• 제목/요약/키워드: Regional Data Assimilation and Prediction System

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RDAPS 모델의 강수량과 실측강수량의 비교를 통한 적용성 검토 (Comparison Study of Rainfall Data Using RDAPS Model and Observed Rainfall Data)

  • 정창삼;신주영;정영훈;허준행
    • 한국수자원학회논문집
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    • 제44권3호
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    • pp.221-230
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    • 2011
  • 최근 우리나라뿐만 아니라 전 세계적으로 기후변화에 따른 국지성 호우의 증가로 피해가 증가하고 있고 그에 따른 대책으로 단기예보의 중요성이 높아지고 있다. 우리나라의 기상청에서는 전구 모형인 GDAPS와 지역 모델인 RDAPS를 이용하여 정량적 예보인 수치 예보를 하고 있다. RDAPS 모델을 이용하여 생성된 자료는 3시간의 누적 강수량으로 48시간에 대한 예측 자료를 12시간 간격으로 00UTC와 12UTC를 생성한다. 본 연구에서는 2005년의 RDAPS의 결과를 9가지의 경우에 대하여 일강수량으로 변환하였으며, 금강유역을 대상으로 면적평균강수량 (MAP)을 산정하였다. 또한, 기상청 강우관측소의 관측강우량과 절대상대오차평균 (AARE)을 산정하여 가장 정확한 변환의 방법을 제시하고 적용성을 검토하였다.

PNU CGCM V1.1을 이용한 12개월 앙상블 예측 시스템의 개발 (Development of 12-month Ensemble Prediction System Using PNU CGCM V1.1)

  • 안중배;이수봉;류상범
    • 대기
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    • 제22권4호
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    • pp.455-464
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    • 2012
  • This study investigates a 12 month-lead predictability of PNU Coupled General Circulation Model (CGCM) V1.1 hindcast, for which an oceanic data assimilated initialization is used to generate ocean initial condition. The CGCM, a participant model of APEC Climate Center (APCC) long-lead multi-model ensemble system, has been initialized at each and every month and performed 12-month-lead hindcast for each month during 1980 to 2011. The 12-month-lead hindcast consisted of 2-5 ensembles and this study verified the ensemble averaged hindcast. As for the sea-surface temperature concerns, it remained high level of confidence especially over the tropical Pacific and the mid-latitude central Pacific with slight declining of temporal correlation coefficients (TCC) as lead month increased. The CGCM revealed trustworthy ENSO prediction skills in most of hindcasts, in particular. For atmospheric variables, like air temperature, precipitation, and geopotential height at 500hPa, reliable prediction results have been shown during entire lead time in most of domain, particularly over the equatorial region. Though the TCCs of hindcasted precipitation are lower than other variables, a skillful precipitation forecasts is also shown over highly variable regions such as ITCZ. This study also revealed that there are seasonal and regional dependencies on predictability for each variable and lead.

Production of Fine-resolution Agrometeorological Data Using Climate Model

  • Ahn, Joong-Bae;Shim, Kyo-Moon;Lee, Deog-Bae;Kang, Su-Chul;Hur, Jina
    • 한국농림기상학회:학술대회논문집
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    • 한국농림기상학회 2011년도 학술발표회
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    • pp.20-27
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    • 2011
  • A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.

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종관 특성에 따른 지상 및 연직 관측자료 동화가 수평 및 연직 확산장에 미치는 영향 (The Effect of Surface and Vertical Observation Data Assimilation on the Horizontal and Vertical Flow Fields Depending on the Upper Wind Conditions)

