• Atmosphere
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• v.18 no.4
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• pp.339-354
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• 2008

A numerical simulation of a heavy snowfall event that occurred 13 January 2008 along the Yeongdong coastal area, was performed using WRF (Weather Research and Forecasting) in order to reveal mesoscale structures and to construct a conceptual model showing the meteorological background that caused the large difference in snowfall amounts between the Yeongdong mountain area and the Yeongdong coastal area. The simulation results matched well with various observations such as corresponding 12h-accumulated observed precipitation, surface wind obscrvation, radar echoes, and satellite infrared images. The simulation and the observations showed that the scale of the event was of meso - $\beta$ and meso - $\gamma$ scale. The simulation represented well the mesoscale process causing the large difference in snowfall amounts in the two areas. First, wind flow was kept, to a certain extent, from crossing the mountains due to the blocking effect of the low Froude number (~1). The northeast flow over the adjaccnt sea tumcd northwest as it approachcd the mountains, where it was trapped, allowing so-called cold air damming. Second, a strong convergence area formed where the cold northwest flow along the Yeongdong coastal area and the relatively warm and moist northeast flow advecting toward the coast met, supporting the fonllation of a coastal front. Thus, the vertical motion was strongest over the front located near the coast, leading to the heavy snowfall there rather than in the remote mountain area.

• Atmosphere
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• v.19 no.4
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• pp.345-370
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• 2009

Numerical experiments using the Weather Research and Forecasting (WRF) model were done to identify the role of the mountain ranges in the northern part of the Peninsula (referred as "the northern mountain complex"), in the occurrence of two heavy snowfall events over the Yeongdong region on 7-8 December 2002 and 20-21 January 2008. To this end, control simulations with the topography of the northern mountain complex and other simulations without the topography of the mountain complex were performed. It was revealed that the amount of snowfall over the Yeongdong region from the control simulation much more exceeded that of the simulation without the topography of the mountain complex. This increase of the snowfall amount over the Yeongdong region can be explained as follows: As the upstream flow approached the northern mountain complex, it deflected around the northern mountain complex due to the blocking effect of the mountains with a low Froude number less than ~0.16. This lead to the strengthening of northeasterly over the East Sea and over the Yeongdong region. The strong northeasterly is accompanied with much more snowfall over the Yeongdong region by intensifying air-mass modification over the sea and the orographic effect of the Taeback mountains. Thus, it was concluded that the topography of the northern mountain complex is one of the main factors in determining the distribution and amount of precipitation in the Yeongdong region when there is an expansion of the Siberian High toward the East Sea.

• Journal of Environmental Science International
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• v.19 no.6
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• pp.689-701
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• 2010

The effects of high-resolution wind profiler (HWP) data on the wind distributions were evaluated in two different coastal areas during the study period (23-26 August, 2007), indicating weak-gradient flows. The analysis was performed using the Weather Research and Forecasting (WRF) model coupled with a three-dimensional variational (3DVAR) data assimilation system. For the comparison purpose, two coastal regions were selected as: a southwestern coastal (SWC) region characterized by a complex shoreline and a eastern coastal (EC) region surrounding a simple coastline and high mountains. The influence of data assimilation using the HWP data on the wind distributions in the SWC region was moderately higher than that of the EC region. In comparison between the wind speed and direction in the two coastal areas, the application of the HWP data contributed to improvement of the wind direction distribution in the SWC region and the wind strength in the EC region, respectively. This study suggests that the application of the HWP data exerts a large impact on the change in wind distributions over the sea and thus can contribute to the solution to lack of satellite and buoy data with their observational uncertainty.

