• Atmosphere
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• v.31 no.5
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• pp.473-488
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• 2021

A new physical/statistical diagnostic downscale model has been developed for use to improve near-surface air temperature forecasts. The model includes a series of physical and statistical correction methods that account for un-resolved topographic and land-use effects as well as statistical bias errors in a low-resolution atmospheric model. Operational temperature forecasts of the Local Data Assimilation and Prediction System (LDAPS) were downscaled at 100 m resolution for three months, which were used to validate the model's physical and statistical correction methods and to compare its performance with the forecasts of the Korea Meteorological Administration Post-processing (KMAP) system. The validation results showed positive impacts of the un-resolved topographic and urban effects (topographic height correction, valley cold air pool effect, mountain internal boundary layer formation effect, urban land-use effect) in complex terrain areas. In addition, the statistical bias correction of the LDAPS model were efficient in reducing forecast errors of the near-surface temperatures. The new high-resolution downscale model showed better agreement against Korean 584 meteorological monitoring stations than the KMAP, supporting the importance of the new physical and statistical correction methods. The new physical/statistical diagnostic downscale model can be a useful tool in improving near-surface temperature forecasts and diagnostics over complex terrain areas.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.484-485
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• 2008

• Fashion & Textile Research Journal
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• v.12 no.5
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• pp.642-649
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• 2010

This study was designed to generate briefs pattern for women in their twenties using 3D parametric body model. 151 women in their 20's were random sampled and measured using Martine's anthropometry. And one subject was chosen as the representative subject for 3D scanning. Parametric model was generated of using CATIA P3, Unigraphics NX4.0, Rapidform 2006. And the 3D surface of parametric body model was flattened onto the 2D plane. 3 downscale ratios(0%, 10%, 15%) were applied to generated pattern to figure out what downscale ratio was suitable to make briefs with stretch fabric. 4 kinds of experimental briefs were made with stretch fabrics(0%, 10%, 15% downscale) and worn on the dressform. Subjective evaluation on the appearance was done and the data was analyzed by ANOVA with post-hoc test. Briefs pattern was generated through the process of flattening the parametric surface and arranging the patches to make briefs pattern by dart manipulation. The different ration of outline and area between 3D surface and 2D pattern were 0.22% and 0.09% respectively. It showed that a parametric model could provide a desirable pattern with minute size error. The results of subjective evaluation on the appearance of 4 experimental briefs showed that stretch briefs with 15% downscale ratio was evaluated most highly in most items. Findings imply that it is feasible to apply 3D parametric model to generate patterns for various items considering various fabric properties.

• Atmosphere
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• v.23 no.3
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• pp.347-356
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• 2013

The climate projection with a high spatial resolution is required for the studies on regional climate changes. The Korea Meteorological Administration (KMA) has provided downscaled RCP (Representative Concentration Pathway) scenarios over Korea with 1 km spatial resolution. If there are additional climate projections produced by dynamically downscale, the quality of impacts and vulnerability assessments of Korea would be improved with uncertainty information. This technical note intends to instruct the methods to downscale the climate projections dynamically from the Community Earth System Model (CESM) to the Weather Research and Forecast (WRF) model. In particular, here we focus on the instruction to utilize CAM2WRF, a sub-program to link output of CESM to initial and boundary condition of WRF at Linux platform. We also provide the example of the dynamically downscaled results over Korean Peninsula with 50 km spatial resolution for August, 2020. This instruction can be helpful to utilize global scale climate scenarios for studying regional climate change over Korean peninsula with further validation and uncertainty/bias analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.181-191
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• 2009

This study suggests the assessment technique for climate change effect on drought in Korea based on the AR4 SRES A2 scenario reported in IPCC fourth assessment report in 2007. IPCC provides monthly outputs of 24 climate models through the DDC. One of the models is BCM2 model which was developed at BCCR in Norway and NCEP data is used for downscaling. The K-NN(K-Nearest Neighbor) and ANN(Artificial Neural Network) are selected as downscaling technique to downscale the temperature and precipitation at Seoul station in Korea. K-NN could downscale both temperature and precipitation well. ANN made a good result for temperature, but it gave a divergence result in precipitation. Finally, SPI of Seoul station is computed to evaluate the effect of climate change on drought. BCM2 predicted that temperature will increase and drought severity will increase because of the increased drought spell at Seoul station.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.627-634
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• 2012

