• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2016년도 추계 학술발표논문집
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• pp.25-28
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• 2016

Recently, because of the weather forecasts through the low-resolution data has been limited, the demand of the high-resolution data is sharply increasing. Therefore, in this study, we restore the ultra-high resolution synthetic precipitation and temperature data for 2000-2014 due to small-scale topographic effect using the QPM (Quantitative Precipitation Model)/QTM (Quantitative Temperature Model). First, we reproduce the detailed precipitation and temperature data with 1km resolution using the distribution of Automatic Weather System (AWS) data and Automatic Synoptic Observation System (ASOS) data, which is about 10km resolution with irregular grid over South Korea. Also, we recover the precipitation and temperature data with 1km resolution using the MERRA reanalysis data over North Korea, because there are insufficient observation data. The precipitation and temperature from restored current climate reflect more detailed topographic effect than irregular AWS/ASOS data and MERRA reanalysis data over the Korean peninsula. Based on this analysis, more detailed prospect of regional climate is investigated.

• 한국기후변화학회지
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• 제6권4호
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• 대기
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• 제18권4호
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• pp.387-395
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• 2008

The impact of horizontal resolution on a regional climate model was investigated by simulating precipitation over the Korean Peninsula. As a regional climate model, the SNURCM(Seoul National University Regional Climate Model) has 21 sigma layers and includes the NCAR CLM(National Center for Atmospheric Research Community Land Model) for land-surface model, the Grell scheme for cumulus convection, the Simple Ice scheme for explicit moisture, and the MRF(Medium-Range Forecast) scheme for PBL(Planetary Boundary Layer) processing. The SNURCM was performed with 20 km resolution for Korea and 60 km resolution for East Asia during a 20-year period (1980-1999). Although the SNURCM systematically underestimated precipitation over the Korean Peninsula, the increase of model resolution simulated more precipitation in the southern region of the Korean Peninsula, and a more accurate distribution of precipitation by reflecting the effect of topography. The increase of precipitation was produced by more detailed terrain data which has a 10 minute terrain in the 20 km resolution model compared to the 30 minute terrain in the 60 km resolution model. The increase in model resolution and more detailed terrain data played an important role in generating more precipitation over the Korean Peninsula. While the high resolution model with the same terrain data resulted in increasing of precipitation over the Korean Peninsula including the adjoining sea, the difference of the terrain data resolution only influenced the precipitation distribution of the mountainous area by increasing the amount of non-convective rain. In conclusion, the regional climate model (SNURCM) with higher resolution simulated more precipitation over the Korean Peninsula by reducing the systematic underestimation of precipitation over the Korean Peninsula.

• 한국토양비료학회지
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• 제48권6호
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• pp.571-581
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• 2015

Soil moisture content is generally accepted as an important factor to understand the process of crop growth and is the basis of earth system models for analysis and prediction of the crop condition. To continuously monitor soil moisture changes at kilometer scale, it is demanded to create high resolution data from the current, several tens of kilometers. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) from 10 km to 30 m resolution using a soil texture and field measurements that have a high correlation with the SMC. As a result, the soil moisture variations of both data (before and after downscaling) were identical, and the Root Mean Square Error (RMSE) of SMC exhibited the low values. Also, time series analyses showed that three kinds of SMC data (field measurement, original AMSR2, and downscaled AMSR2) had very similar temporal variations. Our method can be applied to downscaling of other soil variables and can contribute to monitoring small-scale changes of soil moisture by providing high resolution data.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.379-379
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• 2020

The influence of drought has increased due to global warming. In addition, forest fires have occurred more frequently due to droughts and resulted in property losses and casualty. In this study, the effects of drought on Goseong-Sokcho Forest Fire in 2019 were analyzed using high-resolution synthetic precipitation data. In order to determine the severity of drought, the average, 20%tile and 80%ile values were calculated using the synthetic precipitation data of the past 30 years and compared with the current climatology. We have investigated the multi-year accumulated precipitation data to determine the persistence of drought. In Goseong-Sokcho forest fire case, the two-year cumulative synthetic precipitation data shows a similar value to the climate, but the three-year cumulative synthetic precipitation data was close to the 20%ile lines of the climate value. It may expose that the shortage of precipitation in 2017 had persisted until 2019, despite abundant precipitation during the summer in 2018. Therefore, Goseong-Sokcho forest fire might be spread more rapidly by drought which has been persisted since 2017.

• 한국환경과학회지
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• 제15권12호
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• pp.1141-1154
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• 2006

Orographic effect is one of the important factors to induce Local circulations and to make atmospheric turbulence, so it is necessary to use the exact topographic data for prediction of local circulations. In order to clarify the sensitivity of the spatial resolution of topography data, numerical simulations using several topography data with different spatial resolution are carried out under stable and unstable synoptic conditions. The results are as follows: 1) Influence of topographic data resolution on local circulation tends to be stronger at simulation with fine grid than that with coarse grid. 2) The hight of mountains in numerical model become mote reasonable with high resolution topographic data, so the orographic effect is also emphasized and clarified when the topographic data resolution is higher. 2) The higher the topographic resolution is, the stronger the mountain effect is. When used topographic data resolution become fine, topography in numerical model becomes closer to real topography. 3) The topographic effect tends to be stronger when atmospheric stability is strong stable. 4) Although spatial resolution of topographic data is not fundamental factor for dramatic improvement of weather prediction accuracy, some influence on small scale circulation can be recognized, especially in fluid dynamic simulation.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2011년도 학술발표회
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• pp.20-27
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• 2011

A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.

