• 한국재난정보학회 논문집
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• 제17권4호
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• pp.755-768
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• 2021

연구목적: 다양한 주제와 목적으로 연구가 진행되는 폭염 연구의 특성상 연구의 질적 향상과 고도화를 제고하기 위해서는 연구의 동향 및 발전 방향을 전망하는 것이 중요하다. 따라서, 폭염 연구의 현황과 앞으로 수행될 연구의 방향성을 제시할 수 있는 기초자료를 제공하고자 폭염 관련 연구의 동향과 추세를 살펴보고자 하였다. 연구방법: 2011년부터 2020년까지 한국연구재단에 등록된 학술지에 게재된 폭염 연구들을 대상으로 연구가 진행된 시기, 연구의 목적, 연구에 활용된 연구대상, 연구의 방법으로 분류하여 분석하였다. 연구결과: 주요 연구의 결과는 살펴보면 다음과 같다. 첫째, 폭염에 대한 관심이 증가할수록 폭염 연구의 수도 증가하고 있다. 둘째, 폭염 연구의 목적은 편중되었으며, 다양한 관점으로 연구되어야 할 필요가 있다. 셋째, 다양한 연구대상을 활용하였으나 균등한 연구가 이루어지지 못하였다. 넷째, 연구목적의 영향을 받아 연구방법의 편중이 함께 나타났다. 결론: 폭염에 의한 피해는 지속적이고 광범위하게 나타나고 있다. 이러한 폭염을 재난으로서 관리하고, 예방 및 대응하기 위해서는 다양한 분야에서 균등한 연구가 이루어져야 한다.

• 대기
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• 제33권3호
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• pp.307-317
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• 2023

This study investigates the physical mechanisms that contributed to the 2022 European record-breaking heatwave throughout May-August (MJJA). The European climate has experienced surface warming and drying in the recent decade (1979~2022) which influences the development of the 2022 European heatwave. Since its spatial pattern resembles the 2003 European heatwave which is a well-known case developed by the strong coupling of near-surface conditions to land surface processes, the 2022 heatwave is compared with the 2003 case. Understanding heatwave development is carried out by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and daily maximum surface temperature released by NCEP (National Centers for Environmental Prediction) CPC (Climate Prediction Center). The results suggest that the persistent high pressure along with clear sky tends to increase the downward shortwave radiation which leads to enhanced sensible heat flux with the land surface dryness. Terrestrial Coupling Index (TCI), a process-based multivariate metric, is employed to quantitatively measure segmented feedback processes, separately for the land, atmosphere, and two-legged couplings, which appears to the development of the 2022 heatwave, can be viewed as an expression of the recent trends, amplified by internal land-atmosphere interactions.

• 한국지구과학회지
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• 제45권1호
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• pp.37-47
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• 2024

In the summer of 2018, the Korea-Japan (KJ) region experienced an extremely severe and prolonged heatwave. This study examines the GloSea6 model's prediction performance for the 2018 KJ heatwave event and investigates how its prediction skill is related to large-scale circulation patterns identified by the k-means clustering method. Cluster 1 pattern is characterized by a KJ high-pressure anomaly, Cluster 2 pattern is distinguished by an Eastern European high-pressure anomaly, and Cluster 3 pattern is associated with a Pacific-Japan pattern-like anomaly. By analyzing the spatial correlation coefficients between these three identified circulation patterns and GloSea6 predictions, we assessed the contribution of each circulation pattern to the heatwave lifecycle. Our results show that the Eastern European high-pressure pattern, in particular, plays a significant role in predicting the evolution of the development and peak phases of the 2018 KJ heatwave approximately two weeks in advance. Furthermore, this study suggests that an accurate representation of large-scale atmospheric circulations in upstream regions is a key factor in seasonal forecast models for improving the predictability of extreme weather events, such as the 2018 KJ heatwave.

• 한국멀티미디어학회논문지
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• 제23권5호
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• pp.683-699
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• 2020

Recently, the earth's highest temperature is rising due to severe climate change and heat wave. In addition, due to the increase of elderly population over 65, the number of heat patients is also increasing. In particular, the elderly who live alone in poor living environments, the lower income group, and the socially disadvantaged, such as children and pregnant women, are exposed to the dangers of heat waves, so the government's practical measures are urgently needed. In this study, we will build a visualization platform for each level of heat wave and provide the necessary countermeasure solution according to the heat wave risk. "The Hazard Visualization Platform for Heatwave" provide not only simple information, but also a customized safety service for citizens to prevent heatwaves, respond to heatwaves, and utilize heat wave information.

• 대기
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• 제29권5호
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• pp.671-687
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• 2019

This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.

