• Title/Summary/Keyword: Unified Model(UM)

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Development of Road Surface Temperature Prediction Model using the Unified Model output (UM-Road) (UM 자료를 이용한 노면온도예측모델(UM-Road)의 개발)

  • Park, Moon-Soo;Joo, Seung Jin;Son, Young Tae
    • Atmosphere
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    • v.24 no.4
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    • pp.471-479
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    • 2014
  • A road surface temperature prediction model (UM-Road) using input data of the Unified Model (UM) output and road physical properties is developed and verified with the use of the observed data at road weather information system. The UM outputs of air temperature, relative humidity, wind speed, downward shortwave radiation, net longwave radiation, precipitation and the road properties such as slope angles, albedo, thermal conductivity, heat capacity at maximum 7 depth are used. The net radiation is computed by a surface radiation energy balance, the ground heat flux at surface is estimated by a surface energy balance based on the Monin-Obukhov similarity, the ground heat transfer process is applied to predict the road surface temperature. If the observed road surface temperature exists, the simulated road surface temperature is corrected by mean bias during the last 24 hours. The developed UM-Road is verified using the observed data at road side for the period from 21 to 31 March 2013. It is found that the UM-Road simulates the diurnal trend and peak values of road surface temperature very well and the 50% (90%) of temperature difference lies within ${\pm}1.5^{\circ}C$ (${\pm}2.5^{\circ}C$) except for precipitation case.

Development of the Korean Aviation Turbulence Guidance (KTG) System using the Operational Unified Model (UM) of the Korea Meteorological Administration (KMA) and Pilot Reports (PIREPs) (기상청 현업 통합모델과 조종사기상보고 자료를 이용한 한국형 항공난류 예측시스템 개발)

  • Kim, Jung-Hoon;Chun, Hye-Yeong
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.20 no.4
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    • pp.76-83
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    • 2012
  • Korean aviation Turbulenc Guidance (KTG) system is developed using the operational unified model (UM) of the Korea Meteorological Administration (KMA) and pilot reports (PIREPs) over East Asia. The KTG system comprised of twenty turbulence diagnostics that represent various turbulence potentials and have the best forecasting skills, which are combined into a single ensemble-averaged index, namely KTG, at upper-(above FL250) and mid-(below FL250) levels. It is found that the overall performance of the KTG is higher than those produced from the one single best index, and satisfies the minimum criteria (80% accuracy) that the system is operationally useful in aviation industry.

Development and Validation of the Coupled System of Unified Model (UM) and PArameterized FOG (PAFOG) (기상청 현업 모형(UM)과 1차원 난류모형(PAFOG)의 접합시스템 개발 및 검증)

  • Kim, Wonheung;Yum, Seong Soo
    • Atmosphere
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    • v.25 no.1
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    • pp.149-154
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    • 2015
  • As an attempt to improve fog predictability at Incheon International Airport (IIA) we couple the 3D weather forecasting model currently operational in Korea Meteorological Administration (regional Unified Model, UM_RE) with a 1D turbulence model (PAFOG). The coupling is done by extracting the meteorological data from the 3D model and properly inserting them in the PAFOG model as initial conditions and external forcing. The initial conditions include surface temperature, 2 m temperature and dew point temperature, geostrophic wind at 850 hPa and vertical profiles of temperature and dew point temperature. Moisture and temperature advections are included as external forcing and updated every hr. To validate the performance of the coupled system, simulation results of the coupled system are compared to those of the 3D model alone for the 22 sea fog cases observed over the Yellow Sea. Three statistical indices, i.e., Root Mean Square Error (RMSE), linear correlation coefficient (R) and Critical Success Index (CSI), are examined, and they all indicate that the coupled system performs better than the 3D model alone. These are certainly promising results but more improvement is required before the coupled system can actually be used as an operational fog forecasting model. For the RMSE, R, and CSI values for the coupled system are still not good enough for operational fog forecast.

Development and Evaluation of Urban Canopy Model Based on Unified Model Input Data Using Urban Building Information Data in Seoul (서울 건물정보 자료를 활용한 UM 기반의 도시캐노피 모델 입력자료 구축 및 평가)

