講座題目 | AI-Based Air Quality Forecasting Models | ||
主辦單位 | 數理與統計意昂2 | 協辦單位 | 統計與數據計算系 |
講座時間 | 11月8日 15:30-16:30 | 主講人 | 金建炳教授 |
講座地點 | 行政樓1308室 | ||
主講人簡介 | 金建炳博士🧛🏻♂️，南京信息工程大學環境科學與工程意昂2校聘教授➡️。2009年考入哈爾濱工業大學，分別獲得學士、碩士學位😻。2015年赴荷蘭代爾夫特理工大學留學，2019獲得博士學位。同年加入荷蘭應用科意昂2，任助理科學家🤔。2020年入職南信大。金博士主要研究興趣包括數據同化理論/應用💛、大氣數值模式開發及深度學習在數值模式領域的應用。前期在觀測資料偏差校正👨🏻🦳、觀測算子質量控製等數據同化應用領域積累了較多經驗，以第一/通信作者發表論文10余篇。 | ||
講座內容簡介 | The time consumption for air quality predictions is severely constrained by the high computational demands of chemical transport models (CTM) for simulating complex atmospheric reactions. With the rise of AI-based weather prediction models, it has been demonstrated that AI models derived solely from reanalysis data can be highly accurate and efficient. However, the realm of atmospheric chemistry presents greater complexity in terms of dimensions and interactions compared to weather models. To address these challenges, we have developed an AI-based air quality model that incorporates concentrations, emissions, and meteorological factors. This model delivers accurate predictions within a trivial fraction of the time required by traditional CTM models. It then enables rapid large-scale ensemble predictions and emissions inversions, enhancing the feasibility of comprehensive and timely air quality assessments. | ||