• Journal of the Korean Geographical Society
• /
• v.51 no.2
• /
• pp.201-217
• /
• 2016

We accessed the climate change effects on the distributions of warm-evergreen broad-leaved trees (shorten to warm-evergreens below) in the Korean Peninsula (KP). For this, we first selected nine warm-evergreens with the northern distribution limits at mid-coastal areas of KP and climate variables, coldest month mean temperature and coldest quarter precipitation, known to be important for warm-evergreens growth and survival. Next, species distribution models (SDMs) were constructed with generalized additive model (GAM) algorithm for each warm-evergreen. SDMs projected the potential geographical distributions of warm evergreens under current and future climate conditions in associations with land uses. The nine species were categorized into three groups (mid-coastal, southwest-coastal, and southeast-inland) based on their current spatial patterns. The effects of climate change and land uses on the distributions depend on the current spatial patterns. As considering land uses, the potential current habitats of all warm-evergreens decrease over 60%, showing the highest reduction rate for the Kyungsang-inland group. SDMs forecasted the expansion of potential habitats for all warm-evergreens under climate changes projected for 2050 and 2070. However, the expansion patterns were different among three groups. The spatial patterns of projected coldest quarter precipitation in 2050 and 2070 could account for such differences.

• Journal of Climate Change Research
• /
• v.4 no.1
• /
• pp.11-26
• /
• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• Atmosphere
• /
• v.32 no.2
• /
• pp.87-101
• /
• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• ALGAE
• /
• v.31 no.1
• /
• pp.49-59
• /
• 2016

Ulva pertusa, a common bloom-forming green alga, was used as a model system to examine the effects of elevated carbon dioxide (CO₂) and temperature on growth and photosynthetic performance. To do this, U. pertusa was grown under four temperature and CO₂ conditions; ambient CO₂ (400 μatm) and temperature (16℃) (i.e., present), elevated temperature only (19℃) (ET; i.e., warming), elevated CO₂ only (1,000 μatm) (EC; i.e., acidification), and elevated temperature and CO₂ (ET and EC; i.e., greenhouse), and its steady state photosynthetic performance evaluated. Maximum gross photosynthetic rates (GP_max) were highest under EC conditions and lowest under ET conditions. Further, ET conditions resulted in decreased rate of dark respiration (R_d), but growth of U. pertusa was higher under ET conditions than under ambient temperature conditions. In order to evaluate external carbonic anhydrase (eCA) activity, photosynthesis was measured at 70 μmol photons m⁻² s⁻¹ in the presence or absence of the eCA inhibitor acetazolamide (AZ), which inhibited photosynthetic rates in all treatments, indicating eCA activity. However, while AZ reduced U. pertusa photosynthesis in all treatments, this reduction was lower under ambient CO₂ conditions (both present and warming) compared to EC conditions (both acidification and greenhouse). Moreover, Chlorophyll a and glucose contents in U. pertusa tissues declined under ET conditions (both warming and greenhouse) in conjunction with reduced GP_max and R_d. Overall, our results indicate that the interaction of EC and ET would offset each other’s impacts on photosynthesis and biochemical composition as related to carbon balance of U. pertusa.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.21 no.1
• /
• pp.103-118
• /
• 2018

Ecosystems in subalpine regions are recognized as areas vulnerable to climatic changes because rainfall and the possibility of flora migration are very low due to the characteristics of topography in the regions. In this context, habitat niche was formulated for representative species of arbors in subalpine regions in order to understand the effects of climatic changes on alpine arbor ecosystems. The current potential habitats were modeled as future change areas according to the climatic change scenarios. Based on the growth conditions and environmental characteristics of the habitats, the study was conducted to identify direct and indirect causes affecting the habitat reduction of Abies nephrolepis. Diverse model algorithms for explanation of the relationship between the emergence of biological species and habitat environments were reviewed to construct the environmental data suitable for the six models(GLM, GAM, RF, MaxEnt, ANN, and SVM). Weights determined through TSS were applied to the six models for ensemble in an attempt to minimize the uncertainty of the models. Based on the current climate determined by averaging the climates over the past 30years(1981~2010) and the HadGEM-RA model was applied to fabricate bioclimatic variables for scenarios RCP 4.5 and 8.5 on the near and far future. The results of models of the alpine region tree species studied were put together and evaluated and the results indicated that a total of eight national parks such as Mt. Seorak, Odaesan, and Hallasan would be mainly affected by climatic changes. Changes in the Baekdudaegan reserves were analyzed and in the results, A. nephrolepis was predicted to be affected the most in the RCP8.5. The results of analysis as such are expected to be finally utilizable in the survey of biological species in the Korean peninsula, restoration and conservation strategies considering climatic changes as the analysis identified the degrees of impacts of climatic changes on subalpine region trees in Korean peninsula with very high conservation values.

