• International conference on construction engineering and project management
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• 2015.10a
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• pp.738-739
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• 2015

The main objective of this study, "Spatial Downscaling of Precipitation from GCMs for Assessing Climate Change over Han River and Imjin River Watersheds", is to carry out over Han River and Imjin River watersheds. To this end, a statistical regression method with MOS (Model Output Statistics) corrections at every downscaling step was developed and applied for downscaling the spatially-coarse Global Climate Model Projections (GCMPs) from CCSM3 and CSIRO with respect to precipitation into 0.1 degree (about 11 km) spatial grid over study regions. The spatially archived hydro-climate data sets such as Willmott, GsMap and APHRODITE datasets were used for MOS corrections by means of monthly climatology between observations and downscaled values. Precipitation values downscaled in this study were validated against ground observations and then future climate simulation results on precipitation were evaluated for the projections.

• Atmosphere
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• v.33 no.4
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• pp.423-440
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• 2023

The updated version of Global Ocean Data Assimilation and Prediction System (GODAPS) in the NIMS/KMA (National Institute of Meteorological Sciences/Korea Meteorological Administration), which has been in operation since December 2021, is being introduced. This technical note on GODAPS2 describes main progress and updates to the previous version of GODAPS, a software tool for the operating system, and its improvements. GODAPS2 is based on Forecasting Ocean Assimilation Model (FOAM) vn14.1, instead of previous version, FOAM vn13. The southern limit of the model domain has been extended from 77°S to 85°S, allowing the modelling of the circulation under ice shelves in Antarctica. The adoption of non-linear free surface and variable volume layers, the update of vertical mixing parameterization, and the adjustment of isopycnal diffusion coefficient for the ocean model decrease the model biases. For the sea-ice model, four vertical ice layers and an additional snow layer on top of the ice layers are being used instead of previous single ice and snow layers. The changes for data assimilation include the updated treatment for background error covariance, a newly added bias scheme combined with observation bias, the application of a new bias correction for sea level anomaly, an extension of the assimilation window from 1 day to 2 days, and separate assimilations for ocean and sea-ice. For comparison, we present the difference between GODAPS and GODAPS2. The verification results show that GODAPS2 yields an overall improved simulation compared to GODAPS.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.27-42
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• 2017

The global rise in atmospheric $CO_2$ concentration and its associated climate change have significant effects on agricultural productivity and hydrological cycle. For food security and agricultural water resources planning, it is critical to investigate the impact of climate change on changes in agricultural productivity and water consumption. APEX-Paddy model, which is the modified version of APEX (Agricultural Policy/Environmental eXtender) model for paddy ecosystem, was used to evaluate rice productivity and evapotranspiration based on climate change scenario. Two study areas (Gimjae, Icheon) were selected and the input dataset was obtained from the literature. RCP (Representitive Concentration Pathways) based climate change scenarios were provided by KMA (Korean Meteorological Administration). Rice yield data from 1997 to 2015 were used to validate APEX-Paddy model. The effects of climate change were evaluated at a 30-year interval, such as the 1990s (historical, 1976~2005), the 2025s (2011~2040), the 2055s (2041~2070), and the 2085s (2071~2100). Climate change scenarios showed that the overall evapotranspiration in the 2085s reduced from 10.5 % to 16.3 %. The evaporations were reduced from 15.6 % to 21.7 % due to shortend growth period, the transpirations were reduced from 0.0% to 24.2 % due to increased $CO_2$ concentration and shortend growth period. In case of rice yield, in the 2085s were reduced from 6.0% to 25.0 % compared with the ones in the 1990s. The findings of this study would play a significant role as the basics for evaluating the vulnerability of paddy rice productivity and water management plan against climate change.

• Atmosphere
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• v.23 no.4
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• pp.377-387
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• 2013

Projections of changes in the low latitude atmospheric circulation under global warming are investigated using the results of the CMIP5 ensemble mean. For this purpose, 30-yr periods for the present day (1971~2000) and the end of the $21^{st}$ century (2071~2100) according to the RCP emission scenarios are compared. The wintertime subtropical jet is projected to strengthen on the upper side of the jet due to increase in meridional temperature gradient induced by warming in the tropical upper-troposphere and cooling in the stratosphere except for the RCP2.6. It is also found that a strengthening of the upper side of the wintertime subtropical jet in the RCP2.6 due to tropical upper-tropospheric warmings. Model-based projection shows a weakening of the mean intensity of the Hadley cell, an upward shift of cell, and poleward shift of the Hadley circulation for the winter cell in both hemispheres. A weakening of the Walker circulation, which is one of the most robust atmospheric responses to global warming, is also projected. These results are consistent with findings in the previous studies based on CMIP3 data sets. A weakening of the Walker circulation is accompanied with decrease (increase) in precipitation over the Indo-Pacific warm pool region (the equatorial central and east Pacific). In addition, model simulation shows a decrease in precipitation over subtropical regions where the descending branch of the winter Hadley cell in both hemispheres is strengthened.

