• Title/Summary/Keyword: Atmospheric model

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Compatibility for the Typhoon Damages Predicted by Korea Risk Assessment Model Input Data (한국형 재해평가모형(RAM)의 초기입력자료 적합성 평가)

  • Park, Jong-Kil;Lee, Bo-Ram;Jung, Woo-Sik
    • Journal of Environmental Science International
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    • v.24 no.7
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    • pp.865-874
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    • 2015
  • This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.

Estimation of High Resolution Gridded Precipitation Using GIS and PRISM (GIS와 PRISM을 이용한 고해상도 격자형 강수량 추정)

  • Shin, Sung-Chul;Kim, Maeng-Ki;Suh, Myoung-Suk;Rha, Deuk-Kyun;Jang, Dong-Ho;Kim, Chan-Su;Lee, Woo-Seop;Kim, Yeon-Hee
    • Atmosphere
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    • v.18 no.1
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    • pp.71-81
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    • 2008
  • In this study, in order to estimate high resolution precipitation with monthly time scales, Parameter-elevation Regressions on Independent Slopes Model (PRISM) was modified and configured for Korean precipitation based on elevation, distance, topographic facet, and coastal proximity. Applying this statistical downscaling model to Korean precipitation for 5 years from 2001 to 2005, we have compiled monthly grid data with a horizontal resolution of 5-km and evaluated the model using bias, root mean square error (RMSE), and correlation coefficient between the observed and the estimated. Results show that bias, RMSE, and correlation coefficient of the estimated value have a range from 0.2% to 1.0%, 19.6% (June) to 43.9% (January), and 0.73 to 0.84, respectively, indicating that the modified Korean PRISM (K-PRISM) is reasonably worked by weighting factors, i.e., topographic effect and rain shadow effect.

Algorithm for Determining Aircraft Washing Intervals Using Atmospheric Corrosion Monitoring of Airbase Data and an Artificial Neural Network (인공신경망과 대기부식환경 모니터링 데이터를 이용한 항공기 세척주기 결정 알고리즘)

  • Hyeok-Jun Kwon;Dooyoul Lee
    • Corrosion Science and Technology
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    • v.22 no.5
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    • pp.377-386
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    • 2023
  • Aircraft washing is performed periodically for corrosion control. Currently, the aircraft washing interval is qualitatively set according to the geographical conditions of each base. We developed a washing interval determination algorithm based on atmospheric corrosion environment monitoring data at the Republic of Korea Air Force (ROKAF) bases and United States Air Force (USAF) bases to determine the optimal interval. The main factors of the washing interval decision algorithm were identified through hierarchical clustering, sensitivity analysis, and analysis of variance, and criteria were derived. To improve the classification accuracy, we developed a washing interval decision model based on an artificial neural network (ANN). The ANN model was calibrated and validated using the atmospheric corrosion environment monitoring data and washing intervals of the USAF bases. The new algorithm returned a three-level washing interval, depending on the corrosion rate of steel and the results of the ANN model. A new base-specific aircraft washing interval was proposed by inputting the atmospheric corrosion environment monitoring results of the ROKAF bases into the algorithm.

A Study on Atmospheric Environment Visualization by Integrating 3D City Model and CFD Model (3D City모델과 CFD 모델을 통합한 대기환경 시각화 연구)

  • An, Seung-Man;Lee, Ho-Yeong;Sung, Hyo-Hyun;Choi, Yeong-Jin;Woo, Jung-Hun
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.13-21
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    • 2011
  • The purpose of this study is enhancing CFD model by applying detailed and accurate CFD input data produced from 3D City model and integrating CFD model with 3D city model with OpenGL, 3D city aerodynamic simulation, and visualization tool. CFD_NIMR_SNU model developed by NIMR and SNU and 3D City model produced by NGII were used as input data. Wind flow and pollution diffusion simulator and viewer were developed in this study. Atmospheric environment simulation and visualization tool will save time and cost for urban climate planning and management by enhancing visual communication.

Long-term Forecast of Seasonal Precipitation in Korea using the Large-scale Predictors (광역규모 예측인자를 이용한 한반도 계절 강수량의 장기 예측)

  • Kim, Hwa-Su;Kwak, Chong-Heum;So, Seon-Sup;Suh, Myoung-Seok;Park, Chung-Kyu;Kim, Maeng-Ki
    • Journal of the Korean earth science society
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    • v.23 no.7
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    • pp.587-596
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    • 2002
  • A super ensemble model was developed for the seasonal prediction of regional precipitation in Korea using the lag correlated large scale predictors, based on the empirical orthogonal function (EOF) analysis and multiple linear regression model. The predictability of this model was also evaluated by cross-validation. Correlation between the predicted and the observed value obtained from the super ensemble model showed 0.73 in spring, 0.61 in summer, 0.69 in autumn and 0.75 in winter. The predictability of categorical forecasting was also evaluated based on the three classes such as above normal, near normal and below normal that are clearly defined in terms of a priori specified by threshold values. Categorical forecasting by the super ensemble model has a hit rate with a range from 0.42 to 0.74 in seasonal precipitation.

A Study on Mesoscale Atmospheric Dispersion of Radioactive Particles Released from Nuclear Power Plants (원전부지 주변 국지순환에 따른 방사성 물질의 대기확산 특성 연구)

  • Lee, Gab-Bock;Lee, Myung-Chan;Song, Young-I1
    • Journal of Radiation Protection and Research
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    • v.22 no.4
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    • pp.273-288
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    • 1997
  • A three dimensional sea-land breeze model and Lagrangian particle dispersion model have been employed for the study on the mesoscale atmospheric dispersion of radioactive materials released from Wolsung NPPs. In this study, atmospheric dispersion simulations are carried out under two synoptic weather conditions : the geostrophic flow is a weak northerly wind(CASE 1) and a strong northerly wind(CASE 2) on a clear day in spring. The results show that atmospheric dispersion is affected by sea-land breeze and the recirculation of particles by the change of wind direction between sea breeze and land breeze plays an important role in atmospheric concentration distribution of radoactive materials.

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Improvements in the simulation of sea surface wind over the complex coastal area- I : Assessment of current operational model (복잡 해안지역 해상풍 모의의 정확도 개선- I : 현업모델의 평가)

  • Bae Joo-Hyun;Kim Yoo-Keun;Oh In-Bo;Jeong Ju-Hee;Kweon Ji-Hye;Seo Jang-Won
    • Journal of Environmental Science International
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    • v.14 no.7
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    • pp.657-667
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    • 2005
  • In this study, we focused on the improvements in the simulation of sea surface wind over the complex coastal area. MM5 model being currently used to predict sea surface wind at Korea Meteorological Administration, was used to verify the accuracy to estimate the local wind field. A case study was performed on clear days with weak wind speed(4 m/s), chosen by the analysis of observations. The model simulations were conducted in the southeastern area of Korea during the selected periods, and observational data such as AWS, buoy and QuikSCAT were used to compare with the calculated wind components to investigate if simulated wind field could follow the tendency of the real atmospheric wind field. Results showed that current operational model, MM5, does not estimate accurately sea surface wind and the wind over the coastal area. The calculated wind speed was overestimated along the complex coastal regions but it was underestimated in islands and over the sea. The calculated diurnal changes of wind direction could not follow well the tendency of the observed wind, especially at nighttime. In order to exceed the limitations, data assimilation with high resolution data and more specificated geographical information is expected as a next best policy to estimate accurately the environment of local marine wind field.