• Journal of Korea Water Resources Association
• /
• v.57 no.1
• /
• pp.45-58
• /
• 2024

Drought risk is expected to increase as the frequency, intensity, and duration of droughts increase due to climate change. Drought risk is related to not only hydro-meteorological factors, but also water supply and demand. Recently, along with climate change, socioeconomic factors have also been recognized to increase drought risk. Therefore, it is necessary to outlook the drought risk considering various conditions for coping with future extreme droughts in a timely manner. In addition, considering various drought scenarios help reduce the uncertainty in future drought outlook. In this study, drought scenarios considering climate change scenarios, population, and water demand were created to outlook drought risk for 160 administrative districts in Korea, then new levels of drought risk were assigned based on the results of drought risk outlook to suggest drought management measures. The results showed that the drought risk will increase in the future in 2020, 2025, and 2030, compared to past. Especially the drought risk is likely twice as high in 2030 under the baseline and high scenarios. Applying the drought outlook results from this study to the new methodology for setting the risk levels shows that most regions are in Response (V) in 2020 and 2030 for baseline and high scenarios.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.700-706
• /
• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• Journal of Korean Society of Disaster and Security
• /
• v.16 no.1
• /
• pp.37-48
• /
• 2023

The possibility of a super-large disaster is increasing due to changes in national territory, urban space and social environment, extreme weather conditions due to climate change, and paralysis of national infrastructure due to natural disasters. In this study, in order to support the systematic establishment of national territorial disaster prevention strategies for future disasters, alternatives to intelligent national territorial disaster prevention policies for future disasters were considered. Changes in the national environment related to future disasters, domestic and foreign prior studies and policy trends related to national disaster prevention, and studies related to the national disaster management system were investigated, and institutional and technical policy alternatives were derived. As a policy alternative, it was suggested that the creation of a self-adapting national territory for future disasters should be systematized and continuously supported through a technically intelligent decision-making support system.

• Journal of Climate Change Research
• /
• v.1 no.1
• /
• pp.31-50
• /
• 2010

The Arctic climate change for the Last Glacial Maximum(LGM) occurred at 21,000 years ago (21ka) was investigated using simulation results of atmosphere-ocean coupled models from the second phase of the Paleoclimate Modelling Intercomparison Program(PMIP2). In the analysis, we used seven models, the NCAR CCSM of USA, ECHAM3-MPIOM of German Max-Planxk Institute, HadCM3M2 of UK Met Office, IPSL-CM4 of France Laplace Institute, CNRM-CM3 of France Meteorological Institute, MIROC3.2 of Japan CCSR at University of Tokyo, and FGOALS of China Institute of Atmospheric Physics. All the seven models reproduces the Arctic climate features found in the present climate at 0ka(pre-industrial time) in a reasonable degree in comparison to observations. During the LGM, the atmospheric $CO_2$ concentration and other greenhouse gases were reduced, the ice sheets were expanded over North America and northern Europe, the sea level was lowered by about 120m, and orbital parameters were slightly different. These boundary conditions were implemented to simulated LGM climate. With the implemented LGM conditions, the biggest temperature reduction by more than $24^{\circ}C$ is found over North America and northern Europe owing to ice albedo feedback and the change in lapse rate by high elevation. Besides, the expansion of ice sheets leads to the marked temperature reduction by more then $10^{\circ}C$ over the Arctic Ocean. The temperature reduction in northern winter is larger than in summer around the Arctic and the annual mean temperature is reduced by about $14^{\circ}C$. Compared to low mid-latitudes, the temperature reduction is much larger in high northern altitudes in the LGM. This results mirror the larger warming around the Artic in recent century. We could draw some information for the future under global warming from the knowledge of the LGM.

• Journal of Forest and Environmental Science
• /
• v.33 no.2
• /
• pp.122-129
• /
• 2017

Understanding how future climate conditions will be impact on the biodiversity and species composition is important, because biodiversity becomes more important in environment assessment. To understand the biological changes including diversity and species composition over time (temporal variation within a year), the species diversity and composition of ground beetles were investigated in two well-preserved areas in the Sobaeksan National Park using pitfall traps. In addition, relationships between ground beetles and environmental variables were studied by considering temporal variation. We collected 2,146 ground beetle specimens representing 45 species, and individual-based rarefaction curves indicated that similar species richness was found between Geumseon Valley (GV) and Namcheon Valley (NV). The Bray-Curtis matrix comparisons between study sites were characterized by similar ground beetles sample heterogeneity, while temporal variations in abundance, species richness, and ${\beta}-diversity$ of ground beetles showed rather difference over time according to location of study sites. In GV site, minimum temperature was selected as the best predictor for abundance, species richness, and ${\beta}-diversity$ of ground beetles, while those relationships in NV site were more complicated. In conclusion, our study suggests that understanding the different response of ground beetles to climatic variables related to local habitat conditions is important to predict the effect of climate change on biological communities.