• 제목/요약/키워드: Weather components

검색결과 206건 처리시간 0.033초

레이더기반 다중센서활용 강수추정기술의 개발 (Development of Radar-Based Multi-Sensor Quantitative Precipitation Estimation Technique)

  • 이재경;김지현;박혜숙;석미경
    • 대기
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    • 제24권3호
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    • pp.433-444
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    • 2014
  • Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

일별 온도의 연속형 자기회귀모형 연구 - 6개 광역시를 중심으로 - (The research on daily temperature using continuous AR model)

  • 김지영;정기호
    • Journal of the Korean Data and Information Science Society
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    • 제25권1호
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    • pp.155-167
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    • 2014
  • 본 연구는 기후파생상품의 가격결정 연구를 위한 중간과정으로서 우리나라 일별 평균기온에 대한 연속형 시계열 모형을 추정한다. 6개 광역도시를 대상으로 1954년 1월 1일부터 2010년 12월 31일까지의 57년간 일별 기온 시계열을 추세, 계절성, 불규칙 변동으로 구분하여 분석하였다. 특히 불규칙 성분은 연속형 자기회귀모형을 적용하였다. 분석결과, (1) 57년의 비교적 장기간 온도 시계열을 적용함으로써, 우리나라 선행연구의 결과와는 다르게 추세 성분이 통계적 유의성을 갖는 것으로 나타났다. 특히 추세성분의 기울기가 양의 부호를 가짐으로써 지구온난화의 추이가 우리나라에서 진행 중임을 보였다. (2) 추세와 계절성분이 제거된 불규칙성분에 대해 단위근 검정을 적용한 결과, 6개 광역시 모두에 대해 단위근이 없는 안정적인 것으로 나타났다. (3) 불규칙 성분에 대해 연속형 모형인 CAR모형을 적용한 결과, 차수가 3인 CAR(3)가 적합한 것으로 나타났으며 이러한 결과는 국외문헌의 결과와도 일치한다. 파생상품의 가격결정에는 기초자산의 연속형 시계열 모형의 개발이 가장 중요하므로 본 연구의 결과는 기후파생상품의 가격결정 연구에 활용될 수 있을 것이다.

연안 여객선의 내항성능 위험도를 이용한 항해 안전성 평가에 관한 연구 (Evaluation of the Ship′s Navigational Safety Using Dangerousness on the Korean Coast)

  • 김철승;정창현;김순갑;공길영;설동일;이윤석
    • 해양환경안전학회지
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    • 제9권1호
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    • pp.41-50
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    • 2003
  • 한국 연안의 각 항로에 취항하고 있는 대표적인 선형의 여객선들을 대상으로, 각 선형별로 선체운동 계산, 내항성능을 분석하여 선박의 안전성을 평가하였다. 이를 위하여 선박의 안전운항과 가장 밀접한 관련을 갖는 바람과 파랑을 주요 해역별로 비교 분석하였다. 이러한 기강정보를 입력요소로 하여 주요해역을 항행하는 대표적인 선형의 여객선들에 대하여 수치 시뮬레이션을 실시하여 여객선의 항해안정성을 평가하였다.

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Space Weather Effects on GEO Satellite Anomalies during 1997-2009