• 한국농림기상학회지
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• 제19권3호
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• pp.164-173
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• 2017

기후변화에 대응하기 위해 다양한 작부체계 구축이 시도될 수 있다. 변화하는 기후조건에서 작물들이 최적의 재배지에 배치될 수 있도록 기후적합도를 평가하는 것이 중요하다. EcoCrop 모델과 같은 월별 기후자료를 사용하여 여러 작물의 재배적합도들 계산하는 모델을 사용할 경우, 고해상도의 전자기후도를 사용하여 우리나라의 복잡한 지형을 고려한 재배 적합도 계산이 가능하다. 그러나, 방대한 기후자료의 처리를 위해 여러 전산자원들을 동시에 사용할 수 있는 병렬처리 기술 개발이 선행되어야 한다. 본 연구에서는 공개용 통계분석 도구인 R을 기반으로 EcoCrop 모델을 병렬로 구동할 수 있는 스크립트를 개발하고, 이를 격자형 기후자료에 적용하여 옥수수의 재배적지를 예측하였다. 병렬 처리를 시도한 결과 CPU 코어 개수 증가에 따른 처리 시간 단축이 선형적으로 이루어지지는 않았으나 처리시간의 상당부분을 단축할 수 있었다. 예를 들어 16개의 CPU를 사용하였을 때 이상적인 시간보다 1.5배가 넘는 시간이 소모되었으나 총 시간이 90%정도 단축되었다. 이러한 기술들을 작물 생육 모델들이 개발되지 않은 작물들에 적용할 경우, 기후변화 조건에 적응할 수 있는 작부체계 설계를 지원할 수 있을 것이다. 또한, 본 연구에서 사용한 기술들은 CPU 코어가 많은 워크스테이션에서 작동이 가능하나, 여러 컴퓨터를 연결한 중형 컴퓨터에 사용할 수 있는 MPI 기술을 적용할 수 있는 기술개발이 필요할 것이다.

• 한국환경과학회지
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• 제13권10호
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• pp.891-902
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• 2004

In order to predict air pollution and Yellow-sand dispersion precisely, it is necessary to clarify the sensitivity of meteorological field input interval. Therefore numerical experiment by atmospheric dynamic model(RAMS) and atmospheric dispersion model(PDAS) was performed for evaluating the effect of temporal and spatial resolution of meteorological data on particle dispersion. The results are as follows: 1) Base on the result of RAMS simulation, surface wind direction and speed can either synchronize upper wind or not. If surface wind and upper wind do not synchronize, precise prediction of Yellow-sand dispersion is strongly associated with upwelling process of sand of particle. 2) There is no significant discrepance in distribution of particle under usage of difference temporal resolution of meteorological information at early time of simulation, but the difference of distribution of particles become large as time goes by. 3) There is little difference between calculated particles distributions in dispersion experiments with high temporal resolution of meteorological data. On the other hand, low resolution of meteorological data occur the quantitative difference of particle density and there is strong tendency to the quantitative difference.

• 한국수자원학회논문집
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• 제40권3호
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• pp.191-204
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• 2007

본 연구에서는 기후변화가 국내 수자원에 미치는 영향을 평가하기 위해 고해상도($27km\;{\times}\;27km$)의 SRES A2 시나리오와 LARS-WG를 이용하여 국내 139개 소유역별 기후시나리오를 생산하였다. 본 연구에서 사용된 고해상도 시나리오는 약 350km 수평해상도의 ECHO-G 자료를 NCAR/PSU MM5를 이용하여 27km 수평해상도로 상세화한 것이다. A2 시나리오는 우리나라의 공간적 강수특성을 비교적 잘 모사하였으나, 한강과 금강유역의 강수량이 적게 모의되는 문제점을 보였다. 이러한 기후모형의 한계를 극복하고 유역스케일의 신뢰성 높은 기후시나리오를 생산하기 위해 일기상발생기인 LARS-WG를 선정하고 국내 기후모의에 대한 적요성을 평가하였다. LARS-WG를 이용한 기후모의 결과 월평균최대.최소기온과 월평균강수량은 관측치에 평균에서는 ${\pm}20%$, 표준편차에서는 ${\pm}50%$ 이내로 기후변화에 따른 수자원 영향평가의 목적으로 적용성이 높다고 판단되었다. 또한 LARS-WG를 이용하여 유역별 시나리오를 생산하고 관측치와 비교한 결과 기후모형에서 모의하지 못하는 지역적인 기후특성을 잘 반영하는 것으로 분석되었다.