• Atmosphere
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• v.29 no.4
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• pp.391-401
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• 2019

This study first investigates the changes of the mean and extreme temperatures and precipitation in East Asia (EA) under stabilized 1.5℃ and 2℃ warming conditions above preindustrial levels provided by HAPPI project. Here, five model with 925 members for 10-year historical period (2006~2015) and 1.5/2.0℃ future warming scenarios (2091~2100) have been used and monthly based data have been analyzed. The results show that the spatial distribution fields over EA and domain averaged variables in HAPPI 1.5/2.0℃ hindcast simulations are comparable to observations. It is found that the magnitude of mean temperature warming in EA and Korea is similar to the global mean, but for extreme temperatures local higher warming trend for minimum temperature is significant. In terms of precipitation, most subregion in EA will see more increased precipitation under 1.5/2.0℃ warming compared to the global mean. These attribute for probability density function of analyzed variables to get wider with increasing mean values in 1.5/2.0℃ warming conditions. As the result of vulnerability of 0.5℃ additional warming from 1.5 to 2.0℃, 0.5℃ additional warming contributes to the increases in extreme events and especially the impact over South Korea is slightly larger than EA. Therefore, limiting global warming by 0.5℃ can help avoid the increases in extreme temperature and precipitation events in terms of intensity and frequency.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.3-8
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• 1998

Using GIS and socio-economical data the relationship between human activities and global environmental change Is Analysed from the view point of food productivity and CO2 emission. Under the assumption that the population problem, the food problem and global warming due to energy consumption can be stabilized through managing land use, impacts of human activities such as consumption of food, energy and timber on global environment changes, and global population capacity are Analysed using developed system dynamics model in the research. In the model the world is divided into two groups: OECD countries and the others. Used global land use data set Is land cover map derived from satellite data, and potential distribution of arable land is estimated by the method of Clamor and Solomon which takes into consideration spatial distribution of climate data such as precipitation and evapotranspiration. In addition, impacts of CO2 emission from human activities on food production through global warming are included in the model as a feedback. The results of the analysis for BaU scenario and Toronto Conference scenario are similar to the results of existing models. From the result of this study, the human habitability in 2020 is 8 billion people, and CO2 emission in 2020 based on BaU Scenario and on Toronto Scenario is 1.7 and 1.2 times more than the 1986's respectively. Improving spatial resolution of the model by using global data to distribute the environmental variables and sauce-economical indices is left for further studies.

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.445-458
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• 2021

Gravity Recovery and Climate Experiment (GRACE) gravimeter satellites observed the Earth gravity field with unprecedented accuracy since 2002. After the termination of GRACE mission, GRACE Follow-on (GFO) satellites successively observe global gravity field, but there is missing period between GRACE and GFO about one year. Many previous studies estimated terrestrial water storage (TWS) changes using hydrological models, vertical displacements from global navigation satellite system observations, altimetry, and satellite laser ranging for a continuity of GRACE and GFO data. Recently, in order to predict TWS changes, various machine learning methods are developed such as artificial neural network and multi-linear regression. Previous studies used hydrological and climate data simultaneously as input data of the learning process. Further, they excluded linear trends in input data and GRACE/GFO data because the trend components obtained from GRACE/GFO data were assumed to be the same for other periods. However, hydrological models include high uncertainties, and observational period of GRACE/GFO is not long enough to estimate reliable TWS trends. In this study, we used convolutional neural networks (CNN) method incorporating only climate data set (temperature, evaporation, and precipitation) to predict TWS variations in the missing period of GRACE/GFO. We also make CNN model learn the linear trend of GRACE/GFO data. In most river basins considered in this study, our CNN model successfully predicts seasonal and long-term variations of TWS change.

• Journal of Species Research
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• v.12 no.1
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• pp.109-113
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• 2023

To build a distribution model for Haemadipsa rjukjuana, we collected current occurrences of the species on Heuksando with adjacent islands. Based on current locations and 19 climate variables with DEM (digital elevation model), we built the MaxEnt (maximum entropy) species distribution model for H. rjukjuana in the islands. Then, we applied the MaxEnt model to the mainland of Korea with the current climate condition and topology. In addition to the current distribution scenario, we predicted the future distribution scenarios in Korea by Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models. Shared Socioeconomic Pathway (SSP) 585 of two CMIP6 models(GISS-E2-1 and INM-CM4-8) from 2040 to 2100 were used for the future projection.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.329-334
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• 2001

Many of past studies using physically based numerical climate models indicate that increases in atmospheric $CO_2$could enhance summer dryness over continental region in middle-high latitudes. However the models used in those studies do not take account of permafrost in high latitudes. We have carried out a set of experiments applying a version of global climate model that can reproduce realistic distribution of the permafrost. From the results, it is indicated that permafrost functions as a large reservoir in hydrologic cycle maintaining dry, hot summer over continents in northern middle-high latitudes, and that the $CO_2$warming would reduce this function by causing climatological thawing of permafrost, which would result in moister and cooler summer, and warmer winter in the same region. The present study indicates that an inclusion of very simple description of soil freezing process can make a large difference in a model simulation.

• Water Engineering Research
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• v.5 no.2
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• pp.81-99
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• 2004

Long term streamflow regime under virtual climate change scenario was examined. Rainfall forecast simulation of the Canadian Global Coupled Model (CGCM2) of the Canadian Climate Center for modeling and analysis for the IPCC SRES B2 scenario was used for analysis. The B2 scenario envisions slower population growth (10.4 billion by 2010) with a more rapidly evolving economy and more emphasis on environmental protection. The relatively large scale of GCM hinders the accurate computation of the important streamflow characteristics such as the peak flow rate and lag time, etc. The GCM rainfall with more than 100km scale was downscaled to 2km-scale using the space-time stochastic random cascade model. The HEC-HMS was used for distributed hydrologic model which can take the grid rainfall as input data. The result illustrates that the annual variation of the total runoff and the peak flow can be much greater than rainfall variation, which means actual impact of rainfall variation for the available water resources can be much greater than the extent of the rainfall variation.