• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.449-451
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• 2009

Sea level rise and increase of the typhoon/hurricane intensity due to global warming have threaten coastal areas for residential and industrial and have been widely studied. In this study we showed our recent efforts on sea wind which is one of critical factors for safe maritime traffic and prediction for storm surges and waves. Currently, most of numerical weather models in korea do not have sufficient spatial and temporal resolutions, therefore we set up a find grid(about 9km) sea wind prediction system that predicts every 12 hours for three day using Weather Research and Forecasting(WRF). This system covers adjacent seas around korean peninsula Comparisons of two observed data, Ieodo Ocean Research station(IORS) and Yellow Sea Buoy(YSB), showed reasonable agreements and by data assimilation we will improve better accurate sea winds in near future.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.669-680
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• 2013

Ozone sensitivity analysis with respect to $NO_x$ is conducted around the south-eastern area of the Korean Peninsula. WRF-CMAQ modeling system is used to simulate a local circulation and high ozone episode day. To analyze the sensitivity, the adjoint model for CMAQ is adopted in this study. The purpose of current study is to investigate the location that affects a day time ozone concentration of these receptors on the high ozone episode day. Adjoint sensitivity analysis for Daegu shows two areas of influence. One is the range from the neighboring location to Pohang and it affects mainly on the same day as receptor time. The other is the remote south-eastern area from Daegu. This remote influence area suggests that $NO_x$ emitted on the previous day can change the ozone concentration at receptor time. The influence area for Busan, on the other hand, is originated only from the emission on the previous day because the sea-breeze occurred on the episode day makes low influence of surrounding emission. The cross sectional analysis reveals that $NO_x$ advection is important not only near the surface of land but also around the height of boundary layer.

• Atmosphere
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• v.17 no.4
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• pp.327-337
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• 2007

In this study, we examined the new ensemble training approach to reduce the systematic error and improve prediction skill of wind by using the Short-range Ensemble prediction system (SENSE), which is the mesoscale multi-model ensemble prediction system. The SENSE has 16 ensemble members based on the MM5, WRF ARW, and WRF NMM. We evaluated the skill of surface wind prediction compared with AWS (Automatic Weather Station) observation during the summer season (June - August, 2006). At first stage, the correction of initial state for each member was performed with respect to the observed values, and the corrected members get the training stage to find out an adaptive weight function, which is formulated by Root Mean Square Vector Error (RMSVE). It was found that the optimal training period was 1-day through the experiments of sensitivity to the training interval. We obtained the weighted ensemble average which reveals smaller errors of the spatial and temporal pattern of wind speed than those of the simple ensemble average.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.5
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• pp.223-233
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• 2018

The predictability of winter storm waves using KMA's operational wind forecasts has been studied to predict wind waves and swells in the East coast of Korea using SWAN. The nested model were employed along the East coast of Korea to simulate the wave transformation in the coastal area and wave dissipation term of whitecapping is optimized to improve swell prediction accuracy. In this study, KMA's operational meteorological models (RDAPS and LDAPS) are used as input wind fields. In order to evaluate model accuracy, we also simulate wind waves and swells using ECMWF reanalysis and KIOST WRF wind and they are compared with the KMA's operational wave model and the wave measurement data on the offshore and onshore stations. As a result, it has the lowest RMSE and the highest correlation coefficient in the onshore when the input wind fields are KMA's operational meteorological forecasts. In the offshore, all of the simulate results shows good agreements with similar error statistics. It means that it is very feasible to use SWAN model with the modified whitecapping factor and KMA's operational meteorological forecasts for predicting the wind waves and swells in the East coast of Korea.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.283-302
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• 2022