• Journal of Environmental Science International
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• v.29 no.1
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• pp.1-13
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• 2020

Recently, a heavy rainfall with high spatial variation occurred frequently in the Korean Peninsula. The meteorological event that occurred in Busan on 3 May 2016 is characterized by heavy rain in a limited area. In order to clarify the reason of large spatial variation associated with mountain height and location of low level jet, several numerical experiments were carried out using the dynamic meteorological Weather Research and Forecasting (WRF) model. In this case study, the raised topography of Mount Geumjeong increased a barrier effect and air uplifting due to topographic forcing on the windward side. As a result, wind speed reduced and precipitation increased. In contrast, on the downwind side, the wind speed was slightly faster and since the total amount of water vapor is limited, the precipitation on the downwind side reduced. Numerical experiments on shifting the location of the lower jet demonstrated that if the lower jet is close to the mountain, its core becomes higher due to the effect of friction. Additionally, the water vapor convergence around the mountain increased and eventually the precipitation also increased in the area near the mountain. Hence, the location information of the lower jet is an important factor for accurately predicting precipitation.

• Atmosphere
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• v.31 no.2
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• pp.199-214
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• 2021

A record-breaking high surface air temperature of 41.0℃ was observed on 1 August 2018 at Hongcheon, South Korea. In this study, to quantitatively determine the formation mechanism of this extremely high surface air temperature, particularly considering the contributions of the foehn and the foehnlike wind, observational data from Korea Meteorological Administration (KMA) and the Weather Research and Forecasting (WRF) model were utilized. In the backward trajectory analysis, trajectories of 100 air parcels were released from the surface over Hongcheon at 1600 LST on 1 August 2018. Among them, the 47 trajectories (38 trajectories) are tracked back above (below) heights of 1.4 km above mean sea level at 0900 LST 31 July 2018 and are defined as upper (lower) routes. Lagrangian energy budget analysis shows that for the upper routes, adiabatic heating (11.886 × 10³ J kg^-1) accounts for about 77% of the increase in the thermal energy transfer to the air parcels, while the rest (23%) is diabatic heating (3.650 × 10³ J kg^-1). On the other hand, for the lower routes, adiabatic heating (6.111 × 10³ J kg^-1) accounts for about 49% of the increase, the rest (51%) being diabatic heating (6.295 × 10³ J kg^-1). Even though the contribution of the diabatic heating to the increase in the air temperature rather varies according to the routes, the contribution of the diabatic heating should be considered. The diabatic heating is caused by direct heating associated with surface sensible heat flux and heating associated with the turbulent mixing. This mechanism is the Type 4 foehn described in Takane and Kusaka (2011). It is concluded that Type 4 foehn wind occurs and plays an important role in the extreme event on 1 August 2018.

• Atmosphere
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• v.34 no.2
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• pp.153-176
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• 2024

At 0843 UTC 30 May 2021, a commercial aircraft encountered severe turbulence at z = 11.5 km associated with the rapid development of Mesoscale Convective System (MCS) in the Gyeonggi Bay of Korea. To investigate the generation mechanisms of Near-Cloud Turbulence (NCT) near the MCS, Weather Research and Forecasting model was used to reproduce key features at multiple-scales with four nested domains (the finest ∆x = 0.2 km) and 112 hybrid vertical layers. Simulated subgrid-scale turbulent kinetic energy (SGS TKE) was located in three different regions of the MCS. First, the simulated NCT with non-zero SGS TKE at z = 11.5 km at 0835 UTC was collocated with the reported NCT. Cloud-induced flow deformation and entrainment process on the downstream of the overshooting top triggered convective instability and subsequent SGS TKE. Second, at z = 16.5 km at 0820 UTC, the localized SGS TKE was found 4 km above the overshooting cloud top. It was attributed to breaking down of vertically propagating convectively-induced gravity wave at background critical level. Lastly, SGS TKE was simulated at z = 11.5 km at 0930 UTC during the dissipating stage of MCS. Upper-level anticyclonic outflow of MCS intensified the environmental westerlies, developing strong vertical wind shear on the northeastern quadrant of the dissipating MCS. Three different generation mechanisms suggest the avoidance guidance for the possible NCT events near the entire period of the MCS in the heavy air traffic area around Incheon International Airport in Korea.

