• 한국수자원학회논문집
• /
• 제36권3호
• /
• pp.345-363
• /
• 2003

대기순환모형(GCM)에 의하면 온실가스농도의 증가는 전구와 국지규모의 기후변화에 중요한 관련이 있음이 알려져 있다. GCM은 단일지점의 기상학적 순환과정을 분석하는데는 불확실성을 지니고 있기 때문에 현재로서는 축소기법이 대기순환모형(GCM)의 개발자들이 제공할 수 있는 것과 모형을 이용하여 기후영향을 평가하는 연구자들이 요구하는 것 사이의 차이점을 연계하기 위해 이용되고 있다. 본 논문에서는 통계학적 축소기법을 이용하여 국지 규모의 기후변화의 영향을 평가할 수 있는 방법을 제시하고자 하였다. 본 방법을 이용한다면 현재와 미래의 국지적 규모의 기후강제력 하에서의 지표 기상변수의 시나리오를 저 비용으로 신속하게 작성할 수 있다. 기후변화시나리오의 작성은 통계학적 회귀방법인 전이함수와 추계학적 일기발생모형을 이용하였다. 전이함수는 저해상도의 GCM 격자 변수들을 고해상도의 단일 지점의 변수들로 변환시키며, 이 변수들은 단일 지점의 특정 일 지표 기상 변수를 모의하기 위해 추계학적 일기발생 모형의 매개변수를 수정하는데 이용되었다. 본 연구에서는 YONU GCM을 이용하여 제어실험과 점증실험을 실시하여 전구규모의 기후변화시나리오를 작성하였다.

• 대기
• /
• 제25권4호
• /
• pp.669-683
• /
• 2015

In this study, we investigated the prediction skills of four multiple linear regression methods for monthly air temperature over South Korea. We used simulation results from four regional climate models (RegCM4, SNURCM, WRF, and YSURSM) driven by two boundary conditions (NCEP/DOE Reanalysis 2 and ERA-Interim). We selected 15 years (1989~2003) as the training period and the last 5 years (2004~2008) as validation period. The four regression methods used in this study are as follows: 1) Homogeneous Multiple linear Regression (HMR), 2) Homogeneous Multiple linear Regression constraining the regression coefficients to be nonnegative (HMR+), 3) non-homogeneous multiple linear regression (EMOS; Ensemble Model Output Statistics), 4) EMOS with positive coefficients (EMOS+). It is same method as the third method except for constraining the coefficients to be nonnegative. The four regression methods showed similar prediction skills for the monthly air temperature over South Korea. However, the prediction skills of regression methods which don't constrain regression coefficients to be nonnegative are clearly impacted by the existence of outliers. Among the four multiple linear regression methods, HMR+ and EMOS+ methods showed the best skill during the validation period. HMR+ and EMOS+ methods showed a very similar performance in terms of the MAE and RMSE. Therefore, we recommend the HMR+ as the best method because of ease of development and applications.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2010년도 학술발표회
• /
• pp.268-272
• /
• 2010

The research presented here represents a collaborative effort with the SFWMD on developing scenarios for future climate for the SFWMD area. The project focuses on developing methodology for simulating precipitation representing both natural quasi-oscillatory modes of variability in these climate variables and also the secular trends projected by the IPCC scenarios that are publicly available. This study specifically provides the results for precipitation modeling. The starting point for the modeling was the work of Tebaldi et al that is considered one of the benchmarks for bias correction and model combination in this context. This model was extended in the framework of a Hierarchical Bayesian Model (HBM) to formally and simultaneously consider biases between the models and observations over the historical period and trends in the observations and models out to the end of the 21st century in line with the different ensemble model simulations from the IPCC scenarios. The low frequency variability is modeled using the previously developed Wavelet Autoregressive Model (WARM), with a correction to preserve the variance associated with the full series from the HBM projections. The assumption here is that there is no useful information in the IPCC models as to the change in the low frequency variability of the regional, seasonal precipitation. This assumption is based on a preliminary analysis of these models historical and future output. Thus, preserving the low frequency structure from the historical series into the future emerges as a pragmatic goal. We find that there are significant biases between the observations and the base case scenarios for precipitation. The biases vary across models, and are shrunk using posterior maximum likelihood to allow some models to depart from the central tendency while allowing others to cluster and reduce biases by averaging. The projected changes in the future precipitation are small compared to the bias between model base run and observations and also relative to the inter-annual and decadal variability in the precipitation.

