• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.261-272
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• 2012

In this study, climate variability was predicted by the Weather Research and Forecasting (WRF) model under two different scenarios (current trends scenario; SC1 and managed scenario; SC2) for future urban growth over the Seoul metropolitan area (SMA). We used the urban growth model, SLEUTH (Slope, Land-use, Excluded, Urban, Transportation, Hill-Shade) to predict the future urban growth in SMA. As a result, the difference of urban ratio between two scenarios was the maximum up to 2.2% during 50 years (2000~2050). Also, the results of SLEUTH like this were adjusted in the Weather Research and Forecasting (WRF) model to analysis the difference of the future climate for the future urbanization effect. By scenarios of urban growth, we knew that the significant differences of surface temperature with a maximum of about 4 K and PBL height with a maximum of about 200 m appeared locally in newly urbanized area. However, wind speeds are not sensitive for the future urban growth in SMA. These results show that we need to consider the future land-use changes or future urban extension in the study for the prediction of future climate changes.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.59-68
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• 2014

Climate change influences multiple environmental aspects, certain of which are specifically related to agricultural water resources such as water supply, water management, droughts and floods. Understanding the impact of climate change on reservoirs in relation to the passage of time is an important component of water resource management for stable water supply maintenance. Changes on rainfall and hydrologic patterns due to climate change can increases the occurrence of reservoir water shortage and affect the future availability of agricultural water resources. It is a main concern for sustainable development in agricultural water resources management to evaluate adaptation capability of water supply under the future climate conditions. The purpose of this study is to predict the sustainability of agricultural water demand and supply under future climate change by applying an irrigation vulnerability assessment model to investigate evidence of climate change occurrences at a local scale with respect to potential water supply capacity and irrigation water requirement. Thus, it is a recommended practice in the development of water supply management strategies on reservoir operation under climate change.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.2
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• pp.11-23
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• 2014

The impact and adaption on agricultural water resources considering climate change is significant for reservoirs. The change in rainfall patterns and hydrologic factors due to climate change increases the uncertainty of agricultural water supply and demand. The quantitative evaluation method of uncertainty based on agricultural water resource management under future climate conditions is a major concern. Therefore, it is necessary to improve the vulnerability management technique for agricultural water supply based on a probabilistic and stochastic risk evaluation theory. The objective of this study was to analyse the uncertainty of water resources under future climate change using probability distribution function of water supply in agricultural reservoir and demand in irrigation district. The uncertainty of future water resources in agricultural reservoirs was estimated using the time-specific analysis of histograms and probability distributions parameter, for example the location and the scale parameter. According to the uncertainty analysis, the future agricultural water supply and demand in reservoir tends to increase the uncertainty by the low consistency of the results. Thus, it is recommended to prepare a resonable decision making on water supply strategies in terms of using climate change scenarios that reflect different future development conditions.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.6
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• pp.27-37
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• 2010

The effect of potential future climate change on the storage rate of paddy field during storm periods (June - September) was assessed using the daily paddy water balance model. The CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year 2020s, 2050s and 2080s was downscaled by Change Factor method through bias-correction using 30 years weather data. The future (2020s, 2050s and 2080s) rainfall, storage and irrigation of paddy field, runoff in paddy levee and ponding depth were analyzed for the A2 and B2 climate change scenarios based on a base year (2005). The future irrigation change of paddy field was projected to increase by decrease in rainfall. So, runoff change in paddy levee was decrease slightly, future storage change of paddy was projected to increase.

• 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 Society of Agricultural Engineers
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• v.63 no.6
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• pp.1-16
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• 2021

Global warming due to climate change is expected to significantly affect the hydrological cycle of agriculture. Therefore, in order to predict the magnitude of climate impact on agricultural water resources in the future, it is necessary to estimate the water demand for irrigation as the climate change. This study aimed at evaluating the future changes in water demand for irrigation under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) scenarios for paddy rice in Gimje, South Korea. The APEX-Paddy model developed for the simulation of paddy environment was used. The model was calibrated and validated using the H₂O flux observation data by the eddy covariance system installed at the field. Sixteen General Circulation Models (GCMs) collected from the Climate Model Intercomparison Project phase 6 (CMIP6) and downscaled using Simple Quantile Mapping (SQM) were used. The future climate data obtained were subjected to APEX-Paddy model simulation to evaluate the future water demand for irrigation at the paddy field. Changes in water demand for irrigation were evaluated for Near-future-NF (2011-2040), Mid-future-MF (2041-2070), and Far-future-FF (2071-2100) by comparing with historical data (1981-2010). The result revealed that, water demand for irrigation would increase by 2.3%, 4.8%, and 7.5% for NF, MF and FF respectively under SSP2-4.5 as compared to the historical demand. Under SSP5-8.5, the water demand for irrigation will worsen by 1.6%, 5.7%, 9.7%, for NF, MF and FF respectively. The increasing water demand for irrigating paddy field into the future is due to increasing evapotranspiration resulting from rising daily mean temperatures and solar radiation under the changing climate.

• Atmosphere
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• v.34 no.1
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.267-275
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• 2013

This study projected the future ocean wave climate changes based on global climate change scenario using the coupled climate model HadGEM2-AO according to the emission scenarios and using regional wave model. Annual mean significant wave height (SWH) is linked closely to annual mean wind speed during the forthcoming 21st Century. Because annual mean speed decreased in the western North Pacific, annual mean SWH is projected to decrease in the future. The annual mean SWH decreases for the last 30 years of the 21st century relative to the period 1971-2000 are 2~7% for RCP4.5 and 4~11% for RCP8.5, respectively. Also, extreme SWH and wind speed are projected to decrease in the future. In terms of seasonal mean, winter extreme SWH shows similar trend with annual extreme SWH; however, that of summer shows large increasing tendency compared with current climate in the western North Pacific. Therefore, typhoon intensity in the future might be more severe in the future climate.

• 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 Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.