• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.525-533
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• 2008

Global circulation models (GCMs) have been used to study impact of climate change on water resources for hydrologic models as inputs. Recently, regional circulation models (RCMs) have been used widely for climate change study, but the RCMs have been rarely used in the climate change impacts on water resources in Korea. Therefore, this study is intended to use a set of climate scenarios derived by RegCM3 RCM ($27km{\times}27km$), which is operated by Korea Meteorological Administration. To begin with, the RCM precipitation data surrounding major rainfall stations are extracted to assess validation of the scenarios in terms of reproducing low frequency behavior. A comprehensive comparison between observation and precipitation scenario is performed through statistical analysis, wavelet transform analysis and EOF analysis. Overall analysis confirmed that the precipitation data driven by RegCM3 shows capabilities in simulating hydrological low frequency behavior and reproducing spatio-temporal patterns. However, it is found that spatio-temporal patterns are slightly biased and amplitudes (variances) from the RCMs precipitation tend to be lower than the observations. Therefore, a bias correction scheme to correct the systematic bias needs to be considered in case the RCMs are applied to water resources assessment under climate change.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.6
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• pp.615-631
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• 2012

This study provides an evaluation for capability of Integrated Climate and Air quality Modeling System (ICAMS) on future regional scale climate projection. Temperature and precipitation are compared between ground-level observation data and results of regional models (MM5) for the past 30 years over the Korean peninsula. The ICAMS successfully simulates the local-scale spatial/seasonal variation of the temperature and precipitation. The probability distribution of simulated daily mean and minimum temperature agree well with the observed patterns and trends, although mean temperature shows a little cold bias about $1^{\circ}C$ compared to observations. It seems that a systematic cold bias is mostly due to an underestimation of maximum temperature. In the case of precipitation, the rainfall in winter and light rainfall are remarkably simulated well, but summer precipitation is underestimated in the heavy rainfall phenomena of exceeding 20 mm/day. The ICAMS shows a tendency to overestimate the number of washout days about 7%. Those results of this study indicate that the performance of ICAMS is reasonable regarding to air quality predication over the Korean peninsula.

• Journal of Korean Society on Water Environment
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• v.30 no.5
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• pp.549-558
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• 2014

Occurrence frequency of flood and drought tends to increase in last a few decades, leading to social and economic damage since the abnormality of climate changes is one of the causes for hydrologic facilities by exceedance its designed tolerance. Soil and Water Assessment Tool (SWAT) model was used in the study to estimate temporal variance of groundwater recharge and baseflow. It was limited to consider recession curve coefficients in SWAT model calibration process, thus the recession curve coefficient was estimated by the Baseflow Filter Program (BFLOW) before SWAT model calibration. Precipitation data were estimated for 2014 to 2100 using three models which are GFDL-ESM2G, IPSL-CM5A-LR, and MIROC-ESM with Representative Concentration Pathways (RCP) scenario. SWAT model was calibrated for the Soyang watershed with NSE of 0.83, and $R^2$ of 0.89. The percentage to precipitation of groundwater recharge and baseflow were 27.6% and 17.1% respectively in 2009. Streamflow, groundwater recharge, and baseflow were estimated to be increased with the estimated precipitation data. GFDL-ESM2g model provided the most large precipitation data in the 2025s, and IPSL-CM5A-LR provided the most large precipitation data in the 2055s and 2085s. Overall, groundwater recharge and baseflow displayed similar trend to the estimated precipitation data.

• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.249-258
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• 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.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.125-137
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• 2013

Global warming and climate change have influence on abnormal weather pattern and the rainstorm has a localized and intensive tendency in Korea. IPCC(2007) also reported the rainstorm and typhoon will be more and more stronger due to temperature increase during the 21st century. Flood Estimation Handbook(Institute of Hydrology, 1999) published in United Kingdom, in the case that the data period is shorter than return period, recommends the regional frequency analysis rather than point frequency analysis. This study uses Regional Climate Model(RCM) of Korea Meteorological Administration(KMA) for obtaining the rainfall and for performing the regional frequency analysis. We used the rainfall data from 58 stations managed by KMA and used L-moment algorithm suggested by Hosking and wallis(1993) for the regional frequency analysis considering the climate change. As the results, in most stations, the rainfall amounts in frequencies have an increasing tendency except for some stations. According to the A1B scenario, design rainfall is increased by 7~10% compared with the reference period(1970-2010).

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.31-41
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• 2011

This study was conducted to predict future land-cover changes under climate change scenarios and to cluster analysis of regional land-cover characteristics. To simulate the future land-cover according to climate change scenarios - A1B, A2, and B1 of the Special Report on Emissions Scenarios (SRES), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation with socioeconomic and biophysical driving factors. Gyeonggi-do were selected as study areas. The simulation results from 2010 to 2040 suggested future land-cover changes under the scenario conditions. All scenarios resulted in a gradual decrease in paddy area, while upland area continuously increased. A1B scenario showed the highest increase in built-up area, but all scenarios showed only slight changes in forest area. As a result of cluster analysis with the land-cover component scores, 31 si/gun in Gyeonggi-do were classified into three clusters. This approach is expected to be useful for evaluating and simulating land-use changes in relation to development constraints and scenarios. The results could be used as fundamental basis for providing policy direction by considering regional land-cover characteristics.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.67-74
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• 2008

The regional-scale transient groundwater-river interaction model is developed to gain a better understanding of the regional-scale relationships and interactions between groundwater and river system and quantify the residual river flow after groundwater abstraction from the aquifers with climate variability in the Waimea Plains, New Zealand. The effect of groundwater abstraction and climate variability on river flows is evaluated by calculating river flows at the downstream area for three different drought years (a 1 in 10 drought year, 1 in 20 drought year, and 1 in 24 drought year) and an average year with metered water abstraction data. The effect of future water demand (50 year projection) on river flows is also evaluated. A significant increase in the occurrence of zero flow, or very low flow of 100 L/sec at the downstream area is predicted due to large groundwater abstraction increase with climate variability. Modeling results shows the necessity of establishing dynamic cutback scenarios of water usage to users over the period of drought conditions considering different climate variability from current allocation limit to reduce the occurrence of low flow conditions at the downstream area.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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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.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.863-871
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• 2009

For the assessment of climate change impacts on river flow condition, CGCM 3.1 T63 is selected as future climate information. The projections come from CGCM used to simulate the GHG emission scenario known as A2. Air temperature and precipitation information from the GCM simulations are converted to regional scale data using the statistical downscaling method known as MSPG. Downscaled climate data from GCM are then used as the input data for the modified TANK model to generate regional runoff estimates for 44 river locations in Nakdong river basin. Climate change is expected to reduce the reliability of water supplies in the period of 2021~2030. In the period of 2051~2060, stream flow is expected to be reduced in spring season and increased in summer season. However, it should be noted that there are a lot of uncertainties in such multiple-step analysis used to convert climate information from GCM-based future climate projections into hydrologic information.

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.367-385
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• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.