• 대한토목학회논문집
• /
• 제30권6B호
• /
• pp.561-569
• /
• 2010

본 연구에서는 현재 및 미래 기후에서의 가뭄심도-영향면적-지속기간 곡선의 비교를 통하여 극한 가뭄 사상에 대한 기후변화의 영향을 살펴보았다. 가뭄심도-영향면적-지속기간 곡선은 극한 호우사상을 특성화하기 위한 일반적으로 적용되는 우량깊이-영향면적-지속기간 곡선에서 우량깊이를 가뭄심도를 대표할 수 있는 적절한 지수로 대체함으로써 가뭄사상을 분석할 수 있는 도구를 제공한다. 미래 월 강수량 시계열은 $27km{\times}27km$의 공간적인 해상도를 가지는 기상청 지역기후모형으로부터 획득되었으며, 가뭄심도는 표준강수지수를 이용하여 산출하였다. 분석 결과, 농업가뭄에 대한 위험성은 특히 단기간의 지속기간의 경우에 현재보다 심화될 수 있는 것으로 분석되었으며, 수문학적 가뭄의 경우는 가뭄지속기간에 상관없이 모두 현재보다는 미래에 가뭄심도가 더 깊어질 가능성이 있는 것으로 예측되었다. 이에 따라 현재의 수자원 공급 시스템에 대한 기후변화 취약성 평가가 시급함을 제시하고 있다.

• 한국제4기학회지
• /
• 제19권2호
• /
• pp.50-54
• /
• 2005

Some basic summer precipitation features over East Asia during the $20^{th}-21^{st}$ century as simulated / projected by the 22 coupled climate models under the IPCC AR4 program are investigated. Keeping in view that these are climate runs without prescribed SSTs, models perform well in simulating the regional annual cycle, spatial patterns (not shown) and the inter-annual variability. The projections under the 1% increase in $CO_2$ compounded until reaching double and held constant thereafter reveal that (a) Precipitation is likely to increase in all the months in particular during the summer monsoon (JJA) months. (b) The mean summer monsoon rainfall can increase from 4.2 to 13.5% and its variability is also likely to increase in the warming world due to increase in $CO_2$ (c) Extreme excess and deficient seasonal monsoons are likely to become more intense (not shown here) (d) Once the increase in $CO_2$ is cut-off, the system will reach a state of equilibrium, and then the rate of increase in precipitation is also expected to remain constant.

• Ocean and Polar Research
• /
• 제34권2호
• /
• pp.253-264
• /
• 2012

In the northwestern Pacific, spawning of the common squid, Todarodes pacificus, occurs at continental shelf and slope areas of 100-500 m, and the optimum temperature for the spawning and survival of paralarvae is assumed to be $18-23^{\circ}C$. To predict the spawning ground of Todarodes pacificus under future climate conditions, we simulated the present and future ocean circulations, using an East Asia regional ocean model (Modular Ocean Model, MOM version3), projected by two different global climate models (MPI_echam5, MIROC_hires), under an IPCC SRES A1B emission scenario. Mean climate states for 1990-1999 and 2030-2039 from 20th and 21th Century Climate Change model simulation (from the IPCC 4th Assessment Report) were used as surface conditions for simulations, and we examined changes in spawning ground between the 1990s and 2030s. The results revealed that the distribution of spawning ground in the 2030s in both climate models shifted northward in the East China Sea and East Sea, for both autumn and winter populations, compared to that of the 1990s. Also, the spawning area (with $1/6^{\circ}{\times}1/6^{\circ}$ grid) in the 2030s of the autumn and winter populations will decline by 11.6% (MPI_echam5) to 30.8% (MIROC_hires) and 3.0% (MPI_echam5) to 18.2% (MIROC_hires), respectively, from those of the 1990s.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2009년도 학술발표회 초록집
• /
• pp.529-534
• /
• 2009

Climate models, both global and regional, have increased in sophistication and are being run at increasingly higher resolutions. The Land Surface Models (LSMs) coupled to these climate models have evolved from simple bucket models to sophisticated Soil-Vegetation-Atmosphere Transfer (SVAT) schemes needed to support complex linkages and processes. However, some underpinnings of terrestrial hydrologic parameterizations so crucial in the predictions of surface water and energy fluxes cause model errors that often manifest as non-linear drifts in the dynamic response of land surface processes. This requires the improved parameterizations of key processes for the terrestrial hydrologic scheme to improve the model predictability in surface water and energy fluxes. The Common Land Model (CLM), one of state-of-the-art LSMs, is the land component of the Community Climate System Model (CCSM). However, CLM also has energy and water biases resulting from deficiencies in some parameterizations related to hydrological processes. This research presents the implementation of a selected set of parameterizations and their effects on the runoff prediction. The modifications consist of new parameterizations for soil hydraulic conductivity, water table depth, frozen soil, soil water availability, and topographically controlled baseflow. The results from a set of offline simulations are compared with observed data to assess the performance of the new model. It is expected that the advanced terrestrial hydrologic scheme coupled to the current CLM can improve model predictability for better prediction of runoff that has a large impact on the surface water and energy balance crucial to climate variability and change studies.

