• Journal of Environmental Science International
• /
• v.29 no.1
• /
• pp.33-44
• /
• 2020

Recently, a variety of modeling studies have been conducted to examine the air quality over South Korea during the Korea - United States Air Quality (KORUS-AQ) campaign period (May 1 to June 10, 2016). This study investigates the impact of different meteorological initializations on atmospheric modeling results. We conduct several simulations during the KORUS-AQ period using the Weather Research and Forecasting (WRF) model with two different initial datasets, which is FNL of NCEP and ERA5 of ECMWF. Comparing the raw initial data, ERA5 showed better accuracy in the temperature, wind speed, and mixing ratio fields than those of NCEP-FNL. On the other hand, the results of WRF simulations with ERA5 showed better accuracy in the simulated temperature and mixing ratio than those with FNL, except for wind speed. Comparing the nudging efficiency of temperature and wind speed fields, the grid nudging effect on the FNL simulation was larger than that on the ERA5 simulation, but the results of mixing ratio field was the opposite. Overall, WRF simulation with ERA5 data showed a better performance for temperature and mixing ratio simulations than that with FNL data. For wind speed simulation, however, WRF simulation with FNL data indicated more accurate results compared to that with ERA5 data.

• Journal of Environmental Science International
• /
• v.21 no.4
• /
• pp.517-533
• /
• 2012

This study calculated wind speed at the height of 10 m using a disaster prediction model(Florida Public Hurricane Loss Model, FPHLM) that was developed and used in the United States. Using its distributions, a usable information of surface wind was produced for the purpose of disaster prevention when the typhoon attack. The advanced research version of the WRF (Weather Research and Forecasting) was used in this study, and two domains focusing on South Korea were determined through two-way nesting. A horizontal time series and vertical profile analysis were carried out to examine whether the model provided a resonable simulation, and the meteorological factors, including potential temperature, generally showed the similar distribution with observational data. We determined through comparison of observations that data taken at 700 hPa and used as input data to calculate wind speed at the height of 10 m for the actual terrain was suitable for the simulation. Using these results, the wind speed at the height of 10 m for the actual terrain was calculated and its distributions were shown. Thus, a stronger wind occurred in coastal areas compared to inland areas showing that coastal areas are more vulnerable to strong winds.

• Journal of Korean Society for Atmospheric Environment
• /
• v.23 no.6
• /
• pp.640-652
• /
• 2007

The MM5, RAMS and WRF, meteorological models have provided the dynamical parameters as inputs to air quality model. A major content of this study is that significant characteristics of three models for high-ozone occurrence analyze for surface wind and air temperature fields and compare with observation data in Seoul metropolitan area. An analysis of air temperature field revealed that location of core in high temperature of MM5 and WRF differed from that of RAMS. MM5 and WRF indicated high temperature in Seoul but RAMS represented it on the outskirts of Seoul. MM5 and WRF were underestimated maximum temperature during daytime but RAMS simulated similar value with observation data. Surface wind field with three models, it was shown many differences at horizontal distribution of wind direction. RAMS indicated weak wind speed in land and strong sea breeze at coastal areas than MM5 and WRF. However wind speed simulated by three model were overestimated during both daytime and nighttime.

• Journal of Korean Society for Atmospheric Environment
• /
• v.26 no.6
• /
• pp.666-682
• /
• 2010

The forecasting system for Today's and Tomorrow's PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today's 24 hour average PM10 concentration and at 5 PM to predict Tomorrow's 24 hour average PM10. The Today's forecasting model was operated based on measured air quality and meteorological data while Tomorrow's model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model's predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow's model were 72.4%, 0.0%, and 42.9% while those in Today's model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

• Journal of the Korean earth science society
• /
• v.36 no.2
• /
• pp.158-170
• /
• 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.

• Journal of Environmental Science International
• /
• v.25 no.7
• /
• pp.1017-1028
• /
• 2016

Wind information is one of the major inputs for the prediction of urban air flow using computational fluid dynamic (CFD) models. Therefore, the numerical characteristics of the wind data formed at their mother domains should be clarified to predict the urban air flow more precisely. In this study, the formation characteristics of the wind data in the Seoul region were used as the inlet wind information for a CFD based simulation and were analyzed using numerical weather prediction models for weather research and forecasting (WRF). Because air flow over the central part of the Korean peninsula is often controlled not only by synoptic scale westerly winds but also by the westerly sea breeze induced from the Yellow Sea, the westerly wind often dominates the entire Seoul region. Although simulations of wind speed and air temperature gave results that were slightly high and low, respectively, their temporal variation patterns agreed well with the observations. In the analysis of the vertical cross section, the variation of wind speed along the western boundary of Seoul is simpler in a large domain with the highest horizontal resolution as compared to a small domain with the same resolution. A strong convergence of the sea breeze due to precise topography leads to the simplification of the wind pattern. The same tendency was shown in the average vertical profiles of the wind speed. The difference in the simulated wind pattern of two different domains is greater during the night than in the daytime because of atmospheric stability and topographically induced mesoscale forcing.

• The Korean Journal of Applied Statistics
• /
• v.29 no.7
• /
• pp.1373-1383
• /
• 2016

The wind energy industry and wind power generation have increased; consequently, the stable supply of the wind power has become an important issue. It is important to accurately predict the wind power with short-term basis in order to make a reliable planning for the power supply and demand of wind power. In this paper, we first analyzed the speed, power and the directions of the wind. The neural network and the time series models (ARMA, ARMAX, ARMA-GARCH, Holt Winters) for wind power generation forecasting were compared based on mean absolute error (MAE). For one to three hour-ahead forecast, ARMA-GARCH model was outperformed, and the neural network method showed a better performance in the six hour-ahead forecast.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.4_2
• /
• pp.715-724
• /
• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• Atmosphere
• /
• v.26 no.4
• /
• pp.617-633
• /
• 2016

Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

• Journal of the Korean Geographical Society
• /
• v.39 no.1
• /
• pp.13-26
• /
• 2004

This paper examined the possibility of NET application for a relative weather stress index in Korea. The characteristic of NET distribution used temperature, relative humidity, wind speed which forecasting at Korean Meteorological Administration were analyzed. Regional critical values of daily maximum NET of stress index for summer resembled the distribution of daily maximum temperature because were not impacted wind and humidity but temperature. Regional critical values of daily minimum NET of stress index for winter distributed variously compared with summer. The highland region and the northern region of Seoul were impacted of low temperature and coastal region which strong wind. The occurrences of stressful days did not vary in summer, but obviously increased in winter after mid-1990s.