• Atmosphere
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• v.32 no.1
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• pp.1-15
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• 2022

Recently, Japan's Meteorological Research Institute presented the d4PDF database (Database for Policy Decision-Making for Future Climate Change, d4PDF) through large-scale climate ensemble simulations to overcome uncertainty arising from variability when the general circulation model represents extreme-scale precipitation. In this study, the change of precipitation characteristics between the historical and future climate conditions in the Yongdam-dam basin was analyzed using the d4PDF data. The result shows that annual mean precipitation and seasonal mean precipitation increased by more than 10% in future climate conditions. This study also performed an analysis on the change of the return period rainfall. The annual maximum daily rainfall was extracted for each climatic condition, and the rainfall with each return period was estimated. In this process, we represent the extreme-scale rainfall corresponding to a very long return period without any statistical model and method as the d4PDF provides rainfall data during 3,000 years for historical climate conditions and during 5,400 years for future climate conditions. The rainfall with a 50-year return period under future climate conditions exceeded the rainfall with a 100-year return period under historical climate conditions. Consequently, in future climate conditions, the magnitude of rainfall increased at the same return period and, the return period decreased at the same magnitude of rainfall. In this study, by using the d4PDF data, it was possible to analyze the change in extreme magnitude of rainfall.

• 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 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.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.48-48
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• 2023

The intensified droughts under climate change are expected to threaten stable water resource availability. Droughts exceeding the magnitude of historical variability could occur increasingly frequently under future climate conditions. It is crucial to understand how drought will evolve over time because the assumption of hydrological stationarity of the past decades would be inappropriate for future water resources management. However, the timing of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and with existing water resources management and estimate the timing of the first emergence of unprecedented regional drought conditions that persist for over several consecutive years. This new metric enables a new quantification of the urgency of adaptation and mitigation with regard to drought under climate change. The times are detected for several sub-continental-scale regions, and three regions, namely, southwestern South America, Mediterranean Europe, and northern Africa, exhibit particularly robust and earlier critical times under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood, regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. Nevertheless, appropriate and prior adaptation measures are considered indispensable to when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

• 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.

• 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 Environmental Restoration Technology
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• v.19 no.6
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• pp.19-30
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• 2016

The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.296-304
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• 2018

The objective of this study was to analyze the impact of climate change on rice yield and quality. Experiments were conducted using SPAR(Soil-Plant-Atmosphere-Research) chambers, which was designed to create virtual future climate conditions, in the National Institute of Crop Science, Jeonju, Korea, in 2016. In the future climate conditions($+2.8^{\circ}C$ temp, 580 ppm $CO_2$) of year 2051~2060 according to RCP 8.5 scenario, elevated temperature and $CO_2$ accelerated the heading date by about five days than the present climate conditions, resulted in a high temperature environment during grain filling stage. Rice yield decreased sharply in the future climate conditions due to the high temperature induced poor ripening. And the spikelet numbers, ripening ratio, and 1000-grain weight of brown rice were significantly decreased compared to control. The rice grain quality was also decreased sharply, especially due to the increased immature grains. In the future climate conditions, expression of starch biosynthesis-related genes such as granule-bound starch synthase(GBSSI, GBSSII, SSIIa, SSIIb, SSIIIa), starch branching enzyme(BEIIb) and ADP-glucose pyrophosphorylase(AGPS1, AGPS2, AGPL2) were repressed in developing seeds, whereas starch degradation related genes such as ${\alpha}-amylase$(Amy1C, Amy3D, Amy3E) were induced. These results suggest that the reduction in yield and quality of rice in the future climate conditions is likely caused mainly by the poor grain filling by high temperature. Therefore, it is suggested to develop tolerant cultivars to high temperature during grain filling period and a new cropping system in order to ensure a high quality of rice in the future climate conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.229-229
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• 2015

Downscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods in order to assess whether each method can model the climate conditions at various spatial scales properly. This study introduces a fundamental research from Jang and Kavvas(2015) that precipitation variability from a popular statistical downscaling method (BCSD) and a dynamical downscaling method (MM5) that is based on the NCAR/NCEP reanalysis data for a historical period and on the CCSM3 GCM A1B emission scenario simulations for a projection period, is investigated by means of some spatial characteristics: a) the normalized standard deviation (NSD), and b) the precipitation change over Northern California region. From the results of this study it is found that the BCSD method has limitations in projecting future precipitation values since the BCSD-projected precipitation, being based on the interpolated change factors from GCM projected precipitation, does not consider the interactions between GCM outputs and local geomorphological characteristics such as orographic effects and land use/cover patterns. As such, it is not clear whether the popular BCSD method is suitable for the assessment of the impact of future climate change at regional, watershed and local scales as the future climate will evolve in time and space as a nonlinear system with land-atmosphere feedbacks. However, it is noted that in this study only the BCSD procedure for the statistical downscaling method has been investigated, and the results by other statistical downscaling methods might be different.