• Atmosphere
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• v.26 no.4
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• pp.635-647
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• 2016

The effects of sea surface temperature (SST) gradient induced by the previous typhoon on the following typhoon motion over East Asia have been investigated using Weather Research and Forecasting (WRF) model for the previous Typhoon Bolaven (1215) and following Typhoon Tembin (1214). It was observed that Typhoon Bolaven remarkably reduced SST by about $7^{\circ}C$ at Yellow Sea buoy (YSbuoy). Using the WRF experiments for the imposed cold wake over West of Tembin (WT) and over East of Tembin (ET), this study demonstrates that the effects of eastward SST gradient including cold wake over WT is much significant rather than that over ET in relation to unexpected Tembin's eastward deflection. This difference between two experiments is attributed to the fact that cold wake over WT increases the magnitude of SST gradient under the eastward SST gradient around East Asia and the resultant asymmetric flow deflects Typhoon Tembin eastward, which is mainly due to the different atmospheric response to the SST forcing between ET and WT. Therefore, it implies that the enhanced eastward SST gradient over East Asia results in larger typhoon deflection toward the region of warmer SST according to the location of the cold wake effect. This result can contribute to the improvement of track prediction for typhoons influencing the Korean Peninsula

• Journal of the Korean earth science society
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• v.32 no.3
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• pp.276-293
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• 2011

In this study a modeling system consisting of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), the Community Multiscale Air Quality (CMAQ) model, and the CMAQ-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) model has been applied to estimate enhancements of $PM_{10}$ during Asian dust events in Korea. In particular, 5 experimental formulas were applied to the WRF-SMOKE-CMAQ (MADRID) model to estimate Asian dust emissions from source locations for major Asian dust events in China and Mongolia: the US Environmental Protection Agency (EPA) model, the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model, and the Dust Entrainment and Deposition (DEAD) model, as well as formulas by Park and In (2003), and Wang et al. (2000). According to the weather map, backward trajectory and satellite image analyses, Asian dust is generated by a strong downwind associated with the upper trough from a stagnation wave due to development of the upper jet stream, and transport of Asian dust to Korea shows up behind a surface front related to the cut-off low (known as comma type cloud) in satellite images. In the WRF-SMOKE-CMAQ modeling to estimate the PM10 concentration, Wang et al.'s experimental formula was depicted well in the temporal and spatial distribution of Asian dusts, and the GOCART model was low in mean bias errors and root mean square errors. Also, in the vertical profile analysis of Asian dusts using Wang et al's experimental formula, strong Asian dust with a concentration of more than $800\;{\mu}g/m^3$ for the period of March 31 to April 1, 2007 was transported under the boundary layer (about 1 km high), and weak Asian dust with a concentration of less than $400\;{\mu}g/m^3$ for the period of 16-17 March 2009 was transported above the boundary layer (about 1-3 km high). Furthermore, the difference between the CMAQ model and the CMAQ-MADRID model for the period of March 31 to April 1, 2007, in terms of PM10 concentration, was seen to be large in the East Asia area: the CMAQ-MADRID model showed the concentration to be about $25\;{\mu}g/m^3$ higher than the CMAQ model. In addition, the $PM_{10}$ concentration removed by the cloud liquid phase mechanism within the CMAQ-MADRID model was shown in the maximum $15\;{\mu}g/m^3$ in the Eastern Asia area.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.213-213
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• 2015

