• Journal of Climate Change Research
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• v.7 no.3
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• 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.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.317-331
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• 2011

The CERES-Barley crop simulation model of DSSAT package was used to assess the impacts of climate change on potential yield of winter covered barley in Korea. 56 sites over the southern part of Korean peninsula were selected to compare the climate change impacts in various climatic conditions. The climatological normals (1971~2000) and the three future climatological normals (2011~2040, 2041~2070, and 2071~2100), based on A1B climate change scenarios of Korea, were used in this study, and the three future climatological normals were simulated under three environmental conditions, where only temperature change, only carbon dioxide change, and both of temperature and carbon dioxide change with future A1B climate change scenarios, respectively. Results: The CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter covered barley, because of the agreement between observed and simulated outcomes (e.g., the coefficient of determination of grain yield equals 0.84). (1) The only increased temperature effect with the climate change scenarios was mostly negative to the potential yield of winter covered barley and its magnitude ranges from -21% to +1% for the three future normals. (2) The effect of the only elevated carbon dioxide on the potential yield of winter covered barley was positive and its magnitude ranged from 12% to 43% for the three future normals. (3) For increased temperature and elevated carbon dioxide change cases, potential yields increased by 13%, 21%, 19% increase for the 2011~2040, 2041~2070, 2071~2100 normals, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.61-75
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• 2021

This study aims to assess the changes in crop water requirement of paddy and upland according to future climate and land use changes scenarios. Changes in the spatiotemporal distribution of temperature and precipitation are factors that lower the stability of agricultural water supply, and predicting the changes in crop water requirement in consideration of climate change can prevent the waste of limited water resources. Meanwhile, due to the recent changes in the agricultural product consumption structure, the area of paddy and upland has been changing, and it is necessary to consider future land use changes in establishing an appropriate water use plan. Climate change scenarios were derived from the four GCMs of the CMIP6, and climate data were extracted under two future scenarios, namely SSP1-2.6 and SSP5-8.5. Future land use changes were predicted using the FLUS (Future Land Use Simulation) model. Crop water requirement in paddy was calculated as the sum of evapotranspiration and infiltration based on the water balance in a paddy field, and crop water requirement in upland was estimated as the evapotranspiration value by applying Penman-Monteith method. It was found that the crop water requirement for both paddy and upland increased as we go to the far future, and the degree of increase and variability by time showed different results for each GCM. The results derived from this study can be used as basic data to develop sustainable water resource management techniques considering future watershed environmental changes.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.138-142
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• 2005

The change of precipitation and temperature due to the global. warming eventually caused the variation of water availability in terms of potential evapotranspiration, soil moisture, and runoff. In this reason national long-term water resource planning should be considered the effect of climate change. Study of AOGCM-based scenario to proposed the plausible future states of the climate system has become increasingly important for hydrological impact assessment. Future climate changes over East Asia are projected from the coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios using multi-model ensembles (MMEs) method (Min et al. 2004). MME method is used to reduce the uncertainty of individual models. However, the uncertainty increases are larger over the small area than the large area. It is demonstrated that the temperature increases is larger over continental area than oceanic area in the 21st century.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.6
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• pp.110-119
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• 2007

This study's objects are to predict distribution and to assess vulnerability of sub-alpine vegetations in the Korean peninsula for climate change using various climate models. This study validates relationship between sub-alpine vegetations and environmental factors using Pearson correlation analysis. Then, the future distribution of sub-alpine vegetations are predicted by a logistic regression. The major findings in this study are; First, spring mean temperature (March-May), total precipitation, elevation and warmth index are highly influencing factors to the distribution of sub-alpine vegetations. Second, the sub-alpine vegetations will be disappeared in South Korea and concentrated around Baekdu Mountain in North Korea. North Korea is predicted to have serious impact of climate change because temperature will be increased higher than in South Korea. The study findings concluded that the assessment of the future vulnerability of sub-alpine vegetations to climate change are significant.

• KCID journal
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• v.21 no.1
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• pp.64-77
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• 2014

This study evaluated the soil loss considering the R-Factor value following the climate change. To calculate the soil loss of the basin in Jaun-ri, Hongcheon-gun which is the study area, the future climate change scenario and convenience revision were used to build the past 30 years, future 30 years R-Factor and it was applied to USLE model. As a result, as the R-Factor value declined a little in the future, the soil loss was also reduced but it corresponds to the 'very high' according to the OECD soil loss grade so the solution to reduce the soil loss is necessary and it can be used for another study material.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.740-741
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• 2015

the downscaled air temperature data over study region for the projected 2001 - 2099 period were then ensemble averaged, and the ensemble averages of 6 realizations were compared against the corresponding historical downscaled data for the 1961 - 2000 period in order to assess the impact of climate change on air temperature over study region by graphical, spatial and statistical methods. In order to evaluate the seasonal trends under future climate change conditions, the simulated annual, annual DJF (December-January-February), and annual JJA (June-July-August) mean air temperature for 5 watersheds during historical and future periods were evaluated. From the results, it is clear that there is a rising trend in the projected air temperature and future air temperature would be warmer by about 3 degrees Celsius toward the end of 21^st century if the ensemble projections of air temperature become true. Spatial comparison of 30-year average annual mean air temperature between historical period (1970 - 1999) and ensemble average of 6-realization shows that air temperature is warmer toward end of 21^st century compared to historical period.

• Asian Journal of Business Environment
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• v.11 no.4
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• pp.39-45
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• 2021

Purpose: This study is designed to investigate the extent and nature of climate change disclosure of listed pharmaceutical companies of Bangladesh. Research design, data and methodology: In order to perform this research, a content analysis methodology is used. A climate change disclosure index is constructed to examine 12 different climate change disclosure issues. Information is collected from the annual reports of 29 pharmaceutical companies listed on the Dhaka Stock Exchange for the year 2019. Results: This study finds that only 48.28% of the sample companies provided disclosure on at least one issue regarding climate change. 'Energy savings' is the mostly disclosed issue whereas 'Pollution control expenditure', 'Biodiversity conservation initiatives' are the least disclosed issues. Research implication: This study concludes 64.29% of the companies examined, use less than five sentences for climate change disclosure, which depicts unsatisfactory disclosure practices regarding climate change issues. Study findings would be helpful for different industries of Bangladesh to implement efficient climate change reporting Practice. Future studies can be conducted on other industries to obtain more comprehensive result.