• Journal of Integrative Natural Science
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• v.17 no.1
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• pp.1-12
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• 2024

Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.12-18
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• 2024

The accelerated pace of climate crisis due to continuous industrialization and greenhouse gas emissions necessitates sustainable solutions that simultaneously address mitigation and adaptation to climate change. Naturebased Solutions (NbS) have gained prominence as viable approaches, with Green Infrastructure being a representative NbS. Green Infrastructure involves securing green spaces within urban areas, providing diverse climate adaptation functions such as removal of various air pollutants, carbon sequestration, and isolation. The proliferation of Green Infrastructure is influenced by the quantification of improvement effects related to various projects. To support decision-making by assessing the climate vulnerability of Green Infrastructure, the U.S. Department of Agriculture (USDA) has developed i-Tree Tools. This study proposes a comprehensive evaluation approach for climate change adaptation types by quantifying the climate adaptation performance of urban Green Infrastructure. Using i-Tree Canopy, the analysis focuses on five urban green spaces covering more than 30 hectares, considering the tree ratio relative to the total area. The evaluation encompasses aspects of thermal environment, aquatic environment, and atmospheric environment to assess the overall eco-friendliness in terms of climate change adaptation. The results indicate that an increase in the tree ratio correlates with improved eco-friendliness in terms of thermal, aquatic, and atmospheric environments. In particular, it is necessary to prioritize consideration of the water environment sector in order to realize climate change adaptive green infrastructure, such as increasing green space in urban areas, as it has been confirmed that four out of five target sites are specialized in improving the water environment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.11-22
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• 2010

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.241-263
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• 2010

KoFlux is a Korean network of micrometeorological tower sites that use eddy covariance methods to monitor the cycles of energy, water, and carbon dioxide between the atmosphere and the key terrestrial ecosystems in Korea. KoFlux embraces the mission of AsiaFlux, i.e. to bring Asia's key ecosystems under observation to ensure quality and sustainability of life on earth. The main purposes of KoFlux are to provide (1) an infrastructure to monitor, compile, archive and distribute data for the science community and (2) a forum and short courses for the application and distribution of knowledge and data between scientists including practitioners. The KoFlux community pursues the vision of AsiaFlux, i.e., "thinking community, learning frontiers" by creating information and knowledge of ecosystem science on carbon, water and energy exchanges in key terrestrial ecosystems in Asia, by promoting multidisciplinary cooperations and integration of scientific researches and practices, and by providing the local communities with sustainable ecosystem services. Currently, KoFlux has seven sites in key terrestrial ecosystems (i.e., five sites in Korea and two sites in the Arctic and Antarctic). KoFlux has systemized a standardized data processing based on scrutiny of the data observed from these ecosystems and synthesized the processed data for constructing database for further uses with open access. Through publications, workshops, and training courses on a regular basis, KoFlux has provided an agora for building networks, exchanging information among flux measurement and modelling experts, and educating scientists in flux measurement and data analysis. Despite such persistent initiatives, the collaborative networking is still limited within the KoFlux community. In order to break the walls between different disciplines and boost up partnership and ownership of the network, KoFlux will be housed in the National Center for Agro-Meteorology (NCAM) at Seoul National University in 2011 and provide several core services of NCAM. Such concerted efforts will facilitate the augmentation of the current monitoring network, the education of the next-generation scientists, and the provision of sustainable ecosystem services to our society.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.351-360
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• 2018

