• Title/Summary/Keyword: 자료동화

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Development of Meso-scale Short Range NWP System for the Cheju Regional Meteorological Office, Korea (제주 지역에 적합한 중규모 단시간 예측 시스템의 개발)

  • Kim, Yong-Sang;Choi, Jun-Tae;Lee, Yong-Hee;Oh, Jai-Ho
    • Journal of the Korean earth science society
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    • v.22 no.3
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    • pp.186-194
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    • 2001

  • The operational meso-scale short range NWP system was developed for Cheju Regional Meteorological Office located at Cheju island, Korea. The Central Meteorological Service Center, KMA has reported the information on numerical weather prediction every 12 hours. But this information is not enough to determine the detail forecast for the regional meteorological office because the terrain of the Korean peninsula is very complex and the resolution of the numerical model provided by KMA headquarter is too coarse to resolve the local severe weather system such as heavy rainfall. LAPS and MM5 models were chosen for three-dimentional data assimilation and numerical weather prediction tools respectively. LAPS was designed to provide the initial data to all regional numerical prediction models including MM5. Synoptic observational data from GTS, satellite brightness temperature data from GMS-5 and the composite reflectivity data from 5 radar sites were used in the LAPS data assimilation for producing the initial data. MM5 was performed on PC-cluster based on 16 pentium CPUs which was one of the cheapest distributed parallel computer in these days. We named this system as Halla Short Range Prediction System (HSRPS). HSRPS was verified by heavy rainfall case in July 9, 1999, it showed that HSRPS well resolved local severe weather which was not simulated by 30 km MM5/KMA. Especially, the structure of rainfall amount was very close to the corresponding observation. HSRPS will be operating every 6 hours in the Cheju Regional Meteorological Office from April 2000.

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Development of Realtime Dam's Hydrologic Variables Prediction Model using Observed Data Assimilation and Reservoir Operation Techniques (관측자료 동화기법과 댐운영을 고려한 실시간 댐 수문량 예측모형 개발)

  • Lee, Byong Ju;Jung, Il-Won;Jung, Hyun-Sook;Bae, Deg Hyo
    • Journal of Korea Water Resources Association
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    • v.46 no.7
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    • pp.755-765
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    • 2013

  • This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

  • https://doi.org/10.3741/JKWRA.2013.46.7.755 인용 PDF KSCI

Intercomparison of the Global Ocean Reanalysis Data (전지구 해양 재분석 자료 비교 분석)

  • Chang, You-Soon
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.20 no.2
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    • pp.102-118
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    • 2015

  • This study summarized the results of the international ocean reanalysis intercomparison project. We introduced the characteristics of various ocean reanalysis systems and analyzed the assimilated performance on the typical eight oceanic variables (heat content, steric height, sea level, surface heat fluxes, mixed layer depth, subsurface salinity, depth of $20^{\circ}C$ isotherm, sea ice). In general, ensemble means show better estimations than those of any individual ocean reanalysis, but it depends on analyzed regions and variables. Among the eight oceanic variables, salinity and sea ice variabilities have large spreads among models. The deep sea, Southern Ocean, and coastal regions including western boundary current commonly appear as the areas with largest uncertainty between different objective analyses and assimilation models. We expect that intercomparison project for the ocean assimilation models independently operated in Korea should be processed, which allows us to join relevant international programs in the near future.

  • https://doi.org/10.7850/jkso.2015.20.2.102 인용 PDF KSCI

Estimation of Evapotranspiration using Satellite data and Meteorological Model (인공 위성과 기상 모형을 이용한 증발산 추정)

  • Jang, Keun-Chang;Kang, Sin-Kyu;Kim, Jea-Chul;Kim, Joon
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.213-218
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    • 2009

  • 에너지 전달 과정과 밀접한 관계가 있는 증발산(Evapotranspiration)은 기후 변화나 육상 생태계 생산성에서 매우 중요한 요소이며, 수문학적 순환과 지역적 물 관리 측면에서 매우 중요하다. 최근 인공위성을 이용하여 증발산을 추정하기 위한 노력이 많이 진행되고 있으며, 특히 MODIS (Moderate Resolution Imaging Spectroradiometer)는 증발산을 추정하기 위한 좋은 정보를 제공하고 있다 하지만, 구름 등에 의한 증발산 입력 자료 결측은 전체 자료의 획득률을 낮추고, 연속적인 증발산 모니터 링을 제한한다. 따라서 본 연구에서는 MODIS 기반의 증발산 입력 자료의 개선하여 서로 다른 식생과 지형 구조를 갖는 플럭스 연구지에 대한 증발산의 추정 및 평가하고, 남한에 대한 MODIS 기반의 증발산 지도 작성하였다. 또한 구름에 의해 결측된 날에 대해서는 MODIS-MM5 4차원 자료동화 기법을 이용한 증발산의 연속적인 모니터링 기법을 개발하였다. MODIS 기반의 증발산을 추정하기 위해 Revised RS-PM 알고리즘을 사용하였다. 증발산을 평가하기 위해 4 곳의 플럭스 연구지(광릉, 해남 이상 대한민국, 타카야마, 토마코아미 이상 일본) 자료와 비교하였고, 매우 신뢰성 있는 결과를 얻을 수 있었다. MODIS 입력 자료의 개선으로 획득률은 2배 가량 증가하였다. 남한에 대한 연간 증발산은 평균적으로 약 35%의 획득률 (365일 중 약 120일)과 함께 산출되었고, 시 공간적인 분포를 잘 나타내었다. 구름 낀 날에 대한 MODIS-MM5 자료 동화 기법의 적용은 증발산의 연속적인 모니터링을 가능하게 하였다.

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