• 한국농림기상학회지
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• 제19권4호
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• pp.232-245
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• 2017

본 연구에서는 지표이용도 특성이 반영된 고해상도 기상예측모델 도시캐노피모형(WRF-UCM)의 수치모의 실험을 통해 도심과 전원 지역 기상변수 및 에너지수지 변화 경향에 대하여 분석하였다. UCM을 적용하지 않은 WRF 모의 결과를 규준실험으로 설정하였으며, 거칠기 길이 변화와 인공열 고려에 따라 총 4가지 실험을 비교하여 분석하였다. UCM을 적용한 실험에서 거칠기 길이의 수정 전과 후의 기온과 풍속의 변화가 크게 나타나지 않았으나, 인공열을 고려한 UCM의 모의 기온과 풍속은 고려하기 전보다 크게 차이가 나타났다. 모의 실험 간의 차이는 전원 지역보다 도시 지역에서 더 크게 나타났다. 자동기상관측(AWS) 기온 관측 자료에 대하여 UCM에 인공열을 고려한 결과의 평방근오차(RMSE)가 가장 적었다. 또한, 차세대도시농림융합기상사업단의 중랑 에너지수지관측소지점의 현열플럭스 관측자료에 대한 검증 수치는 인공열을 고려하여 UCM을 적용한 실험의 RMSE와 BIAS 값이 가장 낮았다. 인공열을 고려한 UCM 적용이 도심의 현열플럭스 모의 향상에 영향을 주었다. 또한, UCM을 적용한 후 도시 지역 잠열플럭스의 변화 모의를 분석할 수 있었으며, 도심과 전원 지역 모두 UCM 적용 후에 관측 값과 더 가까운 검증 수치를 나타냈다. 결과적으로 WRF 모델에 UCM의 적용이 지표플럭스 모의 향상에 기여하는 것으로 나타났다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.425-425
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• 2022

동아시아 지역은 몬순 영향으로 계절적인 수자원 변동성이 매우 크고 홍수 및 가뭄과 같은 수재해 피해가 빈번히 발생하고 추세이다. 본 연구에서는 동아시아의 수자원 관리에 활용하기 위해 수문 모형 중 하나인 WRF-Hydro (Weather Research and Forecast and Model Hydrological modeling extension package) 모형을 구축하였다. WRF-Hydro 모형은 미국 NCAR (National Center for Atmospheric Research)에서 개발된 커뮤니티형 고해상도 예측모델로 미국 등에서 활발히 사용되고 있으나, 동아시아 지역에 적용된 연구는 없다. 따라서 모형의 동아시아 적용 가능성에 대한 불확실성이 높다. 본 연구에서는 WRF-Hydro 모형을 0.25°의 공간해상도로 동아시아 대상으로 구축하였고, 기상 및 지면 특성과 유역자료를 활용한 머신러닝 방법으로 파라미터 보정을 시행하여 2006년부터 2015년까지 구동하였다. 머신러닝을 통해 지역특성이 고려된 WRF-Hydro 모형은 표면유출, 보수깊이, 표면 거칠기, 표면 기울기와 같은 매개변수를 보정하였다. 모형 평가를 위해 GRDC (Global Runoff Database Center (GRDC), GLDAS (Global Land Data Assimilation System), ESA-CCI (European Space Agency Climate Change Initiative), MODIS (Moderate Resolution Imaging Spectroradiometer)에서 제공하는 관측 유출량, 토양수분, 증발산량을 비교, 분석하여 동아시아 적용 적절성에 대해 검토하였다.

• 대기
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• 제21권4호
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• pp.391-404
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• 2011

