# 유튜브 스트리밍 예정입니다.:https://youtube.com/live/bDWTfFIuMxw 1. 일시: 2024년 12월 17일(화), 14:00-16:00 2. 장소: 판교 테크노밸리 산업수학혁신센터 세미나실 - 경기 성남시 수정구 대왕판교로 815, 기업지원허브 231호 국가수리과학연구소 - 무료주차는 2시간 지원됩니다. 3. 발표자: 이진실 박사(한국과학기술원) 4. 주요내용: Introduction to Data Assimilation Techniques, PDE Applications, and Weather Forecasting Case Studies Data Assimilation is a powerful technique focused on integrating mathematical models with observational data to estimate the state of physical systems and improve prediction accuracy. Widely applied in fields such as meteorology, oceanography, and environmental science, it plays a critical role in modeling systems that vary over time and space. This presentation provides an introduction to key data assimilation techniques, including 3D-Var, 4D-Var, Kalman Filters (EnKF), and deep learning-based approaches, discussing how they are applied to partial differential equation (PDE)-based models. In particular, I delve into weather forecasting case studies, demonstrating how data assimilation effectively reconstructs atmospheric states and contributes to reducing uncertainties in initial condition estimation and long-term prediction. Additionally, I will introduce potential problems that could be effectively addressed using machine learning approaches.