• 한국환경복원기술학회지
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• 제10권6호
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• pp.110-119
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• 2007

This study's objects are to predict distribution and to assess vulnerability of sub-alpine vegetations in the Korean peninsula for climate change using various climate models. This study validates relationship between sub-alpine vegetations and environmental factors using Pearson correlation analysis. Then, the future distribution of sub-alpine vegetations are predicted by a logistic regression. The major findings in this study are; First, spring mean temperature (March-May), total precipitation, elevation and warmth index are highly influencing factors to the distribution of sub-alpine vegetations. Second, the sub-alpine vegetations will be disappeared in South Korea and concentrated around Baekdu Mountain in North Korea. North Korea is predicted to have serious impact of climate change because temperature will be increased higher than in South Korea. The study findings concluded that the assessment of the future vulnerability of sub-alpine vegetations to climate change are significant.

• 한국기후변화학회지
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• 제9권2호
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• pp.171-179
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• 2018

The causal relationship between El Nino-Southern Oscillation (ENSO) and winter climate variability in Korea is tested by analyzing Korea Meteorological Administration Automatic Synoptic Observing System datasets for the past 59 years. Consistent with previous studies, positive phase of ENSO (El Nino) tends to cause warmer temperature and heavier precipitation in Korea in early winter with three-week lead time. This causality is quantified by performing Granger causality test. It turns out that ENSO explains an additional 9.25% of the variance of early-winter temperature anomalies in Korea, beyond that already provided by temperature itself. Likewise, 22.18% additional information is gained to explain early-winter precipitation variance by considering ENSO. This result, which differs from simple lead-lag correlation analysis, suggests that ENSO needs to be considered in predicting early-winter surface climate variability in Korea.

• 한국해양학회지:바다
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• 제21권2호
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• pp.49-57
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• 2016

기후변화를 일으키는 외부강제력이 전지구적으로 동일하게 주어지더라도 그에 따른 기후변화와 되먹임 효과는 지역마다 다르게 나타난다. 따라서 기후변화에 나타난 내부변동성 및 다른 잡음 효과로부터 지구온난화 신호를 구별하기 위한 기후변화 탐지는 전구평균뿐만 아니라 지역규모에서도 이뤄져 왔다. 본 논문은 지구온난화로 인해 미래에 전례 없는 기후가 나타나는 시기를 추정하고 그 지역적 차이를 분석함이 목적이며 이를 위해, 기후모형 자료를 이용한 기존 연구와는 달리, 관측 자료를 이용하여 내부변동성을 추정하고 미래 온도변화를 전망하였다. 전례 없는 기후 시기는 미래에 예측된 지표 온도가 과거 관측 기록에 나타난 온도 범위를 벗어나 전례 없이 따뜻한 기후가 이후로도 지속되는 시점으로 정의하였다. 1880년부터 2014년까지 관측된 지표온도 아노말리의 연평균 시계열을 이용하여 온난화 선형추세를 계산하였고, 이 추세로부터 벗어난 최대 변이 값을 내부변동성의 크기로 간주하였다. 관측 자료로 구한 온난화 선형추세와 내부변동성의 크기가 미래에도 유지된다고 전제하고 계산한 결과에 따르면, 육지에서 전례없는 기후는, 아프리카는 서쪽에서, 유라시아는 인도와 아라비아 반도 남부 등 저위도에서, 북아메리카는 캐나다 중서부와 그린란드 등 고위도에서, 남아메리카는 아마존을 포함하는 저위도에서, 남극대륙은 로스해 주변지역에서 향후 200년 이내에 비교적 빨리 나타나며, 우리나라를 포함한 동아시아 일부 지역에서도 200년 이내로 빨리 나타난다. 반면에 북유럽을 포함하는 고위도 유라시아 지역과 미국과 멕시코를 포함하는 북아메리카 중남부에서는 400년 이후에 나타난다. 해양에서는 전례 없는 기후가 인도양, 중위도 북대서양과 남대서양, 남극해 일부 해역과 남극 로스해, 북극해 일부 해역에서 200년 이내로 비교적 빨리 나타나는 반면, 내부변동성이 큰 동적도태평양, 중위도 북태평양 등의 일부 해역에서는 수천 년이 지나야 오는 곳도 있다. 즉, 전례 없는 기후시기는 육지에서는 대륙마다 서로 다른 양상을 보이고 해양에서는 온난화 추세가 큰 고위도 해역을 제외하면 내부변동성의 영향을 많이 받는다. 결론적으로 지구온난화로 인한 전례 없는 기후는 특정 시기에 공통적으로 나타나는 것이 아니라 지역에 따라 시기적으로 상당한 차이가 있다. 따라서 기후변화 대응책을 마련할 때 온난화 추세뿐만 아니라 내부변동성의 크기도 함께 고려할 필요가 있다.