This study was conducted to analyze the responses of chlorophyll contents and growth of Pinus densiflora and Quercus variabilis seedlings on distance from the well and $CO_2$ flux after the artificial $CO_2$ release. From June 1 to 30, 2016, $CO_2$ gas was injected at the rate of $6L\;min^{-1}$ at the study site in Eumseong. Chlorophyll content was analyzed in the middle of July, 2016, and root collar diameter (RCD), height (H), and biomass were measured in May and December, 2016 after planting 2-year-old P. densiflora and 1-year-old Q. variabilis seedlings in May, 2015. The chlorophyll content of P. densiflora seedlings did not show a significant correlation with $CO_2$ flux, whereas the chlorophyll content of Q. variabilis seedlings showed a significant negative correlation with increasing $CO_2$ flux (P<0.05). The RCD and H growth rates of both species showed the significant difference in the distance from the well of the $CO_2$ anthropogenic release treatment. In particular, the RCD and H growth rate of P. densiflora seedlings and the RCD growth rate of Q. variabilis seedlings increased significantly as the seedlings were closer to the well, but the H growth rate of Q. variabilis seedlings decreased significantly. In addition, as the $CO_2$ concentration in the ground increases, ${\Delta}R/S$ ratio increases in both species, suggesting that the high $CO_2$ concentration in the soil promotes carbon distribution relative to the root part. The results of this study can be used as data necessary to monitor the $CO_2$ leakage and physiological and growth responses of both species to leakage of stored $CO_2$ in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.346-358
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• 2023

Due to the acceleration of climate change or global warming, it is important to predict rice productivity in the future and investigate physiological changes in rice plants. The research aimed to explore how rice adapts to climate change by examining the response of nitrogen absorption and nitrogen use efficiency in rice under elevated levels of carbon dioxide and temperature, utilizing the SPAR system for analysis. The temperature increased by +4.7 ℃ in comparison to the period from 2001 to 2010, while the carbon dioxide concentration was held steady at 800 ppm, aligning with South Korea's late 21st-century RCP8.5 scenario. Nitrogen was applied as fertilizer at rates of 0, 9, and 18 kg 10a^-1, respectively. Under conditions of climate change, there was an 81% increase in the number of panicles compared to the present situation. However, grain weight decreased by 38% as a result of reduction in the grain filling rate. BNUE, indicative of the nitrogen use efficiency in plant biomass, exhibited a high value under climate change conditions. However, both NUEg and ANUE, associated with grain production, experienced a notable and significant decrease. In comparison to the current conditions, nitrogen uptake in leaves and stems increased by 100% and 151%, respectively. However, there was a 25% decrease in nitrogen uptake in the panicle. Likewise, the nitrogen content and NDFF (Nitrogen Derived from Fertilizer) in the sink organs, namely leaves and roots, were elevated in comparison to current levels. Therefore, it is imperative to ensure resources by mitigating the decrease in ripening rates under climate change conditions. Moreover, there seems to be a requirement for follow-up research to enhance the flow of photosynthetic products under climate change conditions.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.1-30
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• 2024

The international community adopts the SSP (Shared Socioeconomic Pathways) scenario as a new greenhouse gas emission pathway. As part of efforts to reflect these international trends and support for climate change adaptation measure in the agricultural sector, the National Institute of Agricultural Sciences (NAS) produced high-resolution (1 km) climate change scenarios for the Korean Peninsula based on SSP scenarios, certified as a "National Climate Change Standard Scenario" in 2022. This paper introduces SSP climate change scenario of the NAS and shows the results of the climate change projections. In order to produce future climate change scenarios, global climate data produced from 18 GCM models participating in CMIP6 were collected for the past (1985-2014) and future (2015-2100) periods, and were statistically downscaled for the Korean Peninsula using the digital climate maps with 1km resolution and the SQM method. In the end of the 21^st century (2071-2100), the average annual maximum/minimum temperature of the Korean Peninsula is projected to increase by 2.6~6.1℃/2.5~6.3℃ and annual precipitation by 21.5~38.7% depending on scenarios. The increases in temperature and precipitation under the low-carbon scenario were smaller than those under high-carbon scenario. It is projected that the average wind speed and solar radiation over the analysis region will not change significantly in the end of the 21st century compared to the present. This data is expected to contribute to understanding future uncertainties due to climate change and contributing to rational decision-making for climate change adaptation.

