• Journal of Forest and Environmental Science
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• v.39 no.1
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• pp.1-12
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• 2023

To understand the health conditions and growth patterns of forest estate for environmental resilience and climate change mitigation, assessment of structure and species diversity is paramount. This study aimed at assessing the structure, alpha, and beta diversities of tree species in three ecological zones in Taraba, Nigeria for management purposes. In recent time, no research has been reported on the structure and beta diversity of the study areas. A systematic sampling design was used for data collection. Five sample plots of 50×50 m were laid in each of the six natural forest areas. The result showed a mean DBH (42.5 cm) and a tree height (15.0 m) from the forests. The forests have a structure of an inverse "J-shape," which is typical of natural forests in the tropics. The southern Guinea savanna zone had the highest mean Shannon-Weiner diversity index (2.8). The least beta diversity index (0.02) was between Baissa and Jen Gininya forest areas. Baissa and Bakin Dutse Protected Forest Areas (PFAs) contained 76.5% of the tree species. There is a high chance of all tree species to be found in these 2 forest areas. Proximity to a location influences how similar two tree species are, according to the least beta diversity index (0.02) recorded. The Federal Government's method of management for the forest, known as Gashaka Gumti National Park, may be responsible for the high beta diversity index in the Montane ecozone. Therefore, it should be strongly encouraged to practice strict oversight of natural areas, as their contributions to reducing climate change in Taraba State, Nigeria, cannot be overstated.

• Journal of Environmental Policy
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• v.9 no.2
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• pp.185-205
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• 2010

Climate change vulnerability assessment based on local conditions is a prerequisite for establishment of climate change adaptation policies. While some studies have developed a methodology for vulnerability assessment at the national level using statistical data, few attempts, whether domestic or overseas, have been made to develop methods for local vulnerability assessments that are easily applicable to a single city. Accordingly, the objective of this study was to develop a conceptual framework for climate change vulnerability, and then develop a general methodology for assessment at the regional level applied to a single coastal city, Mokpo, in Jeolla province, Korea. We followed the conceptual framework of climate change vulnerability proposed by the IPCC (1996) which consists of "climate exposure," "systemic sensitivity," and "systemic adaptive capacity." "Climate exposure" was designated as sea level rises of 1, 2, 3, 4, and 5 meter(s), allowing for a simple scenario for sea level rises. Should more complex forecasts of sea level rises be required later, the methodology developed herein can be easily scaled and transferred to other projects. Mokpo was chosen as a seaside city on the southwest coast of Korea, where all cities have experienced rising sea levels. Mokpo has experienced the largest sea level increases of all, and is a region where abnormal high tide events have become a significant threat; especially subsequent to the construction of an estuary dam and breakwaters. Sensitivity to sea level rises was measured by the percentage of flooded area for each administrative region within Mokpo evaluated via simulations using GIS techniques. Population density, particularly that of senior citizens, was also factored in. Adaptive capacity was considered from both the "hardware" and "software" aspects. "Hardware" adaptive capacity was incorporated by considering the presence (or lack thereof) of breakwaters and seawalls, as well as their height. "Software" adaptive capacity was measured using a survey method. The survey questionnaire included economic status, awareness of climate change impact and adaptation, governance, and policy, and was distributed to 75 governmental officials working for Mokpo. Vulnerability to sea level rises was assessed by subtracting adaptive capacity from the sensitivity index. Application of the methodology to Mokpo indicated vulnerability was high for seven out of 20 administrative districts. The results of our methodology provides significant policy implications for the development of climate change adaptation policy as follows: 1) regions with high priority for climate change adaptation measures can be selected through a correlation diagram between vulnerabilities and records of previous flood damage, and 2) after review of existing short, mid, and long-term plans or projects in high priority areas, appropriate adaptation measures can be taken as per this study. Future studies should focus on expanding analysis of climate change exposure from sea level rises to other adverse climate related events, including heat waves, torrential rain, and drought etc.

