• 대기
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• 제23권3호
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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.

• ETRI Journal
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• 제29권6호
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• pp.826-828
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• 2007

Efficient downscaling in a transcoder is important when the output should be converted to a lower resolution video. In this letter, we suggest an efficient algorithm for transcoding from MPEG-4 SP (with simple profile) to H.264/AVC with spatial downscaling. First, target image blocks are classified into monotonous, complex, and very complex regions for fast mode decision. Second, adaptive search ranges are applied to these image classes for fast motion estimation in an H.264/AVC encoder with predicted motion vectors. Simulation results show that our transcoder considerably reduces transcoding time while video quality is kept almost optimal.

• 한국농공학회논문집
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• 제63권6호
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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.

• 한국농공학회논문집
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• 제60권4호
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• pp.49-54
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• 2018

With increasing satellite-based RS(Remotely Sensed) techniques, RS soil moisture footprints have been providing for various purposes at the spatio-temporal scales in hydrology, agriculture, etc. However, their coarse resolutions still limit the applicability of RS soil moisture to field regions. To overcome these drawbacks, the LDA(Landsat-based Downscaling Algorithm) was developed to downscale RS soil moisture footprints from the coarse- to finer-scales. LDA estimates Landsat-based soil moisture($30m{\times}30m$) values in a spatial domain, and then the weighting values based on the Landsat-based soil moisture estimates were derived at the finer-scale. Then, the coarse-scale RS soil moisture footprints can be downscaled based on the derived weighting values. The LW21(Little Washita) site in Oklahoma(USA) was selected to validate the LDA scheme. In-situ soil moisture data measured at the multiple sampling locations that can reprent the airborne sensing ESTAR(Electronically Scanned Thinned Array Radiometer, $800m{\times}800m$) scale were available at the LW21 site. LDA downscaled the ESTAR soil moisture products, and the downscaled values were validated with the in-situ measurements. The soil moisture values downscaled from ESTAR were identified well with the in-situ measurements, although uncertainties exist. Furthermore, the SMAP(Soil Moisture Active & Passive, $9km{\times}9km$) soil moisture products were downscaled by the LDA. Although the validation works have limitations at the SMAP scale, the downscaled soil moisture values can represent the land surface condition. Thus, the LDA scheme can downscale RS soil moisture products with easy application and be helpful for efficient water management plans in hydrology, agriculture, environment, etc. at field regions.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• 한국농림기상학회지
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• 제24권3호
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• pp.164-178
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• 2022

주요 곡물 생산 지역에 대한 작황 계절 예측을 위해 작물모형과 기상 예보자료들이 활용되고 있다. 이 때, 작물모형의 입력자료로 활용되는 기상자료의 불확실성이 작황 예측 결과에 영향을 줄 수 있다. 본 연구에서는 기상 예보자료에 따른 작물모형 결과에 미치는 영향을 알아보고자 하였다. 주요 곡물 생산 지역인 미국의 콘벨트 지역을 대상으로 중규모 수치예보 모형인 Weather Research and Forecasting (WRF)로 10km 해상도의 계절 예측 자료를 생산하였다. 보다 상세한 기상 예보자료 생산을 가정하기 위해 통계적 기법인 Parameter-elevation Regressions on Independent Slopes Model (PRISM) 기법을 활용하여 WRF 자료를 기반으로 5km 해상도로 예측 자료를 생산하였다. WRF와 PRISM 계절 예측 자료로 CROPGRO-SOYBEAN 모형을 구동하여 두 기상 예보자료에 따른 작물 생육 모의 결과를 얻었다. 2011~2018 기간에 대하여 4월 10일부터 8일 간격으로 11개의 파종일을 설정하였으며, 3개의 콩 성숙군에 대한 품종 모수가 사용되었다. 기상 자료의 불확실성을 파악하기 위해 작물 재배기간 동안의 누적 생육도일과 누적 일사량을 비교하였다. 예측된 수량 및 성숙일 등의 주요 변수들을 비교하였다. 두 기상 자료로부터 얻어진 변수들 사이의 일치도 통계량 계산을 위해 root mean square error (RMSE), normalized root mean square error (NRMSE) 및 structural similarity(SSIM) index가 사용되었다. WRF와 PRISM에서 계산된 누적 생육도일 사이의 일치도가 낮았던 연도에 콩 성숙일 모의 값에 대한 오차가 크게 나타났다. 콩 모의 수량 또한 성숙일 및 온도의 오차가 크게 나타났던 연도에 상대적으로 낮은 일치도를 가졌다. 또한 파종일이 수량 및 성숙일 예측의 일치도에 상당한 영향을 미치는 것으로 나타났다. 이러한 결과는 WRF와 PRISM 자료 사이에 온도 자료의 불확실성이 작황 예측의 불확실성에 영향을 주었으며, 재배 시기에 따라 그 불확도의 크기가 상이할 수 있음을 암시하였다. 따라서 신뢰도 높은 작황 예측 자료 생산을 위해 작물별 재배기간을 고려한 불확실성 평가 등의 추가적인 연구가 진행되어야 할 것으로 보인다.