• Atmosphere
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• v.17 no.4
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• pp.483-492
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• 2007

The objective of this study is to describe scientific progresses in understanding of climate change in the Intergovernmental Panel on Climate Change (IPCC) assessment reports, contributed by Working group I. Since 1988, IPCC's four assessment reports showed significant improvements in understanding of observed climate change, drivers of climate change, detection and attribution of climate change, climate models, and future projection. The results are based on large amounts of observation data, sophisticated analyses of data, improvements of climate models and the simulations. While the First Assessment Report (FAR) in 1990 reported that a detectable anthropogenic influence on climate has little observational evidence, the Fourth Assessment Report (AR4) reported that warming of the climate system is unequivocal and is very likely due to human influences. It is also noted that anthropogenic warming and sea level rise would continue for centuries due to the time scales associated with climate processes and feedbacks, even if greenhouse gas were to be stabilized.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.4
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• pp.15-20
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• 2024

Purpose: Climate change is greatly affecting the frequency and intensity of fires around the world. The main effects of climate change on fires are rising temperatures, dry seasons and extreme droughts, changes in precipitation, increased strong winds, extended fire danger periods, and changes in natural ecosystems. Several factors due to climate change are increasing the risk of large-scale fires, such as wildfires. Research design, data and methodology: Rising temperatures caused by climate change will make forests and grasslands drier, make it easier for wildfires to occur in drier environments and spread quickly to wider areas, and the generated wildfires will release large amounts of greenhouse gases into the atmosphere, such as carbon dioxide (CO₂), and the released greenhouse gases will strengthen the global greenhouse effect, further raising the temperature. As temperatures rise, the risk of wildfires increases in drier environments, and this process is repeated, leading to a vicious cycle of intensifying climate change as more fires occur and more greenhouse gases are released. Results: In conclusion, climate change is increasing the risk of fire occurrence and this phenomenon is expected to become more frequent and severe in the future. Conclusions: In order to cope with the increasing fire risk caused by climate change, fire prevention and management. Fire detection and response systems need to be strengthened, supportive policies and international cooperation are needed to restore ecosystems, and these measures, along with fire prevention, management and countermeasures, should take into account long-term climate change and adaptation as well as short-term responses.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.535-543
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• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1107-1119
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• 2014

Interesting in abnormal climate is currently growing because of climate change. With this, an increasing number of people continue to show concern over the negative effects of such changes. In Korea, the annual average rainfall amount increased to about 19% from 1,155 mm in the 1910s to 1,375 mm in the 2000s. By the end of the 21st century, it has been projected that rainfall will further increase to about 17%. In particular, the 10-year frequency of localized heavy rain of more than 100-mm rainfall per day reached 385 days in the last 10 years. As such, it increased 1.7 times from 222 in the 1970s-80s. The extreme events caused by climate change is thus reported as having exacerbated over the years. Gangwon-province will suffer more from climate change than any other region in Korea because of its mostly mountainous terrain. It is a special region with both mountainous and oceanic climates divided alongside the eastern and western regions of the Taebaek Mountain Range. As such, this paper try to quantify using ETCCDI (Expert Team on Climate Change Detection and Indices) the recent climate changes in this region.

• 한국환경농학회:학술대회논문집
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• 2009.07a
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• pp.228-239
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• 2009

The observations on climate change show a clear increase in the temperature of the Earth's surface and the oceans, a reduction in the land snow cover, and melting of the sea ice and glaciers. The effects of climate change are likely to include more variable weather, heat waves, increased mean temperature, rains, flooding and droughts. The threat of climate change and global warming on human and animal health is now recognized as a global issue. This presentation is described an overview of the latest scientific knowledge on the impact of climate change on zoonotic diseases. Climate strongly affects agriculture and livestock production and influences animal diseases, vectors and pathogens, and their habitat. Global warming are likely to change the temporal and geographical distribution of infectious diseases, including those that are vector-borne such as West Nile fever, Rift Valley fever, Japanese encephalitis, bluetongue, malaria and visceral leishmaniasis, and other diarrheal diseases. The distribution and prevalence of vector-borne diseases may be the most significant effect of climate change. The impact of climate change on the emergence and re-emergence of animal diseases has been confirmed by a majority of countries. Emerging zoonotic diseases are increasingly recognized as a global and regional issue with potential serious human health and economic impacts and their current upward trends are likely to continue. Coordinated international responses are therefore essential across veterinary and human health sectors, regions and countries to control and prevent emerging zoonoses. A new early warning and alert systems is developing and introducing for enhancing surveillance and response to zoonotic diseases. And international networks that include public health, research, medical and veterinary laboratories working with zoonotic pathogens should be established and strengthened. Facing this challenging future, the long-term strategies for zoonotic diseases that may be affected by climate change is need for better prevention and control measures in susceptible livestock, wildlife and vectors in Korea. In conclusion, strengthening global, regional and national early warning systems is extremely important, as are coordinated research programmes and subsequent prevention and control measures, and need for the global surveillance network essential for early detection of zoonotic diseases.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.149-162
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• 2018