Despite the nationwide COVID-19 lockdown in China since January 23, 2020, haze days with high PM₁₀ levels of 88-98 ㎍ m^-3 occurred on February 1 and 2, 2020. During these haze days, the East Asian region was affected by a warm and stagnant air mass with positive air temperature anomalies and negative zonal wind anomalies at 850 hPa. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to analyze the variation of regional PM₁₀ aerosol transport in Korea due to decreased anthropogenic emissions in East Asia. The base experiment (BASE), which applies the basic anthropogenic emissions in the WRF-Chem model, and the control experiment (CTL) applied by reducing the anthropogenic emission to 50%, were used to assess uncertainty with ground-based PM₁₀ measurements in Korea. The index of agreement (IOA) for the CTL simulation was 0.71, which was higher than that of BASE (0.67). A statistical analysis of the results suggests that anthropogenic emissions were reduced during the COVID-19 lockdown period in China. Furthermore, BASE and CTL applied to zero-out anthropogenic emissions outside Korea (BASE_ZEOK and CTL_ZEOK) were used to analyze the variations of regional PM₁₀ aerosol transport in Korea. Regional PM₁₀ transport in CTL was reduced by only 10-20% compared to BASE. Synthetic weather variables may be another reason for the non-linear response to changes in the contribution of regional transport to PM₁₀ in Korea with the reduction of anthropogenic emissions in East Asia. Although the regional transport contribution of other inorganic aerosols was high in CTL (80-90%), sulfate-nitrate-ammonium (SNA) aerosols showed lower contributions of 0-20%, 30-60%, and 30-60%, respectively. The SNA secondary aerosols, particularly nitrates, presumably declined as the Chinese lockdown induced traffic.

• Journal of Environmental Science International
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• v.24 no.1
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• pp.81-96
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• 2015

The characteristics of atmospheric dispersion of radioactive material (i.e. $^{137}Cs$) related to local wind patterns around the Kori nuclear power plant (KNPP) were studied using WRF/HYSPLIT model. The cluster analysis using observed winds from 28 weather stations during a year (2012) was performed in order to obtain representative local wind patterns. The cluster analysis identified eight local wind patterns (P1, P2, P3, P4-1, P4-2, P4-3, P4-4, P4-5) over the KNPP region. P1, P2 and P3 accounted for 14.5%, 27.0% and 14.5%, respectively. Both P1 and P2 are related to westerly/northwesterly synoptic flows in winter and P3 includes the Changma or typhoons days. The simulations of P1, P2 and P3 with high wind velocities and constant wind directions show that $^{137}Cs$ emitted from the KNPP during 0900~1400 LST (Local Standard Time) are dispersed to the east sea, southeast sea and southwestern inland, respectively. On the other hands, 5 sub-category of P4 have various local wind distributions under weak synoptic forcing and accounted for less than 10% of all. While the simulated $^{137}Cs$ for P4-2 is dispersed to southwest inland due to northeasterly flows, $^{137}Cs$ dispersed northward for the other patterns. The simulated average 137Cs concentrations of each local wind pattern are $564.1{\sim}1076.3Bqm^{-3}$. The highest average concentration appeared P4-4 due to dispersion in a narrow zone and weak wind environment. On the other hands, the lowest average concentration appeared P1 and P2 due to rapid dispersion to the sea. The simulated $^{137}Cs$ concentrations and dispersion locations of each local wind pattern are different according to the local wind conditions.

• Atmosphere
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• v.32 no.2
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• pp.103-118
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• 2022

This study evaluates the simulated meteorological fields with a particular focus on the low-level wind, which plays an important role in air pollutants dispersion, under the varying synoptic environment. Additionally, the effects of subgrid-scale orography parameterization and improved topography/land-use data on the simulated low-level wind is investigated. The WRF model version 4.1.3 is utilized to simulate two cases that were affected by different synoptic environments. One case from 2 to 6 April 2012 presents the substantial low-level wind speed over the Korean peninsula where the synoptic environment is characterized by the baroclinic instability. The other case from 14 to 18 April 2012 presents the relatively weak low-level wind speed and distinct diurnal cycle of low-level meteorological fields. The control simulations of both cases represent the systematic overestimation of the low-level wind speed. The positive bias for the case under the baroclinic instability is considerably alleviated by applying the subgrid-scale orography parameterization. However, the improvement of wind speed for the other case showing relatively weak low-level wind speed is not significant. Applying the high-resolution topography and land-use data also improves the simulated wind speed by reducing the positive bias. Our analysis shows that the increased roughness length in the high-resolution topography and land-use data is the key contributor that reduces the simulated wind speed. The simulated wind direction is also improved with the high-resolution data for both cases. Overall, our study indicates that wind forecasts can be improved through the application of the subgrid-scale orography parameterization and high-resolution topography/land-use data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.415-426
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• 2023

