• Atmosphere
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• v.29 no.2
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• pp.115-129
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• 2019

Surface winds over the ocean influence not only the climate change through air-sea interactions but the coastal erosion through the changes in wave height and direction. Thus, demands on a reliable projection of future changes in surface winds have been increasing in various fields. For the future projections, climate models have been widely used and, as a priori, their simulations of surface wind are required to be evaluated. In this study, we evaluate the climatological mean surface winds over the Korean Waters simulated by five regional climate models participating in Coordinated Regional Climate Downscaling Experiment (CORDEX) for East Asia (EA), an international regional climate model inter-comparison project. Compared with the ERA-interim reanalysis data, the CORDEX-EA models, except for HadGEM3-RA, produce stronger wind both in summer and winter. The HadGEM3-RA underestimates the wind speed and inadequately simulate the spatial distribution especially in summer. This summer wind error appears to be coincident with mean sea-level pressure in the North Pacific. For wind direction, all of the CORDEX-EA models simulate the well-known seasonal reversal of surface wind similar to the ERA-interim. Our results suggest that especially in summer, large-scale atmospheric circulation, downscaled by regional models with spectral nudging, significantly affect the regional surface wind on its pattern and strength.

• International Journal of Contents
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• v.17 no.1
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• pp.61-70
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• 2021

As the resolution of climate change scenario data applied with regional models increased, Earth System Grid Federation (ESGF) was established around major climate-related organizations to jointly operated and manage large-scale climate data. ESGF developed standard software to provide model output, observation data management, dissemination, and analysis using Peer to Peer (P2P) computing technology. Roles of each institution were divided into index and data nodes. Therefore, ESGF data node was established at APEC Climate Center in Korea on behalf of Asia to share data on climate change scenarios of CORDEX-East Asia (CORDEX-EA) to study climate changes in Eastern Asia. Climate researchers are expected to play a large role in researching causes of global warming and responding to climate change by providing CORDEX-EA regional model data to the world through ESGF data node.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.269-281
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• 2011

In this review, numerical model results from global and regional climate models are introduced to regional detailed climate changes over East Asia and Korea. In particular, regional climate change scenarios in this region, which are created by several research groups in Korea based on Special Report on Emissions Scenarios (SRES) of IPCC 4th assessment report are introduced and characteristics of the scenarios are investigated. Despite slight differences in intensity, all scenarios reveal prominent warming over the Korean peninsula in future climate. Changes in precipitation amount vary with given scenarios and periods, but the frequency and intensity of heavy precipitation generally tend to increase in all scenarios. South Korea except for mountainous regions is expected to change into subtropical climate in future, which accompanies distinct changes in ecosystems and seasons.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.5
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• pp.73-78
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• 2007

It has been increasing that significant loss of life and property due to global wanning and extreme weather, and the climate and temperature changes in Korea Peninsula are now greater than the global averages. Climate information from regional climate models(RCM) at a finer resolution than that of global climate models(GCM) is required to predictclimate and weather variability, changes, and impacts. The new surface boundary conditions(SBCs) development is motivated by the limitations and inconsistencies of existing SBCs that have influence on model predictability. A critical prerequisite in constructing SBCs is that the raw data should be accurate with physical consistency across all relevant parameters and must be appropriately filled for missing data if any. The aim of this study is to construct appropriate SBCs for the RCM in Asia domain which will be used for the prevention of disasters due to climate changes. As all SBCs have constructed onto the 30km grid-mesh of the RCM suitable for Asia applications, they can be also used for other distributed models for climate and hydrologic studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1388-1392
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• 2008

Water resources management depends on dealing inherent uncertainties stemming from climatic and hydrological inputs and models. Dealing with these uncertainties remains a challenge. Streamflow forecasts basically contain uncertainties arising from model structure and initial conditions. Recent enhancements in climate forecasting skill and hydrological modeling provide an breakthrough for delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The approach here proposes integration and coupling of global climate models (GCM), multiple regional climate models, and numerous hydrological models to improve streamflow forecasting and characterize system uncertainty through generation of ensemble forecasts.

