近日👨🦱💣，我系博士後陳曉丹、李宏✋🏼、Safi Ullah榮獲2020年上海市“超級博士後”激勵計劃資助。
上海市“超級博士後”計劃是由市人力資源和社會保障局、市財政局聯合開展的一項激勵計劃🧱。旨在落實《國務院辦公廳關於改革完善博士後製度的意見》，深化推進具有全球影響力的上海科技創新中心建設🚅💜，為保障和提高優秀博士後研究人員待遇水平，進一步激發青年專業技術人才創新創造活力。
陳曉丹🥹🏃♂️， 2020年6月獲中國科學院大氣物理研究所氣象學博士學位，碩博連讀期間在《Journal of Climate》、《Geophysical Research Letters》等國際主流刊物上發表論文6篇♐️。2018-2019年間在美國哥倫比亞大學Lamont-Doherty地球研究所進行學術訪問。2020年7月進入我系博士後流動站，與溫之平教授、Aiguo Dai教授合作從事研究工作。已獲得"博新計劃"👩👩👧👦、博後面上基金、上海市超級博士後計劃的資助🕌💂🏿♀️。主要研究方向包括北極海冰與大氣環流相互作用🤏🏼⏫、氣候變化背景下中緯度極端天氣💂🏿♀️、中高緯度大氣動力等。
李宏，2020年6月獲得清華大學地球系統科學系理學博士學位，同年8月進入我系王桂華教授團隊從事博士後工作🧖🏿♂️。曾開發了我國首款在國際上公開發布的全球海洋Argo網格資料集，被國內外廣泛應用😩🧚🏿。博士期間主要研究夏季西太副高的東西移動機理，發現西太副高的東西移動（強度變化）是大氣對海表溫度異常的斜壓（正壓）響應的結果，並指出副高的東西移動可以影響南海熱帶氣旋生成頻率的變化💇♀️。目前研究興趣為海洋中尺度渦，主持1項中國博士後科學基金項目🧛🏼。2019年入選衛星海洋環境動力學國家重點實驗室青年訪問海星學者。
Safi, He’s from Khyber Pakhtunkhwa, Pakistan. He has obtained his Ph.D. in Climate System and Climate Change from Nanjing University of Information Science and Technology (NUIST), Nanjing, China. His Ph.D. dissertation focused on “Observed and projected spatiotemporal changes in temperature and its extremes over the China-Pakistan Economic Corridor”. During his Ph.D. studies, he has published five papers in scientific citation index (SCI) journals such as Atmospheric Research, Climate Dynamics, and International Journal of Climatology. Due to his outstanding academic and research performances, he has been awarded several excellent awards during his studies at NUIST, i.e., Jiangsu Provincial Excellent International student award, NUIST Excellent International student award, and NUIST Outstanding International Graduate.
In July 2020, he joined our department as a Postdoctoral Fellow under the supervision of Professor Qinglong You. Recently, he has been selected for Shanghai Super Postdoctoral Fellowships, which is one of the prestigious fellowships in China. During his Postdoc period, he will work on “Projected changes in temperature extremes and their probability over South Asia using CMIIP6 models. Besides, he will assess population exposure to these extremes in South Asia. He hope that the findings of these studies would help to improve the prediction level of extreme events and will provide a basis for climate change mitigation and adaptation in the region.
