세미나

2024년 9월 24일(화) 세미나 안내 | ||
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제목: 인공지능 기반 전지구 기후예측모델 개발 및 최신연구 동향
연사: 강대현 박사 (KIST 기후탄소순환연구단)
일시: 2024년 9월 24일 화요일 16:00 장소: 과학관 B102호
Abstract: Recent deep learning-based models have shown great potential in predicting and interpreting weather and climate phenomena. For example, the data-driven weather forecast models (e.g., GraphCast and Pangu-Weather) showed better forecast skills of the global atmosphere within a week than the operational numerical weather prediction. However, with their short history, the understanding of trained physical processes in the deep learning-based model is not satisfactory, which limits its predictability until two weeks. Motivated by the above, this study aims to improve the accuracy and capability of data-driven global climate prediction at sub-seasonal timescales. This study uses a deep learning-based model trained with daily-mean atmospheric variables in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) at 250-km horizontal resolution for 1979-2015. A method to better structuralize the horizontal structure of the global atmosphere into the deep learning model shows great potential to improve data-driven prediction skills, which exhibit reliable deterministic forecast skills within a week or longer prediction. The inference results also exhibit realistic sub-seasonal climate variability, such as eastward propagation of the MaddenJulian Oscillation (MJO), indicating that the realistic physical processes are adequately trained in the data-driven method. The results of this study shed light on the necessary processes in the model architecture for state-of-the-art global climate prediction.
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이전글 | 2024년 9월 20일(금) 세미나 안내 | |
다음글 | 2024년 9월 27일(금) 세미나 안내 |