  • Kim, Do-Hyoung;Hong, Seon-Ok;Byon, Jae-Yong;Park, HyangSuk;Ha, Jong-Chul
    • Atmosphere
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    • v.29 no.4
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    • pp.417-427
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    • 2019
  • The purpose of this study is to build urban canopy model (Met Office Reading Urban Surface Exchange Scheme, MORUSES) based to Unified Model (UM) by using urban building information data in Seoul, and then to compare the improving urban canopy model simulation result with that of Seoul Automatic Weather Station (AWS) observation site data. UM-MORUSES is based on building information database in London, we performed a sensitivity experiment of UM-MOURSES model using urban building information database in Seoul. Geographic Information System (GIS) analysis of 1.5 km resolution Seoul building data is applied instead of London building information data. Frontal-area index and planar-area index of Seoul are used to calculate building height. The height of the highest building in Seoul is 40m, showing high in Yeoido-gu, Gangnam-gu and Jamsil-gu areas. The street aspect ratio is high in Gangnam-gu, and the repetition rate of buildings is lower in Eunpyeong-gu and Gangbuk-gu. UM-MORUSES model is improved to consider the building geometry parameter in Seoul. It is noticed that the Root Mean Square Error (RMSE) of wind speed is decreases from 0.8 to 0.6 m s-1 by 25 number AWS in Seoul. The surface air temperature forecast tends to underestimate in pre-improvement model, while it is improved at night time by UM-MORUSES model. This study shows that the post-improvement UM-MORUSES model can provide detailed Seoul building information data and accurate surface air temperature and wind speed in urban region.

Performance Analysis of Simulation of Asian Dust Observed in 2010 by the all-Season Dust Forecasting Model, UM-ADAM2 (사계절 황사단기예측모델 UM-ADAM2의 2010년 황사 예측성능 분석)

  • Lee, Eun-Hee;Kim, Seungbum;Ha, Jong-Chul;Chun, Youngsin
    • Atmosphere
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    • v.22 no.2
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    • pp.245-257
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    • 2012
  • The Asian dust (Hwangsa) forecasting model, Asian Dust Aerosol Model (ADAM) has been modified by using satelliate monitoring of surface vegetation, which enables to simulate dusts occuring not only in springtime but also for all-year-round period. Coupled with the Unified Model (UM), the operational weather forecasting model at KMA, UM-ADAM2 was implemented for operational dust forecasting since 2010, with an aid of development of Meteorology-Chemistry Interface Processor (MCIP) for usage UM. The performance analysis of the ADAM2 forecast was conducted with $PM_{10}$ concentrations observed at monitoring sites in the source regions in China and the downstream regions of Korea from March to December in 2010. It was found that the UM-ADAM2 model was able to simulate quite well Hwangsa events observed in spring and wintertime over Korea. In the downstream region of Korea, the starting and ending times of dust events were well-simulated, although the surface $PM_{10}$ concentration was slightly underestimated for some dust events. The general negative bias less than $35{\mu}g\;m^{3}$ in $PM_{10}$ is found and it is likely to be due to other fine aerosol species which is not considered in ADAM2. It is found that the correlation between observed and forecasted $PM_{10}$ concentration increases as forecasting time approaches, showing stably high correlation about 0.7 within 36 hr in forecasting time. This suggests the possibility that there is potential for the UM-ADAM2 model to be used as an operational Asian dust forecast model.

Verification and Comparison of Forecast Skill between Global Seasonal Forecasting System Version 5 and Unified Model during 2014 (2014년 계절예측시스템과 중기예측모델의 예측성능 비교 및 검증)

  • Lee, Sang-Min;Kang, Hyun-Suk;Kim, Yeon-Hee;Byun, Young-Hwa;Cho, ChunHo
    • Atmosphere
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    • v.26 no.1
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    • pp.59-72
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    • 2016
  • The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

Development of the Seasonal Korean Aviation Turbulence Guidance (KTG) System Using the Regional Unified Model of the Korea Meteorological Administration (KMA) (기상청 통합지역모델을 이용한 계절 한국형 항공난류 예측시스템(계절-KTG) 개발)

  • Lee, Dan-Bi;Chun, Hye-Yeong
    • Atmosphere
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    • v.24 no.2
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    • pp.235-243
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    • 2014
  • Sources of aviation turbulence vary through the seasons, especially in the East Asia including Korean peninsula, associated primarily with the changes in the jet/front system and convective activities. For this reason, a seasonal Korean aviation Turbulence Guidance (KTG) system (seasonal-KTG) is developed in the present study by using pilot reports (PIREPs) and analysis data of the operational Unified Model (UM) of the Korea Meteorological Administration (KMA) for two years between June 2011 and May 2013. Twenty best diagnostics of aviation turbulence in each season are selected by the method of probability of detection (POD) using the PIREPs and UM data. After calculating a weighting value of each selected diagnostics using their area under curve (AUC), the 20 best diagnostics are combined with the weighting scores into a single ensemble-averaged index by season. Compared with the current operational-KTG system that is based on the diagnostics applying all seasons, the performances of the seasonal-KTG system are better in all seasons, except in fall.