• Journal of Climate Change Research
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• v.2 no.2
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• pp.79-91
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• 2011

In order to study interactions between climate change and air quality, a modeling system including the downscaling scheme has been developed in the integrated manner. This research focuses on the development of a downscaling method to utilize CCSM3 outputs as the initial and boundary conditions for the regional climate model, MM5. Horizontal/vertical interpolation was performed to convert from the latitude/longitude and hybrid-vertical coordinate for the CCSM3 model to the Lambert-Conformal Arakawa-B and sigma-vertical coordinate for the MM5 model. A variable diagnosis was made to link between different variables and their units of CCSM and MM5. To evaluate the dynamic downscaling performance of this study, spatial distributions were compared between outputs of CCSM/MM5 and NRA/MM5 and statistic analysis was conducted. Temperature and precipitation patterns of CCSM/MM5 in summer and winter showed a similar pattern with those of observation data in East Asia and the Korean Peninsula. In addition, statistical analysis presented that the agreement index (AI) is more than 0.9 and correlation coefficient about 0.9. Those results indicate that the dynamic downscaling system built in this study can be used for the research of interaction between climate change and air quality.

• Journal of the Korean Wood Science and Technology
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• v.46 no.6
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• pp.627-636
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• 2018

This research was performed to supplement the previous research about the driving rain index (DRI) for Korea determined by using daily weather data for 30 years. The average annual driving rain index (AADRI) was calculated from the hourly weather data, and the magnitude of DRI was investigated according to wind directions. The hourly climate data were obtained from the Korea Meteorological Administration (KMA) for the period 2009 to 2017. Of 82 locations investigated, seven were classified into regions where the level of exposure of walls to rain was high. The result showed quite a difference from the previous results, in which no high exposure regions were observed. Since the hourly-based and the daily-based annual driving rain index (ADRI) values showed only a slight difference, the result may be explained by the length of the periods used in both studies. The change of DRI according to wind directions showed that there was a certain range of wind directions in which driving rain easily approached building walls. It suggests that the consideration of wind directions with high DRI would be useful to develop a good design of wooden buildings from the point of wood preservation and maintenance.

• Atmosphere
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• v.26 no.4
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• pp.687-696
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• 2016

The western North Pacific subtropical high (WNPSH) in boreal summer has interannual and interdecadal variability, which affects East Asian summer monsoon variability. In particular, it is well known that the intensity of WNPSH is reversely related to that of summer monsoon in North East Asia in association with Pacific Japan (PJ)-like pattern. Many coupled climate models weakly simulate this large-scale teleconnection pattern and also exhibit the diverse variability of WNPSH. This study discusses the inter-model differences of WNPSH simulated by different climate models, which participate in the Coupled Model Intercomparison Project phase 5 (CMIP5). In comparing with reanalysis observation, the 29 CMIP5 models could be assorted into two difference groups in terms of interannual variability of WNPSH. This study also discusses the dynamical or thermodynamics factors for the differences of two groups of the CMIP5 climate models. As results, the regressed precipitation in well-simulating group onto the Nino3.4 index ($5^{\circ}N-5^{\circ}S$, $170^{\circ}W-120^{\circ}W$) is stronger than that in poorly-simulating group. We suggest that this difference of two groups of the CMIP5 climate models would have an effect on simulating the interannual variability of WNPSH.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.42-55
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• 2017

Since the phases and patterns of the climate adaptability of vegetation can greatly differ from region to region, an intensive pixel scale approach is required. In this study, Partial Least Squares (PLS) regression on satellite image-based vegetation index is conducted for to assess the effect of climate factors on vegetation productivity and to predict future productivity of forests vegetation in South Korea. The results indicate that the mean temperature of wettest quarter (Bio8), mean temperature of driest quarter (Bio9), and precipitation of driest month (Bio14) showed higher influence on vegetation productivity. The predicted 2050 EVI in future climate change scenario have declined on average, especially in high elevation zone. The results of this study can be used in productivity monitoring of climate-sensitive vegetation and estimation of changes in forest carbon storage under climate change.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.35-45
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• 2011