This study investigates the impact of cumulus parameterization scheme (CPS) with different horizontal grid sizes on the simulation of the local heavy rainfall case over the Korean Peninsula. The Weather Research and Forecasting (WRF)-based real-time forecast system of the Joint Center for High-impact Weather and Climate Research (JHWC) is used. Three CPSs are used for sensitivity experiments: the BMJ (Betts-Miller-Janjic), GD (Grell-Devenyi ensemble), and KF (Kain-Fritsch) CPSs. The heavy rainfall case selected in this study is characterized by low-level jet and low-level transport of warm and moist air. In 27-km simulations (DM1), simulated precipitation is overestimated in the experiment with BMJ scheme, and it is underestimated with GD scheme. The experiment with KF scheme shows well-developed precipitation cells in the southern and the central region of the Korean Peninsula, which are similar to the observations. All schemes show wet bias and cold bias in the lower troposphere. The simulated rainfall in 27-km horizontal resolution has influence on rainfall forecast in 9-km horizontal resolution, so the statements on 27-km horizontal resolution can be applied to 9-km horizontal resolution. In the sensitivity experiments of CPS for DM3 (3-km resolution), the experiment with BMJ scheme shows better heavy rainfall forecast than the other experiments. The experiments with CPS in 3-km horizontal resolution improve rainfall forecasts compared to the experiments without CPS, especially in rainfall distribution. The experiments with CPS show lower LCL(Lifted Condensation Level) than those without CPS at the maximum rainfall point, and weaker vertical velocity is simulated in the experiments with CPS compared to the experiments without CPS. It means that CPS suppresses convective instability and influences mainly convective rainfall. Consequently, heavy rainfall simulation with BMJ CPS is better than the other CPSs, and even in 3-km horizontal resolution, CPS should be applied to control convective instability. This conclusion can be generalized by conducting more experiments for a variety of cases over the Korean Peninsula.

• 대기
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• 제31권5호
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• pp.637-656
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• 2021

The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

• 대기
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• 제31권1호
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• pp.17-28
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• 2021

We investigated the impact of domain size on the simulated summer precipitation over the Korean Peninsula using the Weather Research and Forecasting (WRF) model. Two different domains are integrated up to 72-hours from 29 June 2017 to 28 July 2017 when the Changma front is active. The domain sizes are adopted from previous RDAPS (Regional Data Assimilation and Prediction System) and current LDAPS (Local Data Assimilation and Prediction System) operated by the Korea Meteorological Administration, while other model configurations are fixed identically. We found that the larger domain size showed better prediction skills, especially in precipitation forecast performance. This performance improvement is particularly noticeable over the central region of the Korean Peninsula. Comparisons of physical aspects of each variable revealed that the inflow of moisture flux from the East China Sea was well reproduced in the experiment with a large model domain due to a more realistic North Pacific high compared to the small domain experiment. These results suggest that the North Pacific anticyclone could be an important factor for the precipitation forecast during the summer-time over the Korean Peninsula.

• 한국지구과학회지
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• 제36권5호
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• pp.460-475
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• 2015

A number of heavy rainfall events on the Korean Peninsula are indirectly influenced by tropical cyclones (TCs) when they are located in southeastern China. In this study, a heavy rainfall case in the middle Korean region is selected to examine the influence of typhoon simulation performance on predictability of remote rainfall over Korea as well as direct rainfall over Taiwan. Four different numerical experiments are conducted using Weather Research and Forecasting (WRF) model, toggling on and off two different improvements on typhoon in the model initial condition (IC), which are TC bogussing initialization and dropwindsonde observation data assimilation (DA). The Geophysical Fluid Dynamics Laboratory TC initialization algorithm is implemented to generate the bogused vortex instead of the initial typhoon, while the airborne observation obtained from dropwindsonde is applied by WRF Three-dimensional variational data assimilation. Results show that use of both TC initialization and DA improves predictability of TC track as well as rainfall over Korea and Taiwan. Without any of IC improvement usage, the intensity of TC is underestimated during the simulation. Using TC initialization alone improves simulation of direct rainfall but not of indirect rainfall, while using DA alone has a negative impact on the TC track forecast. This study confirms that the well-suited TC simulation over southeastern China improves remote rainfall predictability over Korea as well as TC direct rainfall over Taiwan.

• 대기
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• 제25권4호
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• pp.639-657
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• 2015

There is an increasing need to improve the air quality over South Korea to protect public health from local and remote anthropogenic pollutant emissions that are in an increasing trend. Here, we evaluate the performance of the WRF-Chem (Weather Research and Forecasting-Chemistry) model in simulating near-surface air quality of major Korean cities, and investigate the impacts of time-varying chemical initial and lateral boundary conditions (IC/BCs) on the air quality simulation using a chemical downscaling technique. The model domain was configured over the East Asian region and anthropogenic MICS-Asia 2010 emissions and biogenic MEGAN-2 emissions were applied with RACM gaseous chemistry and MADE/SORGAM aerosol mechanism. Two simulations were conducted for a 30-days period on April 2010 with chemical IC/BCs from the WRF-Chem default chemical species profiles ('WRF experiment') and the MOZART-4 (Model for OZone And Related chemical Tracers version 4) ('WRF_MOZART experiment'), respectively. The WRF_MOZART experiment has showed a better performance to predict near-surface CO, $NO_2$, $SO_2$, and $O_3$ mixing ratios at 7 major Korean cities than the WRF experiment, showing lower mean bias error (MBE) and higher index of agreement (IOA). The quantitative impacts of the chemical IC/BCs have depended on atmospheric residence time of the pollutants as well as the relative difference of chemical mixing ratios between the WRF and WRF_MOZART experiments at the lateral boundaries. Specifically, the WRF_MOZART experiment has reduced MBE in CO and O3 mixing ratios by 60~80 ppb and 5~10 ppb over South Korea than those in the WRF-Chem default simulation, while it has a marginal impact on $NO_2$ and $SO_2$ mixing ratios. Without using MOZART-4 chemical IC, the WRF simulation has required approximately 6-days chemical spin-up time for the East Asian model domain. Overall, the results indicate that realistic chemical IC/BCs are prerequisite in the WRF-Chem simulation to improve a forecast skill of local air quality over South Korea, even in case the model domain is sufficiently large to represent anthropogenic emissions from China, Japan, and South Korea.