• Ocean and Polar Research
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• v.34 no.4
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• pp.431-444
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• 2012

We simulated and compared present and future ocean circulation in the East China Sea using an East Asia Regional Ocean model. Mean climate states for 1990~1999 and 2030~2039 were used as surface conditions for simulations of present and future ocean circulation, which were derived from the simulations of three different global climate models, ECHAM5-MPI, GFDL-CM2.0 and MIROC3.2_hires, for the 20th century and those of 21st century as projected by the IPCC SRES A1B. East Asia Regional Ocean model simulated the detailed patterns of temperature, salinity and current fields under present and future climate conditions and their changes instead of the simple structures of global climate models. To some extent, there are consistent ocean circulation changes derived from the three pairs corresponding to the global climate model in so much as the temperature increases not only in winter but summer at both the surface and bottom and that temperature and salinity changes are prominent near the Chinese coast and in the Changjiang bank. However, the simulated circulations are different among each other depending on the prescribed atmospheric conditions not only under present climate but also with regard to future climate conditions. There is not a coincident tendency in ocean circulation changes between present and future simulations derived from the three pairs. This suggests that more simulations with different pairs are needed.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.750-760
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• 2011

In this study, the reproducibility of the simulated current climate by using two regional climate models, such as Seoul National University Regional Climate Model (SNURCM) and Weather Resuearch and Forecasting (WRF), is evaluated in advance to produce the standard regional climate scenario of future climate. Within the evaluation framework of a COordinated Regional climate Downscaling EXperiment (CORDEX), 28-year-long (1978-2005) regional climate simulation was conducted by using the Hadley Centre Global Environmental Model (HadGEM2-AO) global simulation data of the National Institute of Meteorological Research (NIMR) as a lateral boundary forcing. The simulated annual surface temperatures were in good agreement with the observation; the spatial correlation coefficients between each model and observation were over 0.98. The cold bias, however, were shown over the northern boundary in the both simulated results. In evaluation of the simulated precipitation, the skill was reasonable and good. The spatial correlation coefficients for the precipitation over the land area were 0.85 and 0.79 in SNURCM and WRF, respectively. It is noted that two regional climate models (RCMs) have different characteristics for the distribution of precipitation over equatorial and midlatitude areas. SNURCM shows better distribution of the simulated precipitation associated with the East Asia summer monsoon in the mid-latitude areas, but WRF shows better in the equatorial areas in comparison to each other. The simulated precipitation is overestimated in summer season (JJA) rather than in spring season (MAM), whereas the spatial distribution of the precipitation in spring season corresponds to the observation better than in summer season. Also the RCMs were capable of reproducing the annual variability of the maximum amount and its timing in July, in which the skills over the inland area were in better agreement with the observation than over the maritime area. The simulated regional climates, however, have the limitation to represent the number of days for extremely hot temperature and heavy rainfall over South Korea.

• Journal of Climate Change Research
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• v.34 no.20
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• pp.8257-8271
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• 2021

This study presents the ability of seasonal forecast models to represent the observed midlatitude teleconnection associated with El Niño-Southern Oscillation (ENSO) events over the North American region for the winter months of December, January, and February. Further, the impacts of the associated errors on regional forecast performance for winter temperatures are evaluated, with a focus on 1-month-lead-time forecasts. In most models, there exists a strong linear relationship of temperature anomalies with ENSO, and, thus, a clear anomaly sign separation between both ENSO phases persists throughout the winter, whereas linear relationships are weak in observations. This leads to a difference in the temperature forecast performance between the two ENSO phases. Forecast verification scores show that the winter-season warming events during El Niño in northern North America are more correctly forecast in the models than the cooling events during La Niña and that the winter-season cooling events during El Niño in southern North America are also more correctly forecast in the models than warming events during La Niña. One possible reason for this result is that the remote atmospheric teleconnection pattern in the models is almost linear or symmetric between the El Niño and La Niña phases. The strong linear atmospheric teleconnection appears to be associated with the models' failure in simulating the westward shift of the tropical Pacific Ocean rainfall response for the La Niña phase as compared with that for the El Niño phase, which is attributed to the warmer central tropical Pacific in the models. This study highlights that understanding how the predictive performance of climate models varies according to El Niño or La Niña phases is very important when utilizing predictive information from seasonal forecast models.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.27-60
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• 2016

An integrated assessment model of climate and the economy (IAM) has been a standard tool for the economic analysis of climate change and policy recommendations. Since policy measures to address climate change take places at a national level, a regional integrated assessment model of climate and the economy (RIAM) is gaining more importance. A RIAM is a useful tool for the assessment of regional (or national) impacts of climate change. This paper investigates the main features of the currently available RIAMs. The focus is social welfare functions and the regional aspects of climate change. The comparative analysis shows that there is a huge gap between the economics of climate change and its applications to RIAMs. As an application, this paper examines the effect of social welfare functions on optimal solutions of the RICE (Regional Integrated model of Climate and the Economy) model. It is found that optimal climate policy such as carbon tax or emissions control rate is very sensitive to the assumptions on social welfare functions of RIAMs. It is better for each country to have their own RIAM as a basic tool for national climate policy-making and for international bargaining in greenhouse-gas mitigation. This is because a country's own preferences such as efficiency, equity, and sustainable development as well as national circumstances can be reflected in RIAM. The Republic of Korea has not developed its own RIAM yet. The comparative analysis and the numerical model in this paper can be a stepping stone for the development of such a national model.

• 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.