• 대한토목학회논문집
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• 제41권2호
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• pp.113-121
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• 2021

폭염의 발생 메커니즘은 대부분 종관 규모적 관점에서 연구가 이루어지고 있으나, 폭염발생 이전의 또 다른 자연재해로 인한 연쇄적인 영향을 해석하기 위한 연구도 중요하다. 본 연구에서는 폭염 발생 이전에 나타나는 가뭄과의 인과관계 및 영향을 평가하기 위해 부분최소제곱 구조방정식 모형(PLS-SEM)을 이용하였다. 1974년부터 약 46년간 발생한 여름철 폭염에 미치는 계절별 가뭄의 영향정도는, 겨울철 서울(경기)지역은 37%, 강원지역은 21 %, 충청지역은 17 %이며, 봄철 서울(경기)지역은 29 %, 강원지역은 18 %, 충청지역은 8 %이며, 여름철 서울(경기)지역은 22 %, 강원지역은 29 %, 충청지역 38 %로 확인되었다. 이는 지역별로 나타나는 폭염과 계절별 가뭄이 미치는 영향의 정도가 다르기 때문에 따라 나타나는 결과로 해석된다. 여름철 가뭄-폭염 간의 영향이 크게 나타난 강원, 충청 지역은 서울(경기)지역에 비해 가뭄-폭염으로 인한 피해양상이 복합적으로 나타날 가능성이 있다.

• 한국환경복원기술학회지
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• 제24권6호
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• pp.97-107
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• 2021

Abnormal climate caused by climate change causes enormous social and economic damage. And such damage and its impact may vary depending on the location and regional characteristics of the region and the social and economic conditions of local residents. Therefore, it is necessary to continuously monitor whether there are indicators that are weaker than other regions among the detailed indicators that constitute the risk, exposure and vulnerability of climate change risk. In this study, the concept of climate change risk was used for heatwave to determine regional inequality of climate change risk. In other words, it was judged that inequality in climate change risk occurred in regions with high risk but high exposure and low vulnerability compared to other regions. As a result of the analysis, it was found that 13 local governments in Korea experienced regional inequality in climate change risk. In order to resolve regional inequality in climate change risks, the current status of regional inequality in climate change should be checked based on the analysis proposed in this study, there is a need for an evaluation and monitoring system that can provide appropriate feedback on areas where inequality has occurred. This continuous evaluation and monitoring-based feedback system is expected to be of great help in resolving regional inequality in climate change risks.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.166-166
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• 2023

Compound hazards (CHs) are two or more extreme climate events combined which occur simultaneously in the same region at the same time. Compared to individual hazards, the combination of hazards that cause CHs can result in greater economic losses and deaths. While several extreme climate events have been recorded across Asia for the past decades, many studies have only focused on a single hazard. In this study, we assess the spatiotemporal pattern of dry compound hazards which includes drought, heatwave, fire and wind across Asia for the last 42 years (1980-2021) using the historical data from ERA5 Reanalysis dataset. We utilize a daily spatial data of each climate event to assess the occurrence of such compound hazards on a daily basis. Heatwave, fire and wind hazard occurrences are analyzed using daily percentile-based thresholds while a pre-defined threshold for SPI is applied for drought occurrence. Then, the occurrence of each type of compound hazard is taken from overlapping the map of daily occurrences of a single hazard. Lastly, a multivariate assessment are conducted to quantify the occurrence frequency, hotspots and trends of each type of compound hazard across Asia. By conducting a multivariate analysis of the occurrence of these compound hazards, we identify the relationships and interactions in dry compound hazards including droughts, heatwaves, fires, and winds, ultimately leading to better-informed decisions and strategies in the natural risk management.

• 한국해양학회지:바다
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• 제29권2호
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• pp.101-115
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• 2024

해양의 고수온 현상은 지구온난화로 인한 주요 문제 중 하나로, 식량 자원의 감소와 해양 탄소 흡수력의 저하 등, 해양 생태계와 인류에게 직접적인 위협으로 부상하고 있다. 따라서, 한반도 주변 해역에서의 고수온 예측은 해양 환경 모니터링 및 관리에 중요하다. 본 연구에서는 역학 모델 기반 한반도 고수온 예측 시스템의 성긴 해양의 수직격자체계로 인한 고수온 예측의 과소모의를 개선하기 위해 LSTM 모델을 개발하였다. 2023년에 대해 수행된 한반도 고수온 예측 시스템의 고수온 예측 결과와 LSTM 모델의 결과를 기반으로 한반도 주변의 동해 해역, 황해 해역 그리고 남해 해역에서의 고수온 예측 성능을 평가했다. 본 연구에서 개발된 LSTM 모델이 세 영역 모두에서 수온이 상승하는 시기에 수온 예측 성능을 크게 개선하는 것으로 나타났으며, 수온 상승이 시작되기 전이나 하강하는 시기에는 예측 성능의 개선 효과가 미미했다. 이는 LSTM 모델이 성층이 강화되는 환경에서 성긴 수직격자로 인해 발생하는 고수온 예측의 과소모의를 개선할 수 있는 가능성을 보여준다. 향후 역학 모델의 예측 성능 개선이나 역학 모델의 대체에 자료기반 인공지능 모델의 활용성이 확대될 것으로 기대한다.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 2004년도 제56차 추계 학술대회 연제집
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• pp.58.2-59
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• 2004