밭에서의 점적 관개를 이용한 노지 재배의 경우 적정 관개 계획 수립을 위해서는 작물 및 토양의 수분 정보에 대한 정확한 파악이 필요하다. 본 연구에서는 밭 토양을 GIS(Geographic Information System)를 통해 격자 형태로 분할하여 작물의 증발산량 및 토양의 수분함량을 모의할 수 있는 격자 기반 토양 물수지 모형을 개발하였다. 본 모형을 통해 작물의 소비수량 및 필요 수량을 파악함으로써 작부기간 중 필요한 관개수량을 제시하는 것이 가능하다. 고도화 기상자료로는 국가농림기상센터에서 운영 중인 고해상도 WRF(Weather Research and Forecasting) 모형에서 생산된 격자 형태의 복사, 온도, 바람, 강수 자료를 사용하였고 고도화 기상자료의 격자 해상도 별로 모의되는 작물 및 토양의 수분 정보 간 비교 및 분석을 실시하였다. 토양 물수지 모형에 입력되는 격자형태의 자료로는 기상, 토성 및 토지이용 자료가 있으며 기상자료의 경우 가로 및 세로의 크기가 각 270, 810, 2430m로 동일한 3가지 경우로 나누어 적용했으며 토성 및 토지이용 자료의 경우 기상 격자의 최소 크기에 맞춰 가로 및 세로의 크기가 각 270m인 격자로 분할하였다. 이와 같은 과정에 의한 모의 결과 각 격자별 작물 증발산량, 토양수분함량 및 관개수량의 일 연별 시계열 자료를 얻을 수 있으며 동시간대 격자별 수문인자 값을 산정하고 위치에 따른 공간적 상호 상관성을 분석하였다. 결과적으로, 고도화 기상자료의 격자 크기에 따른 밭 토양 물수지 분석 결과를 통해 고도화 기상 격자의 규모별 밭 토양 물수지 분석 효용성을 파악하고자 하였다. 더불어, 시험 지역(Test Bed) 선정을 통해 토양수분 및 증발산량을 실측하고 본 모형의 모의 결과와 비교함으로써 검정하는 것을 향후 연구 계획으로 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.63-63
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• 2020

최근 머신러닝 기술의 발전에 따라 비선형 시계열자료에 대한 예측이 가능해졌으며, 기존의 과정기반모형을 대체하여 지하수, 하천수 예측 등 다양한 수문분야에 활용되고 있다. 본 연구에서는 기존의 연구들과 달리 과정기반모형을 이용한 하천수 모의결과를 개선하기 위해 과정기반모형과 결합하는 방식으로 머신러닝 기술을 활용하였다. 머신러닝 기술을 통해 관측값과 모의값 간의 차이를 예측하고 과정기반모형의 모의결과에 반영함으로써 관측값을 정확히 재현할 수 있도록 하는 시스템을 구축하고 평가하였다. 과정기반모형으로는 Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro)을 소양강 유역을 대상으로 구축하였다. 머신러닝 모형으로는 순환 신경망 중 하나인 Long Short-Term Memory (LSTM) 신경망을 이용하여 장기시계열예측이 가능하게 하였다(WRF-Hydro-LSTM). 머신러닝 모형은 2013년부터 2017년까지의 기상자료 및 유입량 잔차를 이용하여 학습시키고, 2018년 기상자료를 이용하여 예상되는 유입량 잔차를 모의하였다. 모의된 잔차를 WRF-Hydro 모의결과에 반영시켜 최종 유입량 모의값을 보정하였다. 또한, 연구에서 제안된 새로운 방법론의 성능을 비교평가하기 위해 머신러닝 단독 모형으로 유입량을 학습 후 모의하였다(LSTM-only). 상관계수와 Nash-Sutcliffe 효율계수(NSE)를 사용해 평가한 결과, LSTM을 이용한 두 방법(WRF-Hydro-LSTM과 LSTM-only) 모두 기존의 과정기반모형(WRF-Hydro-only)에 비해 높은 정확도의 하천수 모의가 가능했으며, PBIAS 지수를 사용하여 평가한 결과, LSTM을 단독으로 사용하였을 때보다 WRF-Hydro와 결합했을 때 더 관측값과 가까운 모의가 가능함을 확인할 수 있었다.