The purpose of this study is visualizing climate change contents from Weather Research and Forecasting model and providing useful tool to anyone who want to use them for communication and actual movement. As a results, we have built a process and user interface for publishing Arrow KML, BWS KML, and DI KML. Arrow KML provide wind rose service and wind attribute information for each arrow. BWS KML provide a wind power index and DI KML provide a thermal comfort. All KML contents are more reliable because those are visualized from the scientifically verified climate change prediction model. Further study will focus on searching for climate change contents mining and useful contents design for wide range of climate change mitigation/adaptation activity.

• Journal of Korean Society of Rural Planning
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• v.16 no.4
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• pp.109-116
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• 2010

Climate change is known to affect both natural and managed ecosystems, and will likely impact on the terrestrail carbon balance. This paper reports the effects of climate change on spatial-temporal changes in carbon reductions in South Korea's during 2000-2100. Future carbon (C) stock distributions are simulated for the same period using various spatial data sets including land cover, net primary production(NPP) and leaf area index (LAI) obtained from MODIS(Moderate Resolution Imaging Spectroradiometer), and climate data from Data Assimilation Office(DAO) and Korea Meteorological Administration(KMA). This study attempts to predict future NPP using multiple linear regression and to model dependence of soil respiration on soil temperature. Plants store large amounts of carbon during the growing periods. During 2030-2100, Carbon accumulation in vegetation was increased to $566{\sim}610gC/m^2$/year owing to climate change. On the other hand, soil respiration is a key ecosystem process that releases carbon from the soil in the form of carbon dioxide. The estimated soil respiration spatially ranged from $49gC/m^2$/year to $231gC/m^2$/year in the year of 2010, and correlating well with the reference value. This results include Spatial-Temporal C reduction variation caused by climate change. Therefore this results is more comprehensive than previous results. The uncertainty in this study is still large, but it can be reduced if a detailed map becomes available.

• Journal of Korean Society on Water Environment
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• v.30 no.5
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• pp.491-502
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• 2014

As meteorology is the driving force for lake thermodynamics and mixing processes, the effects of climate change on the physical limnology and associated ecosystem are emerging issues. The potential impacts of climate change on the physical features of a reservoir include the heat budget and thermodynamic balance across the air-water interface, formation and stability of the thermal stratification, and the timing of turn over. In addition, the changed physical processes may result in alteration of materials and energy flow because the biogeochemical processes of a stratified waterbody is strongly associated with the thermal stability. In this study, a novel modeling framework that consists of an artificial neural network (ANN), a watershed model (SWAT), a reservoir operation model(HEC-ResSim) and a hydrodynamic and water quality model (CE-QUAL-W2) is developed for projecting the effects of climate change on the reservoir water temperature and thermal stability. The results showed that increasing air temperature will cause higher epilimnion temperatures, earlier and more persistent thermal stratification, and increased thermal stability in the future. The Schmidt stability index used to evaluate the stratification strength showed tendency to increase, implying that the climate change may have considerable impacts on the water quality and ecosystem through changing the vertical mixing characteristics of the reservoir.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5349-5354
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• 2014

Climate change is one of the most important factors increasing a system's vulnerability. Therefore, various methods have been applied to evaluate the vulnerability to develop an appropriate adaptation policy to minimize the effects of climate change. On the other hand, it has barely been used to examine the suitability of the selected proxy variables to calculate the vulnerability. In this study, it was shown that the degree of disaster and safety education should be considered as one of the proxy variables in non-structural measures when the vulnerability is calculated using an expert survey. As a result, the degree of the contribution on the climate change vulnerability can be different according to the education target and the characteristics of various systems. The results might be useful for developing a climate change adaptation policy in a specific area.