출원의 강도에 따라 다를 수 있으나 일반적으로 도시 또는 대규모의 발전소로부터의 영향이 적은 지역의 대기로써 인위적 오염원이 거의 없는 지역을 의미한다(WMO, 1978). 세계 기상기구(World Meteorological Organization: WMO)에서는 지구 대기가 인위 적인 오염원으로 인하여 생태계의 변화가 예상되고 인류의 생존이 위협받게 됨에 따라 이에 대한 대책으로 1969년에 배경대기오염관측망(Background Air Pollution Monitoring Network: BAPMoN)을 구축하여 장기적인 지구의 대기 환경 변화를 예측하기 위한 사업을 시작하였다. (중략)

• Atmosphere
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• v.31 no.5
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• pp.593-606
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• 2021

The Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) has monitored atmospheric CO₂ at Anmyeondo (AMY) World Meteorological Organization (WMO) Global Atmosphere Watch Programme (GAW) regional station since 1999, and expanded its observations at Jeju Gosan Suwolbong station (JGS) in the South and at Ulleungdo-Dokdo stations in the East (ULD and DOK) since 2012. Due to a recent WMO CO₂ scale update and a new filter (NIMS) to select baseline levels at each station, the 22 years of CO₂ data are recalculated. After correction for the new CO₂ scale, we confirmed that those corrected records are reasonable within the compatibility goal (±0.1 ppm of CO₂) between KMA/NIMS and National Oceanic and Atmosphereic Administration (NOAA) flask-air measurements with the new scale. With the new NIMS filter, CO₂ baseline levels are now more representative of the large-scale background compared to previous values, which contained large CO₂ enhancements. Atmospheric CO₂ observed in South Korea is 4 to 8 ppm greater than the global average while the amplitude of seasonal variation is similar (10~13 ppm) to the amplitude averaged over a comparable latitude zone (30°N-60°N). Variations in CO₂ growth rate are also similar, increasing and decreasing similar to global values, as it reflects the net balance between terrestrial respiration and photosynthesis. In 2020, atmospheric CO₂ continued increasing despite the COVID-19 pandemic. Even though fossil emission was reduced (around -7% globally), we still emitted large amounts of anthropogenic CO₂. Overall, since CO₂ has large natural variations and its source was derived from not only fossil fuel but also biomass burning, the small fossil emission reduction could not affect the atmospheric level directly.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.427-427
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• 2023

일반적으로 수자원가용량이라 하면 지표·지하·토양 등에 있는 모든 수자원의 양이라 할 수 있다. 정확한 수자원가용량의 평가를 위해서는 강수, 기온 등의 기상 예측의 정확도 확보가 우선되어야 하며, 지표 하에 보이지 않는 수자원의 양을 정확히 평가할 수 있어야 한다. 한국건설기술연구원은 2012년부터 세계기상기구(WMO, World Meteorological Organization)에서 수자원평가 부문 리더 역할을 수행하면서 회원국들에게 수자원가용량평가를 위한 '동적수자원평가시스템'의 개발을 제안하여 추진하였다. 그 결과, 동적수자원평가시스템(Dynamic Water resources Assessment Tool, DWAT)이 2017년 12월에 개발되었고, 2019년 5월에는 WMO 웹사이트 (https://public.wmo.int/en/water/dynamic-water-resources-assessment-tool)를 통해 193개 회원국에 보급되기 시작하였다. DWAT은 전 세계가 무료로 이용할 수 있는 수자원평가 도구로, 지하수, 용수이용 뿐만 아니라 지표수를 고려한 수자원계획 및 관리를 위해 중⋅소규모 하천 유역에 적용될 수 있다. 특히, 논 지역의 유출특성을 모의할 수 있는 모듈을 탑재하였으며, 고위도 및 고산지대의 수문학적 특성을 반영할 수 있는 융설 모듈이 포함되었고, 매개변수 최적화 기능도 포함되었다. WMO는 수자원분야 주요사업 중 하나인 "전지구 수문현황 및 전망 시스템(HYDROSOS, global HYDROlogical Status and Outlook System)" 사업을 추진하고 있다. 본 사업은 전지구 기상예보를 활용하여 주요 지점의 자연 유출량에 대한 현황과 예보를 수행하는 것을 목표로 한다. 2019년 6월 제18차 WMO 총회에서는 수자원분야 주요 사업인 HYDROSOS의 시범사업을 DWAT이 지원하는 것으로 의결되었다. 따라서 이러한 DWAT의 활용을 통해 대한민국의 수자원 평가 실무와 관련된 기술이 WMO 회원국에 지속적으로 보급될 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.194-194
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• 2018