The Impact of Satellite Observations on the UM-4DVar Analysis and Prediction System at KMA (위성자료가 기상청 전지구 통합 분석 예측 시스템에 미치는 효과)

  • Lee, Juwon;Lee, Seung-Woo;Han, Sang-Ok;Lee, Seung-Jae;Jang, Dong-Eon
    • Atmosphere
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    • v.21 no.1
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    • pp.85-93
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    • 2011
  • UK Met Office Unified Model (UM) is a grid model applicable for both global and regional model configurations. The Met Office has developed a 4D-Var data assimilation system, which was implemented in the global forecast system on 5 October 2004. In an effort to improve its Numerical Weather Prediction (NWP) system, Korea Meteorological Administration (KMA) has adopted the UM system since 2008. The aim of this study is to provide the basic information on the effects of satellite data assimilation on UM performance by conducting global satellite data denial experiments. Advanced Tiros Operational Vertical Sounder (ATOVS), Infrared Atmospheric Sounding Interferometer (IASI), Special Sensor Microwave Imager Sounder (SSMIS) data, Global Positioning System Radio Occultation (GPSRO) data, Air Craft (CRAFT) data, Atmospheric Infrared Sounder (AIRS) data were assimilated in the UM global system. The contributions of assimilation of each kind of satellite data to improvements in UM performance were evaluated using analysis data of basic variables; geopotential height at 500 hPa, wind speed and temperature at 850 hPa and mean sea level pressure. The statistical verification using Root Mean Square Error (RMSE) showed that most of the satellite data have positive impacts on UM global analysis and forecasts.

Development of the Korean Mid- and Upper-Level Aviation Turbulence Guidance (KTG) System Using the Regional Unified Model (통합지역모델을 이용한 한국형 중·상층 항공난류예측시스템 개발)

  • Kim, Jung-Hoon;Chun, Hye-Yeong
    • Atmosphere
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    • v.21 no.4
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    • pp.497-506
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    • 2011
  • Korean mid- and upper-level aviation turbulence guidance (KTG) system is developed using the unified model (UM)-based regional data assimilation and prediction system (RDAPS) of the Korea Meteorological Administration. The KTG system includes three steps. First, the KTG system calculates a suite of diagnostics in the UM-RDAPS domain. Second, component diagnostics that have different units and numerical magnitudes are normalized into the values between 0 and 1, according to their own thresholds in the KTG system. Finally, normalized diagnostics are combined into one KTG predictor by measuring the weighting scores based on the probability of detection, which is calculated using the observed pilot reports (PIREPs) exclusively of moderate-or-greater (MOG) and null (NIL) intensities. To investigate the optimal performance of the KTG system, two types (RD-KTG and UM-KTG) of the KTG systems are developed and evaluated using the PIREPs over Korea and East Asia. Component diagnostics and their thresholds in the RD-KTG are founded on the 8-yrs (2002.12-2010.11) MM5-based RDAPS (previous version of the RDAPS; ${\Delta}x$ = 30 km) and PIREPs data, while those in the UM-KTG are based on the 6 months (2010.12-2011.5) UM-based RDAPS (${\Delta}x$ = 12 km) and PIREPs data. In comparison between the RD-KTG and UM-KTG, overall performance of the UM-KTG (0.815) is better than that of the RD-KTG (0.79) during the recent 6 months, because forecasting skill for the upper-level wind is higher in the UM-RDAPS than in the MM5-RDAPS. It is also found that the UM-KTG is more efficient than the RD-KTG according to the statistical evaluations and sensitivity tests to the number of component diagnostics.

Analysis of low level cloud prediction in the KMA Local Data Assimilation and Prediction System(LDAPS) (기상청 국지예보모델의 저고도 구름 예측 분석)

  • Ahn, Yongjun;Jang, Jiwon;Kim, Ki-Young
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.25 no.4
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    • pp.124-129
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    • 2017
  • Clouds are an important factor in aircraft flight. In particular, a significant impact on small aircraft flying at low altitude. Therefore, we have verified and characterized the low level cloud prediction data of the Unified Model(UM) - based Local Data Assimilation and Prediction System(LDAPS) operated by KMA in order to develop cloud forecasting service and contents important for safety of low-altitude aircraft flight. As a result of the low level cloud test for seven airports in Korea, a high correlation coefficient of 0.4 ~ 0.7 was obtained for 0-36 leading time. Also, we found that the prediction performance does not decrease as the lead time increases. Based on the results of this study, it is expected that model-based forecasting data for low-altitude aviation meteorology services can be produced.