• Title/Summary/Keyword: numerical weather forecast model

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Impact of a Convectively Forced Gravity Wave Drag Parameterization in Global Data Assimilation and Prediction System (GDAPS) (대류가 유도하는 중력파 항력의 모수화가 GDAPS에 미치는 영향)

  • Kim, So-Young;Chun, Hye-Yeong;Park, Byoung-Kwon;Lee, Hae-Jin
    • Atmosphere
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    • v.16 no.4
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    • pp.303-318
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    • 2006
  • A parameterization of gravity wave drag induced by cumulus convection (GWDC) proposed by Chun and Baik is implemented in the KMA operational global NWP model (GDAPS), and effects of the GWDC on the forecast for July 2005 by GDAPS are investigated. The forecast result is compared with NCEP final analyses data (FNL) and model's own analysis data. Cloud-top gravity wave stresses are concentrated in the tropical region, and the resultant forcing by the GWDC is strong in the tropical upper troposphere and lower stratosphere. Nevertheless, the effect of the GWDC is strong in the mid- to high latitudes of Southern Hemisphere and high latitudes of Northern Hemisphere. By examining the effect of the GWDC on the amplitude of the geopotential height perturbation with zonal wavenumbers 1-3, it is found that impact of the GWDC is extended to the high latitudes through the change of planetary wave activity, which is maximum in the winter hemisphere. The GWDC reduces the amplitude of zonal wavenumber 1 but increases wavenumber 2 in the winter hemisphere. This change alleviates model biases in the zonal wind not only in the lower stratosphere where the GWDC is imposed, but also in the whole troposphere, especially in the mid- to high latitudes of Southern Hemisphere. By examining root mean square error, it is found that the GWDC parameterization improves GDAPS forecast skill in the Southern Hemisphere before 7 days and partially in the Northern Hemisphere after about 5 days.

Evaluation of Surface Wind Forecast over the Gangwon Province using the Mesoscale WRF Model (중규모 수치모델 WRF를 이용한 강원 지방 하층 풍속 예측 평가)

  • Seo, Beom-Keun;Byon, Jae-Young;Lim, Yoon-Jin;Choi, Byoung-Choel
    • Journal of the Korean earth science society
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    • v.36 no.2
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    • pp.158-170
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    • 2015
  • This study evaluates the wind speed forecast near the surface layer using the Weather Research Forecasting with Large Eddy Simulation (WRF-LES) model in order to compare the planetary boundary layer (PBL) parameterization with the LES model in terms of different spatial resolution. A numerical simulation is conducted with 1-km and 333-m horizontal resolution over the Gangwon Province including complex mountains and coastal region. The numerical experiments with 1-km and 333-m horizontal resolution employ PBL parameterization and LES, respectively. The wind speed forecast in mountainous region shows a better forecast performance in 333-m experiment than in 1-km, while wind speed in coastal region is similar to the observation in 1-km spatial resolution experiment. Therefore, LES experiment, which directly simulates the turbulence process near the surface layer, contributes to more accurate forecast of surface wind speed in mountainous regions.

PV Power Prediction Models for City Energy Management System based on Weather Forecast Information (기상정보를 활용한 도시규모-EMS용 태양광 발전량 예측모델)

  • Eum, Ji-Young;Choi, Hyeong-Jin;Cho, Soo-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.3
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    • pp.393-398
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    • 2015
  • City or Community-scale Energy Management System(CEMS) is used to reduce the total energy consumed in the city by arranging the energy resources efficiently at the planning stage and controlling them economically at the operating stage. Of the operational functions of the CEMS, generation forecasting of renewable energy resources is an essential feature for the effective supply scheduling. This is because it can develop daily operating schedules of controllable generators in the city (e.g. diesel turbine, micro-gas turbine, ESS, CHP and so on) in order to minimize the inflow of the external power supply system, considering the amount of power generated by the uncontrollable renewable energy resources. This paper is written to introduce numerical models for photo-voltaic power generation prediction based on the weather forecasting information. Unlike the conventional methods using the average radiation or average utilization rate, the proposed models are developed for CEMS applications using the realtime weather forecast information provided by the National Weather Service.