  • 최현정;이화운;김민정
    • 한국대기환경학회지
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    • 제26권2호
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    • pp.177-189
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    • 2010
  • In order to incorporate correctly the large or local scale circulation in an atmospheric model, a nudging term is introduced into the equation of motion. The MM5 model was used to assess the meteorological values differences in each case, during ozone episode days in Gwangyang bay. The main objective of this study is to investigate the effect of horizontal and vertical flow fields according to the surface and vertical observation data assimilation by upper wind conditions. Therefore, we carried out several numerical experiments with various parameterization methods for nudging coefficient considering the upper wind conditions (synoptic or asynoptic condition). Nudging considering the synoptic and asynoptic nudging coefficient does have a clear advantage over dynamic initialization, therefore appropriate limitation of these nudging coefficient values on its upper wind conditions is necessary before making an assessment. Obviously, under the weak synoptic wind, there was apparent advantage associated with nudging coefficient by the regional difference. The accuracy for the prediction of the meteorological values has been improved by applying the appropriate PBL (Planetary Boundary Layer) limitation of circulation.

호남지방 고층관측자료동화가 수치기상예보에 미치는 영향에 관한 연구 (A Study on the Influence of Aerological Observation Data Assimilation at Honam Area on Numerical Weather Prediction)

  • 류찬수;원효성;이순환
    • 한국지구과학회지
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    • 제26권1호
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    • pp.66-77
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    • 2005
  • 한반도 남서해안에 위치한 흑산도 고층관측이 2003년 6월 1일부터 실시되고 있다. 이러한 흑산도 관측자료에 의한 수치예보개선효과를 보기 위하여 광주의 관측자료와 비교 분석하였다. 분석에는 MM5를 기본으로 제작한 호남지방 고밀도 예측시스템을 이용하였다. 먼저 지표면 마찰과 현열플러스의 차이에 의하여 광주와 흑산도의 바람장과 온도장은 다르게 나타났으며, 광주와 흑산도의 자료를 모두 동화시킨 수치예측 바람장과 기상장이 관측과 제일 잘 일치하였다. 강수면에서 비록 강수량은 과소평가를 하고 있으나, 강수시간과 강수구역은 흑산도자료를 포함하여 자료동화를 시킨 경우 관측과 유사하게 나타났다.

WRF 모형에서 한반도 여름철 강수 예측에 모의영역이 미치는 영향 (Effect of Model Domain on Summer Precipitation Predictions over the Korean Peninsula in WRF Model)

  • 김형규;이혜영;김주완;이승우;부경온;이송이
    • 대기
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    • 제31권1호
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    • pp.17-28
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    • 2021
  • We investigated the impact of domain size on the simulated summer precipitation over the Korean Peninsula using the Weather Research and Forecasting (WRF) model. Two different domains are integrated up to 72-hours from 29 June 2017 to 28 July 2017 when the Changma front is active. The domain sizes are adopted from previous RDAPS (Regional Data Assimilation and Prediction System) and current LDAPS (Local Data Assimilation and Prediction System) operated by the Korea Meteorological Administration, while other model configurations are fixed identically. We found that the larger domain size showed better prediction skills, especially in precipitation forecast performance. This performance improvement is particularly noticeable over the central region of the Korean Peninsula. Comparisons of physical aspects of each variable revealed that the inflow of moisture flux from the East China Sea was well reproduced in the experiment with a large model domain due to a more realistic North Pacific high compared to the small domain experiment. These results suggest that the North Pacific anticyclone could be an important factor for the precipitation forecast during the summer-time over the Korean Peninsula.

광역 위성 영상과 수치예보자료를 이용한 여름철 강수량 예측 (Summer Precipitation Forecast Using Satellite Data and Numerical Weather Forecast Model Data)

