大泉 伝 / OIZUMI, Tsutao

事項	詳細
所属・職名	気象予報研究部・第一研究室・研究官
連絡先	aooizumitsutaoo
個人ページ	https://researchmap.jp/t_oizumi
専門分野	メソ気象学、水文学、災害予測
学位	博士(工学)
受賞歴、委員等
発表論文	Saito, K., T. Matsunobu, and T. Oizumi, 2022: Effect of upper-air moistening by northward ageostrophic winds associated with a tropical cyclone on the PRE enhancement. SOLA, 18, 81-87, doi:10.2151/sola.2022-014 Duc, L., T. Kawabata, K. Saito, and T. Oizumi, 2021: Forecasts of the July 2020 Kyushu heavy rain using a 1000-member ensemble Kalman filter. SOLA, 17, 41-47, doi:10.2151/sola.2021-007 Kobayashi, K., L. Duc, T. Oizumi and K. Saito, 2020: Ensemble flood simulation for a small dam catchment in Japan using nonhydrostatic model rainfalls. Part 2: Flood forecasting using 1600 member 4D-EnVAR predicted rainfalls.Natural Hazards and Earth System Sciences, 20,755-700, doi:10.5194/nhess-20-755-2020 Oizumi, T., K. Saito, L. Duc, and J. Ito, 2020: Ultra-high-resolution numerical weather prediction with a large domain using the K computer: Part 2 Case of the Hiroshima heavy rainfall event on August 2014 and size dependency of simulated convection cores on model resolutions. J. Meteor. Soc. Jpn., 98, 1163-1182, doi:10.2151/jmsj.2020-060 Oizumi, T., K. Saito, J. Ito, T. Kuroda, and L. Duc, 2018: Ultra-High-Resolution Numerical Weather Prediction with a Large Domain Using the K Computer: A Case Study of the Izu Oshima Heavy Rainfall Event on October 15-16, 2013.J. Meteor. Soc. Jpn., 96, 25-54, doi:10.2151/jmsj.2018-006 Ito, J., T., Oizumi, and H., Niino, 2017: Near-surface coherent structures explored by large eddy simulation of entire tropical cyclones, Scientific Reports.Scientific Reports, 7, 3798,doi:10.1038/s41598-017-03848-w Saito K., T. Tsuyuki, H. Seko, F. Kimura, T. Tokioka, T. Kuroda, L. Duc, K. Ito, T. Oizumi, G. Chen, J. Ito, and SPIRE Field 3 Mesoscale NWP group, 2013: Super high-resolution mesoscale weather prediction.J. of Physics: Conference Series, vol. 454, 012073, doi:10.1088/1742-6596/454/1/012073
担当課題リスト	気象研究所 基盤技術研究「大気の物理過程の解明と物理過程モデルの開発に関する研究」 科研費課題「巨大アンサンブルを用いた浸水危険度と被災者数の確率的な高精度推定手法の開発」研究活動スタート支援