현재까지 우리나라에서는 공식적으로 총 세 번의 전국 가능최대강수량(Probable Maximum Precipitation, PMP) 추정이 이루어졌다. 첫 번째는 1988년에 건설부 주도로 작성된 바 있는데, 1987년까지의 관측된 기상자료를 이용한 수문기상학적인 방법을 전국에 적용하여 한국가능최대강수량도를 작성하였다. 이후 12년 뒤인 2000년에 건설교통부 주도로 그 동안의 축적된 관측자료를 추가하여 한국가능최대강수량을 추정하였다(건설교통부, 2000a). 2000년의 전국 PMP도 추정은 WMO 보고서(WMO, 1986)를 가능한 충실히 반영하려는 노력이 있었으며, 과학적인 측면에서도 한층 진일보된 PMP도가 생산되었다고 평가할 수 있다. 그러나 2000년 이후 태풍 '루사' 또는 태풍 '매미'와 같은 관측 최대 강우량 기록을 경신하는 대형 호우사상들이 연이어서 발생하였기 때문에, 기존에 추정된 전국 PMP도에 대한 의문이 제기됨에 따라 해당 호우들을 추가하여 전국 PMP도를 개략적으로 재산정하여 제시한 바 있다(건설교통부, 2004). 국외에서는 PMP 추정의 표준으로 인정받고 있는 World Meteorological Organization (WMO) 보고서(WMO, 1986)가 2009년에 수정되어 발간됨에 따라 PMP 추정절차 중 일부 방법에 대한 기술적 보완이 이루어졌다(WMO, 2009). 그러나 우리나라의 경우 2008년 PMP 및 PMF 산정절차 지침 수립 용역 이후 중앙정부 차원의 전국 PMP도 생산은 더 이상 추진되고 있지 않은 상태이기 때문에, 2018년 현재에도 2000년 혹은 2004년에 재산정된 전국 PMP도를 그대로 수자원 실무에 이용하고 있다. 이에 본 연구에서는 WMO(2009)에서 제시하는 방법 및 최근 국외에서 적용되고 있는 PMP 추정방식을 참고하여 1973년부터 2017년까지의 기상 자료를 이용하여 전국을 대상으로 PMP를 추정하여 다양한 지속시간별 영향면적별 전국 PMP도를 생산하고 기존 2004년 보고서 결과와 비교를 수행하고자 한다.

• Atmosphere
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• v.15 no.1
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• pp.35-46
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• 2005

Today, the outreach of National Meteorological Service such as PC cluster based Numerical Weather Prediction (NWP) technique is vigorous in the world wide. In this regard, WMO (World Meteorological Organization) asked KMA (Korea Meteorological Administration) to formulate a regional project, which cover most of RA II members, using similar technical system with KMA's. In that sense, Meteorological Research Institute (METRI) in KMA developed Mongolian NWP System (MNWPS) based on PC cluster and transferred the technology to Weather Service Center in Mongolia. The hybrid parallel algorithm and channel bonding technique were adopted to cut cost and showed 41% faster performance than single MPI (Message Passing Interface) approach. The cluster technique of Beowulf type was also adopted for convenient management and saving resources. The Linux based free operating system provide very cost effective solution for operating multi-nodes. Additionally, the GNU software provide many tools, utilities and applications for construction and management of a cluster. A flash flood event happened in Mongolia (2 September 2003) was selected for test run, and MNWPS successfully simulated the event with initial and boundary condition from Global Data Assimilation and Prediction System (GDAPS) of KMA. Now, the cluster based NWP System in Mongolia has been operated for local prediction around the region and provided various auxiliary charts.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.24 no.1
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• pp.19-27
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• 1996

The ozone layer monitoring program of the Global Environment Laboratory at Yonsei University in Seoul, established as one of the Global Ozone Observing System($GO_3OS$) of the World Meteorological Organization(WMO), has been carried out daily by measuring total ozone and its vertical distribution using a Dobson Ozone Spectrophotometer(Beck #124) since 1984. In this paper, we review the organization and the historical background of ozone measurements in Korea, describe data acquisition and analysis systems, and briefly summarize the results from our ozone observations.