• 한국환경과학회지
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• 제33권6호
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• pp.435-442
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• 2024

We investigated the accuracy of surface air temperature prediction according to the selection of land-use data and initial meteorological data using the Weather Research and Forecasting model-v4.2.1. A numerical experiment was conducted at the Daegu Dyeing Industrial Complex. We initially used meteorological input data from GFS (Global forecast system)and GDAPS (Global data assimilation and prediction system). High-resolution input data were generated and used as input data for the weather model using the land cover data of the Ministry of Environment and the digital elevation model of the Ministry of Land, Infrastructure, and Transport. The experiment was conducted by classifying the terrestrial and topographic data (land cover data) and meteorological data applied to the model. For simulations using high-resolution terrestrial data(10 m), global data assimilation, and prediction system data(CASE 3), the calculated surface temperature was much closer to the automatic weather station observations than for simulations using low-resolution terrestrial data(900 m) and GFS(CASE 1).

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.84-87
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• 2012

수자원 분야에서 지표와 대기 사이의 물과 에너지 교환에 대한 해석을 위하여 다양한 수문 모형이 이용되고 있다. 이 과정은 물 순환 과정을 이해하기 위한 한 방법으로 본 연구에서는 Common Land Model (CLM)을 이용해 수문 기상학적 인자를 모의하였다. CLM은 Soil-Vegetation-Atmosphere Transfer (SVAT) 모형 중 하나이며, 본 모형을 이용한 연구들이 활발히 이루어지고 있다. 그러나 한반도를 포함한 영역에서의 참고할만한 결과가 부족한 실정이며, 국내에서의 사용 가능한 기초자료도 부족하여 모형 구동을 위해 본 연구에서는 1 km의 높은 해상도의 강제입력자료를 Weather Research Forecast (WRF) 모형을 통하여 생산하여 사용하였다. 이 자료는 관측자료 및 위성 자료 등을 이용한 자료동화방법을 통하여 산출하였으며, 이를 이용하여 낙동강 유역에 대하여 CLM의 수문 기상학적 인자들을 산정하였다. 향후 보다 넓은 범위의 연구 지역을 설정하여 국내 관측 자료와의 비교를 통해 본 자료에 대한 사용 가능성을 검증할 계획이다. 또한 이를 바탕으로 수문 모형을 이용한 아시아 지역의 높은 해상도의 수문 기상학적 인자에 대한 연구를 진행할 예정이다.

• 대기
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• 제29권5호
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• pp.567-583
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• 2019

In this study, the high-resolution numerical simulations considering detailed anthropogenic heat, albedo, emission and roughness length are analyzed by using single layer Urban Canopy Model (UCM) in Weather Research Forecast (WRF). For this, improved urban parameter data for Seoul Metropolitan Area (SMA) was collected from global data. And then the parameters were applied to WRF-UCM model after it was processed into 2-dimensional topographical data. The 6 experiments were simulated by using the model with each parameter and verified against observation from Automated Weather Station (AWS) and flux tower for the temperature and sensible heat flux. The data for sensible heat flux of flux towers on Jungnang and Bucheon, the temperature of AWS on Jungnang, Gangnam, Bucheon and Neonggok were used as verification data. In the case of summer, the improvement of simulation by using detailed anthropogenic heat was higher than the other experiments in sensible flux simulation. The results of winter case show improved in all simulations using each advanced parameters in temperature and sensible heat flux simulation. Improvement of urban parameters in this study are possible to reflect the heat characteristics of urban area. Especially, detailed application of anthropogenic heat contributed to the enhancement of predicted value for sensible heat flux and temperature.