Development of statistical forecast model for PM10 concentration over Seoul (서울지역 PM10 농도 예측모형 개발)

  • Sohn, Keon Tae;Kim, Dahong
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.289-299
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    • 2015
  • The objective of the present study is to develop statistical quantitative forecast model for PM10 concentration over Seoul. We used three types of data (weather observation data in Korea, the China's weather observation data collected by GTS, and air quality numerical model forecasts). To apply the daily forecast system, hourly data are converted to daily data and then lagging was performed. The potential predictors were selected based on correlation analysis and multicollinearity check. Model validation has been performed for checking model stability. We applied two models (multiple regression model and threshold regression model) separately. The two models were compared based on the scatter plot of forecasts and observations, time series plots, RMSE, skill scores. As a result, a threshold regression model performs better than multiple regression model in high PM10 concentration cases.

Performance comparison of rainfall and flood forecasts using short-term numerical weather prediction data from Korea and Japan (한-일 단기 수치예보자료를 이용한 강우 및 홍수 예측 성능 비교)

  • Yu, Wansik;Yoon, Seongsim;Choi, Mikyoung;Jung, Kwansue
    • Journal of Korea Water Resources Association
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    • v.50 no.8
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    • pp.537-549
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    • 2017
  • This study evaluated the accuracy of rainfall and flood forecasts in Sancheong basin with three rainfall events such as typhoon and stationary front by using LDAPS provided by Korea Meteorological Agency and MSM provided by Japan Meteorological Agency. In the rainfall forecast result, both LDAPS and MSM showed high forecast accuracy for wide-area prediction such as typhoon event, but local-area prediction such as stationary front has a limit to quantitative precipitation forecast (QPF). In the flood forecast result, the forecast accuracy was improved with the increase of the lead time, and it showed the possibility of LDAPS and MSM in the field of rainfall and flood forecast by linking meteorology and water resources.

Recent Trends of Meteorological Research in North Korea (2007-2016) - Focusing on Journal of Weather and Hydrology - (최근 10년(2007~2016년) 북한의 기상기후 연구 동향 - 기상과 수문지를 중심으로 -)

  • Lee, Seung-Wook;Lee, Dae-Geun;Lim, Byunghwan
    • Atmosphere
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    • v.27 no.4
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    • pp.411-422
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    • 2017
  • The aim of this research is to review recent trends in weather and climate research in North Korea. We selected North Korean journal 'Weather and Hydrology' for the last 10 years (2007-2016), and identified trends in research subject, researchers, and affiliations. Furthermore, we analyzed the major achievements and trends by research sector. Our main results are same as follows. The largest number of researches on 'modernization and informatization on prediction' have been carried out in North Korea's recent meteorological and climatological research. This could be implicated that the scope of national science policy directly affected the promotion of specific research field. Especially, North Korea was evaluated to be concentrating its efforts on numerical model research and development. The numerical model which enables very short-term (6 hours) rainfall forecast which using ensemble Kalman filter data assimilation method (4D EnKF) was developed. In addition, development of automatic weather system and improvement of the data transfer system were promoted. However, the result reveals that the automated real-time data transfer system was not fully equipped yet. These results could be used as a basic data for meteorological cooperation between South and North Korea.

The Effect of Radar Data Assimilation in Numerical Models on Precipitation Forecasting (수치모델에서 레이더 자료동화가 강수 예측에 미치는 영향)

  • Ji-Won Lee;Ki-Hong Min
    • Atmosphere
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    • v.33 no.5
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    • pp.457-475
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    • 2023
  • Accurately predicting localized heavy rainfall is challenging without high-resolution mesoscale cloud information in the numerical model's initial field, as precipitation intensity and amount vary significantly across regions. In the Korean Peninsula, the radar observation network covers the entire country, providing high-resolution data on hydrometeors which is suitable for data assimilation (DA). During the pre-processing stage, radar reflectivity is classified into hydrometeors (e.g., rain, snow, graupel) using the background temperature field. The mixing ratio of each hydrometeor is converted and inputted into a numerical model. Moreover, assimilating saturated water vapor mixing ratio and decomposing radar radial velocity into a three-dimensional wind vector improves the atmospheric dynamic field. This study presents radar DA experiments using a numerical prediction model to enhance the wind, water vapor, and hydrometeor mixing ratio information. The impact of radar DA on precipitation prediction is analyzed separately for each radar component. Assimilating radial velocity improves the dynamic field, while assimilating hydrometeor mixing ratio reduces the spin-up period in cloud microphysical processes, simulating initial precipitation growth. Assimilating water vapor mixing ratio further captures a moist atmospheric environment, maintaining continuous growth of hydrometeors, resulting in concentrated heavy rainfall. Overall, the radar DA experiment showed a 32.78% improvement in precipitation forecast accuracy compared to experiments without DA across four cases. Further research in related fields is necessary to improve predictions of mesoscale heavy rainfall in South Korea, mitigating its impact on human life and property.