This study includes results of basin test for hydrodynamic performance evaluation with a developed inflatable kayak. Inclining experiment and turning trial experiment of the developed inflatable kayak and an abroad product were carried out in the Ocean engineering Basin. Resistance test was carried out by using downscale model in the circulating water channel. Through method of following performance evaluation, advantage and disadvantage of the developed inflatable kayak were compared with those of the abroad product.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.370-374
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• 2011

기후변화에 따른 수해를 대비하기 위해서는 미래의 확률강수량을 알아야 한다. Global Circulation Model(GCM)은 미래의 기후변화를 예측하기 위하여 많은 분야에서 널리 쓰이고 있다. GCM의 시간축척은 일반적으로 월단위로 시간단위 자료를 사용하는 수공학 분야에 직접적으로 적용하기에는 많은 문제가 있다. 또한 GCM 예측값은 실강우값과 큰 편의(bias)를 가지고 있어 직접적인 적용이 힘들다. 이런 문제를 해결하고자 다양한 다운스케일(downscale)기법이 연구되고 있다. 다운스케일기법을 적용하여 시간자료를 예측하면 전반적인 통계값을 잘 재현해내나, 극치값의 경우 잘 재현해내지 못하는 문제가 있다. 이런 문제점을 극복하고자 본 연구에서는 연최대 월강수량과 연최대 시간강수량의 이변량빈도해석을 통하여 기후변화를 고려한 강우-지속기간-빈도 관계의 변화를 평가해보고자 한다. 본 연구는 연최대 월강수량과 연최대 시간강수량과의 관계가 변하지 않는다는 가정하에 관측강수량을 이용하여 연최대 월강수량과 연최대 시간강수량의 이변량분포모형을 구축하였다. 이변량 분포모형을 구축하기 위하여 copula 모형을 적용하였다. 구축된 모형에 GCM으로 예측된 연최대 월강수량을 적용하여 미래의 확률강수량을 평가하였다. 본 연구에서는 서울지점을 대상지점으로 선정하였으며, A2 기후변화시나리오를 적용한 GCM 예측값을 이용하였다. 적용결과 A2 기후변화 시나리오 상에서 미래의 확률강수량이 크게 증가하는 것이 확인되었다.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.49-60
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• 2021

BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.821-831
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• 2009

The study was aimed to assess the expected impact of climate change on the water cycle and soil losses in Daecheong Reservoir watershed, Korea using the Soil and Water Assessment Tool (SWAT) that was validated for the watershed in a previous study. Future climate data including precipitation, temperature and humidity generated by introducing a regional climate model (Mesoscale Model Version 5, MM5) to dynamically downscale global circulation model (European Centre Hamburg Model Version 4, ECHAM4) were used to simulate the hydrological responses and soil erosion processes in the future 100 years (2001~2100) under the Special Report on Emissions Scenario (SRES) A1B. The results indicated that the climate change may increase in the amount of surface runoff and thereby sediment load to the reservoir. Spatially, the impact was relatively more significant in the subbasin Bocheongcheon because of its lower occupation rate of forest land compared to other subbasins. Seasonally, the increase of surface runoff and soil losses was more significant during late summer and fall season when both flood control and turbidity flow control are necessary for the reservoir and downstream. The occurrence of extreme turbidity flow events during these period is more vulnerable to reservoir operation because the suspended solids that remained water column can be resuspended by vertical mixing during winter turnover period. The study results provide useful information for the development of adaptive management strategy for the reservoir to cope with the expected impact of future climate change.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.231-248
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• 2011

This study aims to develop the Flood Vulnerability Index (FVI) and apply it to the Bukhan River Basin. A1B and A2 scenarios of CGCM3 of IPCC were adopted and SDSM (Statistical Downscaling Model) was used to downscale the original data to the daily data. Driver-Presure-State-Impact-Response (DPSIR) model was introduced to select all appropriate indicators for FVI and the daily rainfall-runoff model was simulated using HSPF (Hydrological Simulation Program-Fortran). Since FIV proposed in this study has a capability to quantify the potential flood vulnerability considering both present and future climate conditions, it is expected to be used for the comprehensive water resources and environmental planning.