• Title/Summary/Keyword: Meteorological Prediction Data

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Development of 3D Visualization Technology for Meteorological Data (기상자료 3차원 가시화 기술개발 연구)

  • Seo In Bum;Joh Min Su;Yun Ja Young
    • Journal of the Korean Society of Visualization
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    • v.1 no.2
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    • pp.58-70
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    • 2003
  • Meteorological data contains observation and numerical weather prediction model output data. The computerized analysis and visualization of meteorological data often requires very high computing capability due to the large size and complex structure of the data. Because the meteorological data is frequently formed in multi-variables, 3-dimensional and time-series form, it is very important to visualize and analyze the data in 3D spatial domain in order to get more understanding about the meteorological phenomena. In this research, we developed interactive 3-dimensional visualization techniques for visualizing meteorological data on a PC environment such as volume rendering, iso-surface rendering or stream line. The visualization techniques developed in this research are expected to be effectively used as basic technologies not only for deeper understanding and more exact prediction about meteorological environments but also for scientific and spatial data visualization research in any field from which three dimensional data comes out such as oceanography, earth science, and aeronautical engineering.

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Study on the Impact of Various Observations Data Assimilation on the Meteorological Predictions over Eastern Part of the Korean Peninsula (관측자료별 자료동화 성능이 한반도 동부 지역 기상 예보에 미치는 영향 분석 연구)

  • Kim, Ji-Seon;Lee, Soon-Hwan;Sohn, Keon-Tae
    • Journal of Environmental Science International
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    • v.27 no.11
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    • pp.1141-1154
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    • 2018
  • Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

A Study on Multi-site Rainfall Prediction Model using Real-time Meteorological Data (실시간 기상자료를 이용한 다지점 강우 예측모형 연구)

  • Jung, Jae-Sung;lee, Jang-Choon;Park, Young-Ki
    • Journal of Environmental Science International
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    • v.6 no.3
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    • pp.205-211
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    • 1997
  • For the prediction of multi-site rainfall with radar data and ground meteorological data, a rainfall prediction model was proposed, which uses the neural network theory, a kind of artifical Intelligence technique. The Input layer of the prediction model was constructed with current ground meteorological data, their variation, moving vectors of rain- fall field and digital terrain of the measuring site, and the output layer was constructed with the predicted rainfall up to 3 hours. In the application of the prediction model to the Pyungchang river basin, the learning results of neural network prediction model showed more Improved results than the parameter estimation results of an existing physically based model. And the proposed model comparisonally well predicted the time distribution of ralnfall.

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Crime Prediction Model based on Meteorological Changes and Discomfort Index (기상변화 및 불쾌지수에 따른 범죄발생 예측 모델)

  • Kim, JongMin;Kim, MinSu;Kim, Kuinam J.
    • Convergence Security Journal
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    • v.14 no.6_2
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    • pp.89-95
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    • 2014
  • This study analyzed a correlation between crime and meteorological changes and discomfort index of Seoul and p resented a prediction expression through the regression analysis. For data used in this study, crime data from Januar y 2008 to December 2012 of Seoul Metropolitan Police Agency and meteorological records and discomfort index recor ded in the Meteorological Agency through the portal sites were used. Based on this data, SPSS 18.0 was used for the regression analysis and the analysis of correlation between crime and meteorological changes and discomfort index and a prediction expression was derived through the analysis and the risk index was shown in 5 steps depending on predicted values obtained through the prediction expression derived. The risk index of 5 steps classified like this is considered to be used as important data for crime prevention activities.

An impact of meteorological Initial field and data assimilation on CMAQ ozone prediction in the Seoul Metropolitan Area during June, 2007 (기상 모델의 초기장 및 자료동화 차이에 따른 수도권 지역의 CMAQ 오존 예측 결과 - 2007년 6월 수도권 고농도 오존 사례 연구 -)

  • Lee, Dae-Gyun;Lee, Mi-Hyang;Lee, Yong-Mi;Yoo, Chul;Hong, Sung-Chul;Jang, Kee-Won;Hong, Ji-Hyung
    • Journal of Environmental Impact Assessment
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    • v.22 no.6
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    • pp.609-626
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    • 2013
  • Air quality models have been widely used to study and simulate many air quality issues. In the simulation, it is important to raise the accuracy of meteorological predicted data because the results of air quality modeling is deeply connected with meteorological fields. Therefore in this study, we analyzed the effects of meteorological fields on the air quality simulation. This study was designed to evaluate MM5 predictions by using different initial condition data and different observations utilized in the data assimilation. Among meteorological scenarios according to these input data, the results of meteorological simulation using National Centers for Environmental Prediction (Final) Operational Global Analysis data were in closer agreement with the observations and resulted in better prediction on ozone concentration. And in Seoul, observations from Regional Meteorological Office for data assimilations of MM5 were suitable to predict ozone concentration. In other areas, data assimilation using both observations from Regional Meteorological Office and Automatical Weather System provided valid method to simulate the trends of meteorological fields and ozone concentrations. However, it is necessary to vertify the accuracy of AWS data in advance because slightly overestimated wind speed used in the data assimilation with AWS data could result in underestimation of high ozone concentrations.