• Korean Journal of Environment and Ecology
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• v.30 no.6
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• pp.1022-1031
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• 2016

Relationships of standing biomass with biodiversity and structural diversity were examined in the Quercus mongolica-dominated forest in Mt. Jeombong, Gangwon-do. We examined the standing biomass of the Q. mongolia community ($311.1ton{\cdot}ha^{-1}$) from 2004 to 2013, and the observed major species were Q. mongoilca, Carpinus cordata, Tilia amurensis whose standing biomasses were $206.3ton{\cdot}ha^{-1}$ (66.3%), $36.9ton{\cdot}ha^{-1}$ (11.9%), and $30.6ton{\cdot}ha^{-1}$ (9.8%), respectively. Although the number of Q. mongolica individuals was very small compared with total density, the reason that Q. mongolica showed the most biomass than other species is due to greater average diameter at breast height (DBH) and the higher number of $DBH{\geq}50cm$ individuals. We calculated the range of Shannon index (H') and Shannon evenness (J') in the Q. mongolica community, and they were gradually increased in time, showing 2.015~2.166, 0.673~0.736, respectively. Their H' and J' showed positive linear relationships with their standing biomass. This indicates that the spatial distribution of the standing biomass in Q. mongoilca community becomes more homogeneous with time and this homogenization appears in various species in the community. In addition, we estimated biomass-species index (BS) and abundance-biomass-speciesdiversity (ABS) and they also showed gradual increase in time, ranging from 3.746 to 3.811 and from 4.781 to 5.028, respectively. Their indices showed positive linear relationships with the standing biomass. This can be explained from the observations of variations in standing biomass with tree diameters as the differences in the average standing biomass in the community have reduced gradually in time. Moreover, it is expected that increase in the structure diversity of the Q. mongoilca community enhances the efficiency in carbon sequestration and productivity, so the community can be developed to a more sustainable ecosystem with more abundant resources. Thus, applications of uneven-aged plantations with considerations of local ecological properties can be a very efficient reforestation method to ensure stable support of biodiversity and productivity.

• The Korean Journal of Ecology
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• v.22 no.3
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• pp.145-153
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• 1999

Authors report the changes of the community structure and secondary succession after fire in Mt. Samma (333 m). Approximately six ha of the red pine (Pinus densiflora) forest and its floor vegetation were burned and cutted down. The vegetation and soil properties were investigated in the burned and unburned sites from April to October, 1998. The dominant species based on SDR₃ in the burned site were Lespedeza cyrtobotrya (96.87), Quercus serrata (77.90), Cyperus amuricus (46.22) and Miscanthus sinensis var. purpurascens (38.33), whereas the dominant species in the unburned site were Pinus densiflora (100.00) and Q. variabilis (66.10) at the tree layer, Q. serrata (100.00) and Zanthoxylum schinifolium (29.64) at the shrub layer., and Q. serrata (76.30) and M. sinensis var. purpurascens (72.84) at the herb layer. The biological spectra based on SDR₃ were Th-D₁-R/sub 5/-e for the burned and H (M)-D₁-R/sub 5/-e type for the unburned site, respectively. The index of similarity (CCs) between the burned and unburned sites was 0.41. The degree of succession (DS) were 609 for the burned and 1168 for the unburned site, respectively. The species diversity (H) and evenness indices (e) of the burned site were lower than those of the unburned site, but the dominance indices (C) was higher in the burned site. In the analysis of soil properties, pH, the content of NO₃/sup -/-N, available phosphrous, and exchangeable cations (K/sup +/, Ca/sup 2+/, Na/sup +/, Mg/sup 2+/) in the burned site were higher than those in the unburned site, whereas the contents of organic matter, total carbon, total nitrogen and NH₄/sup +/-N were lower in the burned site. The results show that dominant species in the burned site change from Miscanthus-Lespedeza→Lespedeza→Quercus and finally to Quercus forest, and the changes of soil properties also affect the early vegetational succession after fire.