• 한국농림기상학회지
• /
• 제23권1호
• /
• pp.68-81
• /
• 2021

농업 생태계는 주요 온실가스의 배출원 중 하나로, 농경지에서의 온실가스 배출량을 최소화하면서 최적의 수량을 얻기 위한 기후변화 적응옵션을 도출하기 위해서는, 상세한 공간적 규모에서 여러 모형들을 연계하여 구동하는 것이 유리하다. 본 연구에서는 DSSAT 모형과 DNDC 모형을 연계하여 상세한 공간 규모에서 기후변화 영향평가를 수행할 수 있도록 지원하기 위한 도구를 개발하고자 하였다. 객체 지향 언어인 R과 C++을 사용하여 DNDC 모형의 격자형 입력자료를 생성하기 위한 DRIFT (DNDC Regional Input File Tool)을 구현하였다. 기후변화 조건에서 격자별 작물 생육모의를 위해 생성된 DSSAT 모형의 입력자료 및 출력자료를 사용하여 DNDC 모형의 입력자료를 생성하였다. 생성된 입력자료를 사용하여 미래 기후변화 조건에서의 온실가스 배출량을 모의하였다. 입력자료를 생성하는 시간은 격자 지점의 수에 비례하여 증가하였다. 그 중, DSSAT 모형의 담수 깊이 자료를 DNDC 모형의 담수 기간으로 변환하는 과정에서 시간이 비교적 오래 걸렸으나, 그 외의 입력자료를 생성하는 데에는 짧은 시간만이 소요되었다. 본 연구에서는 비교적 적은 지점을 대상으로 하였으나, 대량의 자료를 처리하고자 할 경우 일부 계산과정을 병렬화함으로써 구동시간을 줄일 필요가 있을 것이다. 이후 다른 모형들에 대한 확장을 통해 모형 간 연계를 위한 입력자료 생성에 소요되는 시간을 줄일 수 있을 것이다.

• 환경영향평가
• /
• 제15권4호
• /
• pp.249-258
• /
• 2006

Impacts of global warming have been identified in many areas including natural ecosystem. A good number of studies based on climate models forecasting future climate have been conducted in many countries worldwide. Due to its global coverage, GCM, which is a most frequently used climate model, has limits to apply to Korea with such a narrower and complicated terrain. Therefore, it is necessary to perform a study impact assessment of climate changes with a climate model fully reflecting characteristics of Korean climate. In this respect, this study was designed to compare and analyze the GCM and RCM in order to determine a suitable climate model for Korea. In this study, spatial scope was Korea for 10 years from 1981 to 1990. As a research method, current climate was estimated on the basis of the data obtained from observation at the GHCN. Future climate was forecast using 4 GCMs furnished by the IPCC among SRES A2 Scenario as well as the RCM received from the NIES of Japan. Pearson correlation analysis was conducted for the purpose of comparing data obtained from observation with GCM and RCM. As a result of this study, average annual temperature of Korea between 1981 and 1990 was found to be around $12.03^{\circ}C$, with average daily rainfall being 2.72mm. Under the GCM, average annual temperature was between 10.22 and $16.86^{\circ}C$, with average daily rainfall between 2.13 and 3.35mm. Average annual temperature in the RCM was identified $12.56^{\circ}C$, with average daily rainfall of 5.01mm. In the comparison of the data obtained from observation with GCM and RCM, RCMs of both temperature and rainfall were found to well reflect characteristics of Korea's climate. This study is important mainly in that as a preliminary study to examine impact of climate changes such as global warming it chose appropriate climate model for our country. These results of the study showed that future climate produced under similar conditions with actual ones may be applied for various areas in many ways.

• 대기
• /
• 제23권4호
• /
• pp.527-538
• /
• 2013

In this study, climate over Korea based on the Historical scenario induced by HadGEM2-AO is simulated by WRF. For this purpose, a system that can be used be for numerical integration over the Far East Asian area of the center of the Korean Peninsula with 12.5 km-horizontal resolution was set-up at "Haebit", the early portion of KMA Supercomputer Unit-3. Using the system, the downscaling experiments were conducted for the period 1979-2010. The simulated results of HadGEM2-AO and WRF are presented in terms of 2 m-temperature and precipitation during boreal summer and winter of Historical for the period 1981~2005, compared with observation. As for the mean 2 m-temperature, the general patterns of HadGEM2-AO and WRF are similar with observation although WRF showed lower values than observation due to the systematic bias. WRF reproduced a feature of the terrain-following characteristics reasonably well owing to the increased horizontal resolution. Both of the models simulated the observed precipitation pattern for DJF than JJA reasonably, while the rainfall over the Korean Peninsula in JJA is less than observation. HadGEM2-AO in DJF 2 m-temperature and JJA precipitation has warm and dry biases over the Korean Peninsula, respectively. WRF showed cold bias over JJA 2 m-temperature and wet bias over DJF precipitation. The larger bias in WRF was attributed to the addition of HadGEM2-AO's bias to WRF's systematic bias. Spatial correlation analysis revealed that HadGEM2-AO and WRF had above 0.8 correlation coefficients except for JJA precipitation. In the EOF analysis, both models results explained basically same phase changes and variation as observation. Despite the difference in mean and bias fields for both models, the variabilities of the two models were almost similar with observation in many respects, implying that the downscaled results can be effectively used for the study of regional climate around the Korean Peninsula.