Faculty Research Profile

지구환경도시건설공학과

박민규

조교수Mingyu Park

박민규

Mingyu Park

Biography

학력

· 2021: Ph.D., Meteorology and Atmospheric Science, Pennsylvania State University, USA
· 2016: B.S., Atmospheric Science, Seoul National University, Korea

주요 경력

· 2025~present: Assistant Professor, Dept. of Civil, Urban, Earth, and Environmental Eng., UNIST, Korea
· 2022~2025: Postdoctoral Research Associate, Atmospheric and Oceanic Sciences Program, Princeton University

수상/학회/외부활동

· 2025: Young Atmospheric Scientist Award, Korean Meteorological Society
· 2023~Present: Session Convener and OSPA Liaison at the American Geophysical Union session: Bridging the Gap from Climate to Extreme Weather
· 2022: Princeton Atmospheric and Oceanic Sciences Fellowship for Postdoctoral Research Scientists
· 2022: Hans Neuberger Award (Best Teaching Award), Pennsylvania State University
· 2019: Student Travel Grant, 99th American Meteorological Society Annual Meeting

Research

기후 역학 모델링 연구실

Climate Dynamics and Modeling Lab

Climate Science는 인간 활동으로 인해 가속화된 급격한 기후변화를 탐지하고, 이상기후에 따른 생태계와 인류에 미치는 영향을 종합적으로 평가 및 예측하는 분야입니다. 이를 위해서는 지구 시스템 내 대기, 해양, 빙하, 지권, 생물권 등의 각 요소 간 상호작용과 변동성을 이해하고, 기후 모델링을 통해 재현 및 예측하는 연구가 필요합니다. UNIST의 Climate Dynamics and Modeling Lab은 기후변화 대응이라는 거시적 문제의식 아래, 기후예측모델의 모의 능력 개선과 지역별 기후 전망 및 영향력에 대한 역학적 분석을 중심으로 연구를 수행하고 있습니다.
* 중점 연구 주제: (1) 폭염, 한파, 집중호우, 가뭄 등의 기상재해의 발생 메커니즘 및 경향성 분석 (2) 주요 기상 인자 및 기후 변동성의 계절내-계절 예측 및 예측성 평가 (3) 풍력・태양광 신재생에너지 발전량 예측을 위한 바람・일사량 예측성 분석 (4) 기후변화 시나리오에서의 중위도 대기 현상 분석과 고해상도 모델 자료와 인공지능을 활용한 모의 성능 개선
Climate Science aims to detect abrupt climate change accelerated by human activities, and to evaluate and predict the impacts of climate extremes on ecosystems and human societies. To this end, it is essential to understand interactions and variabilities across the components of the Earth system, as well as their representation and future projection through climate modeling. Within the broader context of addressing climate change, the Climate Dynamics and Modeling lab at UNIST conducts research primarily on improving the performance of climate models and on dynamical analyses of regional climate projections and impacts.
The major research interests of the lab are as follows: (1) Analysis of mechanisms and long-term trends of weather extremes such as heatwave, cold spell, extreme precipitation, and drought; (2) Assessment of predictability and predictive skill of major meteorological variables and climate variabilities on subseasonal-to-seasonal time scales; (3) Evaluating the predictability of wind and shortwave radiation on a regional scale for renewable energy generation; (4) Understanding projected changes in midlatitude atmospheric phenomena and enhancing their representation by leveraging high-resolution model simulations and AI/ML techniques.

Climate Science aims to detect abrupt climate change accelerated by human activities, and to evaluate and predict the impacts of climate extremes on ecosystems and human societies. To this end, it is essential to understand interactions and variabilities across the components of the Earth system, as well as their representation and future projection through climate modeling. Within the broader context of addressing climate change, the Climate Dynamics and Modeling lab at UNIST conducts research primarily on improving the performance of climate models and on dynamical analyses of regional climate projections and impacts.
The major research interests of the lab are as follows: (1) Analysis of mechanisms and long-term trends of weather extremes such as heatwave, cold spell, extreme precipitation, and drought; (2) Assessment of predictability and predictive skill of major meteorological variables and climate variabilities on subseasonal-to-seasonal time scales; (3) Evaluating the predictability of wind and shortwave radiation on a regional scale for renewable energy generation; (4) Understanding projected changes in midlatitude atmospheric phenomena and enhancing their representation by leveraging high-resolution model simulations and AI/ML techniques.

연구분야

극한기상 분석, 예측성 평가, 중기 예보 모델 평가 / Extreme weather event analysis, Predictability assessment, Evaluation of medium-range forecast model performance

Extreme weather event analysis, Predictability assessment, Evaluation of medium-range forecast model performance

연구 희망분야

하이브리드 예보: 수치예보모델과 결정론적 AI 모델을 함께 활용하는 예보 기술 / Hybrid Forecasting: weather predictions by combining physics-based models and AI models

Hybrid Forecasting: weather predictions by combining physics-based models and AI models

연구주제

기후변화 시나리오에 따른 중위도 역학적 현상의 시공간적 변화, 기상재해의 발생 메커니즘 및 변동성, 기후변화에 따른 대기-해양 및 지면-대기 상호작용 변화 분석, 고해상도 기후예측모델 자료와 머신러닝 기술 활용을 통한 예측성 개선
Spatiotemporal changes in midlatitude atmospheric dynamics under future climate scenarios, Mechanisms and variability of extreme weather events, Changes in air-sea and land-atmosphere interactions under climate change, Enhancing predictability using high-resolution model simulations and machine learning techniques

Spatiotemporal changes in midlatitude atmospheric dynamics under future climate scenarios, Mechanisms and variability of extreme weather events, Changes in air-sea and land-atmosphere interactions under climate change, Enhancing predictability using high-resolution model simulations and machine learning techniques

국가연구개발사업 기술 분류체계

국가과학기술표준분류

ND. 지구과학(지구/대기/해양/천문) > ND04. 대기과학 > ND0403. 대기역학

Outputs

논문

· Npj climate and atmospheric science, A hybrid approach for skillful multiseasonal prediction of winter North Pacific blocking, Park, M., N. C. Johnson, J. Hwang, and L. Jia / 2024-09
· Nature Communications, The Driving of North American Climate Extremes by North Pacific Stationary-transient Wave Interference, Park, M., N. C. Johnson, T. L. Delworth / 2024-08
· Journal of the Atmospheric Sciences, Which is the More Effective Driver of the Poleward Eddy Heat Flux: Zonal Gradient of Tropical Convective Heating or Equator-To-Pole Temperature Gradient? Park, M., and S. Lee / 2022-06