It is necessary to select the appropriate global climate model (GCM) to take into account the impacts of climate change on integrated water management. The objective of this study was to develop the selection technique of representative GCMs for uncertainty in climate change scenario. The selection technique which set priorities of GCMs consisted of two steps. First step was evaluating original GCMs by comparing with grid-based observational data for the past period. Second step was evaluating whether the statistical downscaled data reflect characteristics for the historical period. Spatial Disaggregation Quantile Delta Mapping (SDQDM), one of the statistical downscaling methods, was used for the downscaled data. The way of evaluating was using explanatory power, the stepwise ratio of the entire GCMs by Expert Team on Climate Change Detection and Indices (ETCCDI) basis. We used 26 GCMs based on CMIP5 data. The Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios were selected for this study. The period for evaluating reproducibility of historical period was 30 years from 1976 to 2005. Precipitation, maximum temperature, and minimum temperature were used as collected climate variables. As a result, we suggested representative 13 GCMs among 26 GCMs by using the selection technique developed in this research. Furthermore, this result can be utilized as a basic data for integrated water management.

• Atmosphere
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• v.16 no.3
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• pp.215-223
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• 2006

Among observational, local-environmental, and large-scale factors causing significant changes in climate records, the site relocations and the replacement of the instruments are well-known nonclimatic factors for the analysis of climatic trends, climatic variability, and for the detection of anthropogenic climate change such as heat-island effect and global warming. Using dataset that were contaminated by these nonclimatic factors can affect seriously the assessment of climatic trends and variability, and the detection of the climatic change signal. In this paper, the inhomogeneities, which have been caused by relocation of the observation site, in the climate data of Korea Meteorological Administration (KMA) were examined using two-phase regression model. The observations of pan evaporation and wind speed are more sensitive to site relocations than those of other meteorological elements, such as daily mean, maximum and minimum temperatures, with regardless to region.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.393-396
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• 2022

Recently, rapid climate change has had a significant impact on the ecosystem of honeybees. In addition, the problem of Vespa Hornets invasion of colonies has a fatal impact on the bee ecosystem, independent of climate change. Especially in late summer. This study relates to a method for preventing Vespa Hornets attack. In this study, we developed a Vespa Hornets sound detection device was developed by collecting and analyzing the sound of a Vespa Hornets and applying IoT technology. The developed device detects the sound of a Vespa Hornets when Vespa Hornets appears around the hive of the bees and sends a signal to automatically close the door of the beehive. The device that receives the signal drives the motor that controls the honeycomb door to close the beehive door. The Vespa Hornets sound detection device operates until no Vespa Hornets sound is detected. The system developed by us is expected to be installed in the beehives of actual beekeeping farms to dramatically reduce the damage caused by by Vespa Hornets.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.188-200
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• 2014

The IPCC 5th Assessment Report (Climate Change 2013: The Physical Science Basis) was accepted at the 36th Session of the IPCC on 26 September 2013 in Stockholm, Sweden. It consists of the full scientific and technical assessment undertaken by Working Group I. This comprehensive assessment of the physical aspects of climate change puts a focus on those elements that are relevant to understand past, document current, and project future of climate change. The assessment builds on the IPCC Fourth Assessment Report and the recent Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. The assessment covers the current knowledge of various processes within, and interactions among, climate system components, which determine the sensitivity and response of the system to changes in forcing, and they quantify the link between the changes in atmospheric constituents, and hence radiative forcing, and the consequent detection and attribution of climate change. Projections of changes in all climate system components are based on model simulations forced by a new set of scenarios. The report also provides a comprehensive assessment of past and future sea level change in a dedicated chapter. The primary purpose of this Technical Summary is to provide the link between the complete assessment of the multiple lines of independent evidence presented in the main report and the highly condensed summary prepared as Policy makers Summary. The Technical Summary thus serves as a starting point for those readers who seek the full information on more specific topics covered by this assessment. Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased. Total radiative forcing is positive, and has led to an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of $CO_2$ since 1750. Human influence on the climate system is clear. This is evident from the increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and understanding of the climate system. Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. The in-depth review for past, present and future of climate change is carried out on the basis of the IPCC 5th Assessment Report.