Evaluation of the Intensity Predictability of the Numerical Models for Typhoons in 2013 (2013년 태풍에 대한 수치모델들의 강도 예측성 평가)

  • Kim, Ji-Seon;Lee, Woojeong;Kang, KiRyong;Byun, Kun-Young;Kim, Jiyoung;Yun, Won-Tae
    • Atmosphere
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    • v.24 no.3
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    • pp.419-432
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    • 2014
  • An assessment of typhoon intensity predictability of numerical models was conducted to develop the typhoon intensity forecast guidance comparing with the RSMC-Tokyo best track data. Root mean square error, box plot analysis and time series of wind speed comparison were performed to evaluate the each model error level. One of noticeable fact is that all models have a trend of error increase as typhoon becomes stronger and the Global Forecast System showed the best performance among the models. In the detailed analysis in two typhoon cases [Danas (1324) and Haiyan (1330)], GFS showed good performance in maximum wind speed and intensity trend in the best track, however it could not simulate well the rapid intensity increasing period. On the other hand, ECMWF and Hurricane-WRF overestimated the typhoon intensity but simulated track trend well.

Observing System Experiments Using the Intensive Observation Data during KEOP-2005 (KEOP-2005 집중관측자료를 이용한 관측시스템 실험 연구)

  • Won, Hye Young;Park, Chang-Geun;Kim, Yeon-Hee;Lee, Hee-Sang;Cho, Chun-Ho
    • Atmosphere
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    • v.18 no.4
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    • pp.299-316
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    • 2008
  • The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.

Forecast Sensitivity to Observations for High-Impact Weather Events in the Korean Peninsula (한반도에 발생한 위험 기상 사례에 대한 관측 민감도 분석)

  • Kim, SeHyun;Kim, Hyun Mee;Kim, Eun-Jung;Shin, Hyun-Cheol
    • Atmosphere
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    • v.23 no.2
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    • pp.171-186
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    • 2013
  • Recently, the number of observations used in a data assimilation system is increasing due to the enormous amount of observations, including satellite data. However, it is not clear that all of these observations are always beneficial to the performance of the numerical weather prediction (NWP). Therefore, it is important to evaluate the effect of observations on these forecasts so that the observations can be used more usefully in NWP process. In this study, the adjoint-based Forecast Sensitivity to Observation (FSO) method with the KMA Unified Model (UM) is applied to two high-impact weather events which occurred in summer and winter in Korea in an effort to investigate the effects of observations on the forecasts of these events. The total dry energy norm is used as a response function to calculate the adjoint sensitivity. For the summer case, TEMP observations have the greatest total impact while BOGUS shows the greatest impact per observation for all of the 24-, 36-, and 48-hour forecasts. For the winter case, aircraft, ATOVS, and ESA have the greatest total impact for the 24-, 36-, and 48-hour forecasts respectively, while ESA has the greatest impact per observation. Most of the observation effects are horizontally located upwind or in the vicinity of the Korean peninsula. The fraction of beneficial observations is less than 50%, which is less than the results in previous studies. As an additional experiment, the total moist energy norm is used as a response function to measure the sensitivity of 24-hour forecast error to observations. The characteristics of the observation impact with the moist energy response function are generally similar to those with the dry energy response function. However, the ATOVS observations were found to be sensitive to the response function, showing a positive (a negative) effect on the forecast when using the dry (moist) norm for the summer case. For the winter case, the dry and moist energy norm experiments show very similar results because the adjoint of KMA UM does not calculate the specific humidity of ice properly such that the dry and moist energy norms are very similar except for the humidity in air that is very low in winter.