Red Tide Prediction in the Korean Coastal Areas by RS and GIS

  • Yoon, Hong-Joo
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.332-335
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    • 2006
  • Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water temperature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations). Finally our purpose is support to the prediction information for the possible red tide occurrence by coastal meteorological information and contribute to reduce the red tide disaster by the prediction technique for red tide.

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Low-Level Wind Shear (LLWS) Forecasts at Jeju International Airport using the KMAPP (고해상도 KMAPP 자료를 활용한 제주국제공항에서 저층 윈드시어 예측)

  • Min, Byunghoon;Kim, Yeon-Hee;Choi, Hee-Wook;Jeong, Hyeong-Se;Kim, Kyu-Rang;Kim, Seungbum
    • Atmosphere
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    • v.30 no.3
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    • pp.277-291
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    • 2020
  • Low-level wind shear (LLWS) events on glide path at Jeju International Airport (CJU) are evaluated using the Aircraft Meteorological Data Relay (AMDAR) and Korea Meteorological Administration Post-Processing (KMAPP) with 100 m spatial resolution. LLWS that occurs in the complex terrains such as Mt. Halla on the Jeju Island affects directly aircraft approaching to and/or departing from the CJU. For this reason, accurate prediction of LLWS events is important in the CJU. Therefore, the use of high-resolution Numerical Weather Prediction (NWP)-based forecasts is necessary to cover and resolve these small-scale LLWS events. The LLWS forecasts based on the KMAPP along the glide paths heading to the CJU is developed and evaluated using the AMDAR observation data. The KMAPP-LLWS developed in this paper successfully detected the moderate-or-greater wind shear (strong than 5 knots per 100 feet) occurred on the glide paths at CJU. In particular, this wind shear prediction system showed better performance than conventional 1-D column-based wind shear forecast.

Development and Evaluation of the High Resolution Limited Area Ensemble Prediction System in the Korea Meteorological Administration (기상청 고해상도 국지 앙상블 예측 시스템 구축 및 성능 검증)

  • Kim, SeHyun;Kim, Hyun Mee;Kay, Jun Kyung;Lee, Seung-Woo
    • Atmosphere
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    • v.25 no.1
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    • pp.67-83
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    • 2015
  • Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

Verification of Low-Level Wind Shear Prediction System Using Aircraft Meteorological Data Relay (AMDAR) (항공기 기상관측자료(AMDAR)를 이용한 인천국제공항 저고도 급변풍 예측시스템 검증)

  • Jae-Hyeok Seok;Hee-Wook Choi;Geun-Hoi Kim;Sang-Sam Lee;Yong Hee Lee
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.31 no.3
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    • pp.59-70
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    • 2023
  • In order to predict low-level wind shear at Incheon International Airport (RKSI), a Low-Level Wind Shear prediction system (KMAP-LLWS) along the runway take-off and landing route at RKSI was established using Korea Meteorological Administration Post-Processing (KMAP). For the performance evaluation, the case of low-level wind shear cases calculated from Aircraft Meteorological Data Relay (AMDAR) from July 2021 to June 2022 was used. As a result of verification using the performance evaluation index, POD, FAR, CSI, and TSS were 0.5, 0.85, 0.13, and 0.34, respectively, and the prediction performance was improved by POD, CSI, and TSS compared to the Low-Level Wind Shear prediction system (LDPS-LLWS) calculated using the Korea Meteorological Administration's Local Data Assimilation and Prediction System (LDAPS). This means that the use of high-resolution numerical models improves the predictability of wind changes. In addition, to improve the high FAR of KMAP-LLWS, the threshold for low-level wind shear strength was adjusted. As a result, the most effective low-level wind shear threshold at 8.5 knot/100 ft was derived. This study suggests that it is possible to predict and respond to low-level wind shear at RKSI. In addition, it will be possible to predict low-level wind shear at other airports without wind shear observation equipment by applying the KMAP-LLWS.