In this study, the horizontal and vertical structure of wind speed and wind direction were analyzed at the origin of migratory insect pests in China. Wind rose analysis was carried out using the Land-Atmosphere Modeling Package (LAMP) - WRF data, which has the spatiotemporal resolution of about 20 km and 1 hour intervals. Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was employed for backward trajectory analysis between South Korea and Southeastern China with Global Data Assimilation System (GDAS). The research interest date is July 16, when rice planthopper and leafhopper were observed at the same time. In order to examine where a jet stream occurs in the vertical in source regions and South Korea during the period (July 8 to July 17 in 2021), three-dimensional wind information was extracted and analyzed using the east-west, north-south, and vertical component wind data of the LAM P. The vertical distribution of wind showed that the wind changed in favor of the inflow of migratory insect pests during the period. As a result of analyzing the wind rose, about 30% or more of the wind at a point close to South Korea was classified into the low-level jet stream. In addition, majority of the wind directions for the low-level jet streams (rather than high-level jet streams) at the five origin sites were heading toward South Korea and even Japan, and this was supported by the HYSPLIT-based backward trajectory analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.323-323
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• 2018

최근 기후변화에 대한 관심이 증대됨에 따라 미래 기후모델자료를 기반으로 연구가 다양하게 진행되고 있다. 기후변화가 적용된 자료는 미래 수자원관리, 방재를 위한 수공구조물의 설계 등 다양한 방식으로 실무에 적용되고 있다. 하지만 기후모델로부터 모의된 결과는 어느 정도 관측자료와 차이가 발생하게 되며, 이러한 계통적 오차는 모델 내부에서 해결하기가 쉽지 않다. 그렇기 때문에 기후모델로부터 모의된 결과를 보정하기 위해 편의보정 기법을 활용한다. 그리고 미래 기후모델자료는 불확실성을 내재하고 있기 때문에 다양한 편의보정 기법을 적용하여 불확실성의 범위를 확인해 보았다. 사용된 편의보정 기법으로는 Quantile Mapping(QM), Quantile Delta Mapping(QDM), Detrended Quantile Mapping(DQM), Delta Change Method(DCM)을 이용하였다. 편의보정에 적용한 확률분포형은 일반극치분포(GEV분포), Type-1 극치분포(Gumbel분포)를 사용하였다. GEV분포를 기본으로 하여 조건적으로 GEV분포를 사용할 수 없는 경우, Gumbel분포를 사용하였다. 본 연구에서는 독일의 전지구기후모델(Global Climate Model, GCM)인 MPI-ESM-LR에 RCP 8.5 사나리오를 강제장으로 하여 지역기후모델(Regional Climate Model, RCM)인 WRF를 이용하여 동역학적으로 다운스케일한 강우자료를 사용하였다. 강우자료 중에서 강릉, 인천, 부산, 목포지점에 해당하는 자료를 추출하여 연 최대 강우강도 시계열을 산정하고 4가지 편의보정 기법을 이용하여 편의보정을 하였다. 편의보정 수행된 연 최대 강우강도 시계열을 scale-invariance 기법으로 다운스케일하여 미래 IDF곡선을 유도한 뒤, 편의보정별로 유도한 IDF곡선의 비교를 통해 편의보정기법이 미래 IDF곡선에 미치는 영향을 분석하였다.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.557-577
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• 2023

This study defines non-precipitation information as areas with weak precipitation or cloud particles that radar cannot detect due to weak returned signals, and suggests methods for its utilization in data assimilation. Previous studies have demonstrated that assimilating radar data from precipitation echoes can produce precipitation in model analysis and improve subsequent precipitation forecast. However, this study also recognizes the non-precipitation information as valuable observation and seeks to assimilate it to suppress spurious precipitation in the model analysis and forecast. To incorporate non-precipitation information into data assimilation, we propose observation operators that convert radar non-precipitation information into hydrometeor mixing ratios and relative humidity for the Weather Research and Forecasting Data Assimilation system (WRFDA). We also suggest a preprocessing method for radar non-precipitation information. A single-observation experiment indicates that assimilating non-precipitation information fosters an environment conducive to inhibiting convection by lowering temperature and humidity. Subsequently, we investigate the impact of assimilating non-precipitation information to a real case on July 23, 2013, by performing a subsequent 9-hour forecast. The experiment that assimilates radar non-precipitation information improves the model's precipitation forecasts by showing an increase in the Fractional Skill Score (FSS) and a decrease in the False Alarm Ratio (FAR) compared to experiments in which do not assimilate non-precipitation information.