• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.282-282
• /
• 2016

지표수문해석모형이란 전 지구를 대상으로 수문해석 및 예측이 가능한 분포형 수문모형이다. 본 연구에서는 CSEOF(Cyclostationary Empirical Orthogonal Functions) 분석 방법을 이용하여 지표수문해석 모형 중 하나인 VIC(Variable Infiltration Capacity)모형의 토양수분 모의 성능을 평가해보고자 한다. 이를 위하여 먼저 남한에 대한 VIC 모형으로 모의한 토양수분 예측 결과와 관측자료를 수집하였다. 모의 성능 평가 기간은 1976년부터 2006년까지이다. 이후 본 연구에서는 수집된 VIC 모형의 예측 결과와 관측 자료에 대한 CSEOF 분석을 수행하여 각 자료의 월별 주된 변동 특성을 추출하였다. VIC 모형의 예측 결과와 관측자료의 상관관계는 CSEOF 분석 결과에 대한 Pattern Correlation으로 정량화되었다. 이와 더불어 본 연구에서는 모형의 모의 성능 평가에 주로 사용되는 NRMSE(Nomalized Root Mean Square Error)를 산정하여 예측 결과의 오차를 평가하였다. Pattern Correlation과 NRMSE를 모두 고려하여 VIC 모형의 성능을 평가해본 결과, 건기에 해당하는 기간과 우기에 해당하는 기간의 모의 성능이 다르게 나타났다. 본 연구의 결과는 추후에 지표수문해석 모형의 예측 결과를 이용하는 기후변화 관련 연구에 활용될 수 있을 것으로 판단된다.

• Atmosphere
• /
• v.19 no.2
• /
• pp.107-125
• /
• 2009

Statistical downscaled surface temperature datasets by employing the cyclostationary empirical orthogonal function (CSEOF) analysis and multiple linear regression method are examined. For evaluating the efficiency of this statistical downscaling method, monthly surface temperature of the ECMWF has been downscaled into monthly temperature having a fine spatial scale of ~20km over the Korean peninsula for the 1973-2000 period. Monthly surface temperature of the ECHOG has also been downscaled into the same spatial scale data for the same period. Comparisons of temperatures between two datasets over the Korean peninsula show that annual mean temperature of the ECMWF is about $2^{\circ}C$ higher than that of the ECHOG. After applying to the statistical downscaling method, the difference of two annual mean temperatures reduces less than $1^{\circ}C$ and their spatial patterns become even close to each other. Future downscaled data shows that annual temperatures in the A1B scenario will increase by $3.5^{\circ}C$ by the late 21st century. The downscaled data are influenced by the ECHOG as well as observation data which includes effects of complicated topography and the heat island.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.299-303
• /
• 2008

In this study, an uncertainty assessment for surface air temperature(T2m) and precipitation(PCP) over East Asia is carried out. The data simulated by the intergovermental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Atmosphere-Ocean coupled general circulation Model (AOGCM) are used to assess the uncertainty. Examination of the seasonal uncertainty of T2m and PCP variabilities shows that spring-summer cold bias and fall warm bias of T2m are found over both East Asia and the Korea peninsula. In contrast, distinctly summer dry bias and winter-spring wet bias of PCP over the Korea peninsula is found. To investigate the PCP seasonal variability over East Asia, the cyclostationary empirical orthogonal function(CSEOF) analysis is employed. The CSEOF analysis can extract physical modes (spatio-temporal patterns) and their undulation (PC time series) of PCP, showing the evolution of PCP. A comparison between spatio-temporal patterns of observed and modeled PCP anomalies shows that positive PCP anomalies located in northeastern China (north of Korea) of the multi-model ensemble(MME) cannot explain properly the contribution to summer monsoon rainfalls across Korea and Japan. The uncertainty of modeled PCP indicates that there is disagreement between observed and MME anomalies. The spatio-temporal deviation of the PCP is significantly associated with lower- and upper-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly contribute to summer rainfalls. These lower- and upper-level circulations physically consistent with PCP give a insight of the reason why differences between modeled and observed PCP occur.

• Atmosphere
• /
• v.20 no.2
• /
• pp.111-130
• /
• 2010

An uncertainty assessment for precipitation datasets simulated by Atmosphere-Ocean Coupled General Circulation Model (AOGCM) is conducted to provide reliable climate scenario over East Asia. Most of results overestimate precipitation compared to the observational data (wet bias) in spring-fall-winter, while they underestimate precipitation (dry bias) in summer in East Asia. Higher spatial resolution model shows better performances in simulation of precipitation. To assess the uncertainty of spatiotemporal precipitation in East Asia, the cyclostationary empirical orthogonal function (CSEOF) analysis is applied. An annual cycle of precipitation obtained from the CSEOF analysis accounts for the biggest variability in its total variability. A comparison between annual cycles of observed and modeled precipitation anomalies shows distinct differences: 1) positive precipitation anomalies of the multi-model ensemble (MME) for 20 models (thereafter MME20) in summer locate toward the north compared to the observational data so that it cannot explain summer monsoon rainfalls across Korea and Japan. 2) The onset of summer monsoon in MME20 in Korean peninsula starts earlier than observed one. These differences show the uncertainty of modeled precipitation. Also the comparison provides the criteria of annual cycle and correlation between modeled and observational data which helps to select best models and generate a new MME, which is better than the MME20. The spatiotemporal deviation of precipitation is significantly associated with lower-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly are strongly associated with summer rainfalls. These lower-level circulations physically consistent with precipitation give insight into description of the reason in the monsoon of East Asia why behaviors of individually modeled precipitation differ from that of observation.