• 한국환경보건학회지
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• 제37권6호
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• pp.397-405
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• 2011

Objectives: The impact of climate change on the health has been of increasing concern due to a recent temperature increase and weather abnormality, and the research results of the impact varied depending on regions. We synthesized risk estimates of the overall health effects of low and high temperature taking account of the heterogeneity. Methods: A comprehensive literature search was conducted using PUBMED to identify journal articles of low and/or high temperature effects on mortality. The search was limited to the English language and epidemiological studies using time-series analysis and/or case-crossover design. Random-effect models in meta analysis were used to estimate the percent increase in mortality with $1^{\circ}C$ temperature decrease or increase with 95% confidence intervals (CI) in cold or hot days. Results: Twenty three studies were presented in two tables: 1) low temperature effects; 2) high temperature effects on mortality. The combined effects of low and high temperatures on total mortality were 2% (95% CI, 1-4%) per $1^{\circ}C$ decrease and 4% (95% CI, 2-5%) per $1^{\circ}C$ increase of temperature, respectively. Conclusions: This meta analysis found that both low and high temperatures affected mortality, and the magnitude of high temperature appeared to be stronger than that of low temperature.

• 한국기후변화학회지
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• 제9권3호
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• pp.235-243
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• 2018

Loss of favorable habitats for species due to temperature increase is one of the main concerns of climate change on the ecosystem, and endangered species might be much more sensitive to such unfavorable changes. This study aimed to analyze the impact of future climate change on endangered wild animals in South Korea by investigating thermal sensitivity and vulnerability to temperature increase. We determined thermal sensitivity by testing normality in species distribution according to temperature. Then, we defined the vulnerability when the future temperature range of South Korea completely deviate from the current temperature range of species distribution. We identified 13 species with higher thermal sensitivity. Based on IPCC future scenarios RCP 4.5 and RCP 8.5, the number of species vulnerable to future warming doubled from 3 under RCP4.5 to 7 under the RCP8.5 scenario. The species anticipated to be at risk under RCP 8.5 are flying squirrel (Pteromys volans aluco), ural owl (Pteromys volans aluco), black woodpecker (Dryocopus martius), tawny owl (Strix aluco), watercock (Gallicrex cinerea), schrenck?s bittern (Ixobrychus eurhythmus), and fairy pitta (Pitta nympha). The other 10 species showing very narrow temperature ranges even without normal distributions and out of the future temperature range may also need to be treated as vulnerable species, considering the inevitable observation scarcity of such endangered species.

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2011년도 학술발표회
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• pp.46-46
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• 2011

• 한국농림기상학회:학술대회논문집
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• 한국농림기상학회 2016년도 추계 학술발표논문집
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• pp.181-183
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• 2016

• KIEAE Journal
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• 제14권4호
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• pp.127-131
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• 2014

The ground source heat pump (GSHP) system is a kind of the temperature differential energy system using relatively stable underground temperature as heat source of space heating and cooling. This system can achieve higher performance of system than it of conventional air source heat pump systems. However, its superiority of the system performance is different according to installation location or local climate, because the system performance depends on the underground condition which is decided by annual average air temperature. In this study, in order to estimate the feasibility of the ground source heat pump system according to the local climate, numerical simulation was conducted using the ground heat transfer model and the surface heat balance model. The case study was conducted in the condition of Seoul, Daejeon, and Busan, In the result, the heat exchange rate of Busan was 34.33 W/m as the largest in heating season and it of Seoul was 40.61 W/m as the largest in cooling.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 봄 학술발표회 논문집
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• pp.199-204
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• 2000

When fresh concrete is exposed to low temperature, the concrete may suffer from the frost damage at early ages and the strength development may be delayed. To solve such problems of cold weather concreting, admixtures called agent for enduring cold climate are developed to prevent the fresh concrete from being frozen at early ages In this study, the experiments are carried out on several kinds of agent for enduring cold climate to present their performance. According to experimental results, most kinds of agent for enduring cold climate show the satisfactory properties of decreasing the freezing point and acceleating the cement hydration in low temperature environment, which is available for placing concrete in spite of cold weather.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.157-157
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• 2018

A reliable and accurate downscaling model which can provide climate change information, obtained from global climate models (GCMs), at finer resolution has been always of great interest to researchers. In order to achieve this model, linear methods widely have been studied in the past decades. However, nonlinear methods also can be potentially beneficial to solve downscaling problem. Therefore, this study explored the applicability of some nonlinear machine learning techniques such as neural network (NN), extreme learning machine (ELM), and ELM autoencoder (ELM-AE) as well as a linear method, least absolute shrinkage and selection operator (LASSO), to build a reliable temperature downscaling model. ELM is an efficient learning algorithm for generalized single layer feed-forward neural networks (SLFNs). Its excellent training speed and good generalization capability make ELM an efficient solution for SLFNs compared to traditional time-consuming learning methods like back propagation (BP). However, due to its shallow architecture, ELM may not capture all of nonlinear relationships between input features. To address this issue, ELM-AE was tested in the current study for temperature downscaling.