  • 최호성;이재진;조경석;조일현;박영득
    • 천문학회보
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    • 제35권1호
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    • pp.30.2-30.2
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    • 2010
  • Numerous operational anomalies and satellite failures have been reported since the beginnings of the "space age". Space weather effects on modern spacecraft systems have been emphasized more and more as increasing their complexity and capability. Energetic particles potentially can destroy and degrade electronic components in satellites. We analyzed the geostationary (GEO) satellite anomalies during 1997-2009 to search possible influences of space weather on the satellite anomalies like power problem, control processor problem, attitude control problem, etc. For this we use particle data from GOES and LANL satellites to investigate space weather effects on the GEO satellites' anomalies depending on Kp index, local time, seasonal variation, and high-energy electron contribution. As results, we obtained following results: (1) there is a good correlation between geomagnetic index(Kp) and anomaly occurrences of the GEO satellite; (2) especially during the solar minimum, occurrence of the satellite anomalies are related to electron flux increase due to high speed solar wind; (3) satellite anomalies occurred more preferentially in the midnight and dawn sector than noon and dusk sector; (4) and the anomalies occurred twice more in Spring and Fall than Summer and Winter; (5) the electron with the lowest energy channel (50-75keV) has the highest correlation (cc=0.758) with the anomalies. High association between the anomalies and the low energy electrons could be understand by the facts that electron fluxes in the spring and fall are stronger than those in the summer and winter, and low-energy electron flux is more concentrated in the dawn sector where the GEO satellite anomalies occurred more frequently than high-energy electron flux. While we could not identify what cause such local time dependences, our results shows that low-energy electrons (~100keV) could be main source of the satellite anomaly, which should be carefully taken into account of operating satellites.

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비축대칭 3차원 모조 소용돌이를 이용한 열대저기압의 진로 및 강도예측 (Tropical Cyclone Track and Intensity Forecast Using Asymmetric 3-Dimensional Bogus Vortex)

  • 이재덕;정형빈;강현규;권인혁
    • 대기
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    • 제24권2호
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    • pp.207-223
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    • 2014
  • The bogussing method was further developed by incorporating the asymmetric component into the symmetric bogus tropical cyclone of the Structure Adjustable Balanced Vortex (SABV). The asymmetric component is separated from the disturbance field associated with the tropical cyclone by establishing local polar coordinates whose center is the location of the tropical cyclone. The relative importance of wave components in azimuthal direction was evaluated, and only two or three wave components with large amplitude are added to the symmetric components. Using the Weather Research and Forecast model (WRF), initialized with the asymmetric bogus vortex, the track and central pressure of tropical cyclones were predicted. Nine tropical cyclones, which passed over Korean peninsula during 2010~2012 were selected to assess the effect of asymmetric components. Compared to the symmetric bogus tropical cyclone, the track forecast error was reduced by about 18.9% and 17.4% for 48 hours and 72 hours forecast, while the central pressure error was not improved significantly. The results suggest that the inclusion of asymmetric component is necessary to improve the track forecast of tropical cyclones.

복잡 지형의 대기질 예측을 위한 지상자료동화의 효용성에 관한 수치연구 (Numerical Study on Surface Data Assimilation for Estimation of Air Quality in Complex Terrain)

  • 이순환;김헌숙;이화운
    • 한국대기환경학회지
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    • 제20권4호
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    • pp.523-537
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    • 2004
  • In order to raise the accuracy of meteorological data, several numerical experiments about the usefulness of data assimilation to prediction of air pollution was carried out. Used data for data assimilation are surface meteorological components observed by Automatical Weather System with high spatial density. The usage of surface data assimilation gives changes of temperature and wind fields and the change caused by the influence of land-use on meterological simulation is more sensitive at night than noon. The data quality in assimilation it also one of the important factors to predict the meteorological field precisely and through the static IOA (Index of Agreement), simulated meteorological components with selected limited surface data assimilation are agree well with observations.

Evaluation of Pathogenic Variability Based on Leaf Blotch Disease Development Components of Bipolaris sorokiniana in Triticum aestivum and Agroclimatic Origin