  • 김광섭;조소현
    • 한국수자원학회논문집
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    • 제45권7호
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    • pp.631-641
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    • 2012
  • 본 연구에서는 지상의 관측 자료와 광역의 정보를 제공하는 수치 예보 모형 자료 및 인공위성 자료를 이용하고 자료와 강수예측치의 물리적 상관 특성을 나타내기 위하여 자료 사이의 비선형 거동을 잘 나타내는 신경망 모형에 적용시켜 단시간 강수 예측을 수행하였다. 이를 위하여 서울지점에 대하여 현재로부터 3시간, 6시간, 9시간, 12시간의 선행시간을 가지는 인공위성자료(MTSAT-1R) 및 수치 예보 모형 자료(RDAPS, Regional Data Assimilation and Prediction System)와 실시간 전송되는 자동 기상 관측 시스템(AWS, Automatic Weather System)의 관측치를 신경망 모형의 입력 자료로 하여 3시간, 6시간, 9시간, 12시간의 선행시간을 가지는 자료로 강수를 예측 할 수 있는 강수 예측 모형을 개발하였다. 장마와 태풍과 같이 전선형강수와 선풍형강수 등 강수 양상의 차이를 고려하기 위하여 6월, 7월과 8월, 9월 자료를 구분하여 신경망을 구축하였으며, 자료가용성에 기초하여 2006년에서 2008년 기간 동안에 대하여 모형을 학습하고 2009년에 대하여 모형의 적용성을 검증한 결과, 단시간 강수예측에 대한 모형의 적용 가능성을 보여주었으나 다양한 광역 자료와 인공신경망을 사용함에도 불구하고 단시간 강수예측의 정량적 정도향상을 위한 여지가 많음을 보여준다.

한반도에서 해상도 변화에 따른 지표면 일사량의 시공간 분포 (Temporal and Spatial Distributions of the Surface Solar Radiation by Spatial Resolutions on Korea Peninsula)

  • 이규태;조일성;지준범;최영진
    • 신재생에너지
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    • 제7권1호
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    • pp.22-28
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    • 2011
  • The surface solar radiations were calculated and analyzed with spatial resolutions (4 km and 1 km) using by GWNU (Gangneung-Wonju National University) solar radiation model. The GWNU solar radiation model is used various data such as aerosol optical thickness, ozone amount, total precipitable water and cloud factor are retrieved from Moderate Resolution Imaging Spectrometer (MODIS), Ozone Monitoring Instrument (OMI), MTSAT-1R satellite data and output of the Regional Data Assimilation Prediction System(RDAPS) model by Korea Meteorological Administration (KMA), respectively. The differences of spatial resolutions were analyzed with input data (especially, cloud factor from MTSAT-1R satellite). And the Maximum solar radiation by GWNU model were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud factor.

QAR 데이터 분석을 통한 항공난류 조기 인지 가능성 연구 (A Study on the Precursors of Aviation Turbulence via QAR Data Analysis)

  • 김인규;장조원
    • 한국항공운항학회지
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    • 제26권4호
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    • pp.36-42
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    • 2018
  • Although continuous passenger injuries and physical damages are repeated due to the unexpected aviation turbulence encountered during operations, there is still exist the limitation for preventing recurrence of similar events because the lack of real-time information and delay in technological developments regarding various operating conditions and variable weather phenomena. The purpose of this study is to compare and analyze the meteorological data of the aviation turbulence occurred and actual flight data extracted from the Quick Access Recorder(QAR) to provide some precursors that the pilot can identify aviation turbulence early by referring thru the flight instrumentation indications. The case applied for this study was recent event, a scheduled flight from Incheon Airport, Korea to Narita Airport, Japan that suddenly encountered turbulence at an altitude of approximately 14,000 feet during approach. According to the Korea Meteorological Administration(KMA)'s Regional Data Assessment and Prediction System(RDAPS) data, it was observed that the strong amount of vorticity in the rear area of jet stream, which existed near Mount Fuji at that time. The QAR data analysis shows significant changes in the aircraft's parameters such as Pitch and Roll angle, Static Air Temperature(SAT), and wind speed and direction in tens of seconds to minutes before encounter the turbulence. If the accumulate reliability of the data in addition and verification of various parameters with continuous analysis of additional cases, it can be the precursors for the pilot's effective and pre-emptive action and conservative prevention measures against aviation turbulence to reduce subsequent passenger injuries in the aviation operations.

Optimization of SWAN Wave Model to Improve the Accuracy of Winter Storm Wave Prediction in the East Sea

  • Son, Bongkyo;Do, Kideok
    • 한국해양공학회지
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    • 제35권4호
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    • pp.273-286
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    • 2021
  • In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.