  • Sultana, Sabiha;Adhikary, Sanjoy Kumar;Islam, Md. Monirul;Rahman, Sorder Mohammad Mahbubur
    • The Plant Pathology Journal
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    • 제34권2호
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    • pp.93-103
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    • 2018
  • Leaf blotch of wheat caused by Bipolaris sorokiniana is a major constraint to wheat production, causing significant yield reduction resulting in severe economic impact. The present study characterizes to determine and compare pathogenic variability exist/not based on components of leaf blotch disease development and level of aggressiveness due to agroclimatic condition of B. sorokiniana in wheat. A total of 169 virulent isolates of B. sorokiniana isolated from spot blotch infected leaf from different wheat growing agroclimate of Bangladesh. Pathogenic variability was investigated on a susceptible wheat variety 'kanchan' now in Bangladesh. A clear evidence of positive relationship among the components was recorded. From hierarchical cluster analysis five groups were originating among the isolates. It resolved that a large amount of pathogenic diversity exists in Bipolaris sorokiniana. Variation in aggressiveness was found among the isolates from different wheat growing areas. Most virulent isolates BS 24 and BS 33 belonging to High Ganges River Flood Plain agro-climatic zones considered by rice-wheat cropping pattern, hot and humid weather, high land and low organic matter content in soil. Positive relationship was found between pathogenic variability and aggressiveness with agro-climatic condition.

이어도 해양종합과학기지에서의 3차원 바람성분에 따른 에어로솔 수 농도 변동 특성 (The Variation of Aerosol Number Concentrations in Relation with 3D Wind Components in the Ieodo Ocean Research Station)

  • 박성화;장상민;이동인;정운선;정종훈;정성아;정창훈;김경식;김경익
    • 대기
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    • 제22권1호
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    • pp.97-107
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    • 2012
  • To investigate variation of aerosol number concentration at each different size with three-dimensional (3D) wind components in ocean area, aerosol particles and 3D wind components were measured in the Ieodo Ocean Research Station, which is located to 419 km southwest from Marado, the southernmost island of Korea, from 25 June to 8 July 2010. The Laser Particle Counter (LPC) and ultrasonic anemometer were used to measure the size of aerosol particles and 3D wind components (zonal (u), meridional (v), and vertical (w) wind) respectively. Surface weather chart, NCEP/NCAR reanalysis data and sounding data were used to analyze the synoptic condition. The distribution of aerosol number concentration had a large variation from bigger particles more than 1.0 ${\mu}m$ in diameter by wind direction during precipitation. In the number concentration of aerosol particles with respect to the weather conditions, particles larger than 1.0 ${\mu}m$ in size were decreased and sustained to the similar concentration at smaller particles during precipitation. The increase in aerosol number concentration was due to the sea-salt particles which was suspended by southwesterly and upward winds. In addition, the aerosol number concentration with vertical wind flow could be related with the occurrence and increasing mechanism of aerosol in marine boundary layer.

인공신경망 기법을 이용한 장래 잠재증발산량 산정 (Estimation of Future Reference Crop Evapotranspiration using Artificial Neural Networks)

  • 이은정;강문성;박정안;최진영;박승우
    • 한국농공학회논문집
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    • 제52권5호
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    • pp.1-9
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    • 2010
  • Evapotranspiration (ET) is one of the basic components of the hydrologic cycle and is essential for estimating irrigation water requirements. In this study, artificial neural network (ANN) models for reference crop evapotranspiration ($ET_0$) estimation were developed on a monthly basis (May~October). The models were trained and tested for Suwon, Korea. Four climate factors, daily maximum temperature ($T_{max}$), daily minimum temperature ($T_{min}$), rainfall (R), and solar radiation (S) were used as the input parameters of the models. The target values of the models were calculated using Food and Agriculture Organization (FAO) Penman-Monteith equation. Future climate data were generated using LARS-WG (Long Ashton Research Station-Weather Generator), stochastic weather generator, based on HadCM3 (Hadley Centre Coupled Model, ver.3) A1B scenario. The evapotranspirations were 549.7 mm/yr in baseline period (1973-2008), 558.1 mm/yr in 2011-2030, 593.0 mm/yr in 2046-2065, and 641.1 mm/yr in 2080-2099. The results showed that the ANN models achieved good performances in estimating future reference crop evapotranspiration.