Construction of mathematical models for long-term forecast of atmospheric variation by climate time-series

2014 Fiscal Year Final Research Report

• Project/Area Number: 25610028
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Foundations of mathematics/Applied mathematics
• Research Institution: Kyoto University
• Principal Investigator: SAKAJO Takashi 京都大学, 理学(系)研究科(研究院), 教授 (10303603)
• Co-Investigator(Kenkyū-buntansha): SAIKI Yoshitaka 一橋大学, 大学院商学研究科, 准教授 (20433740) ; NAKANO Naoto 北海道大学, 大学院理学研究院, 研究院研究員 (30612642) ; INATSU Masaru 北海道大学, 大学院理学研究院, 准教授 (80422450)
• Co-Investigator(Renkei-kenkyūsha): MIYOSHI Takemasa 理化学研究所, 計算科学研究機構データ同化チーム, チームリーダ (90646209)
• Project Period (FY): 2013-04-01 – 2015-03-31
• Keywords: 確率微分方程式 / データ同化 / カオス力学系 / 時系列解析 / 対流圏 / 成層圏 / Conley-Morse分解

Outline of Final Research Achievements

With close cooperation between mathematicians and meteorologist, the following　research have been promoted. Firstly, we have developed a theoretical procedure to derive an empirical stochastic differential equation from climate time-series. It is applied to time-series of the tropospheric and the stratospheric winter-time low-frequency variability, which were published in an international journal. This procedure is applicable to the construction of wide range of atmospheric phenomena. Secondly, we constantly hold joint workshops between Kyoto University and RIKEN AICS on the data assimilation. They yield the development of a new non-Gaussian and non-linear data assimilation technique, which is now under close investigation as a seed research topic. Finally, we have carried out a fundamental research on the characterization of the data assimilation as chaos synchronization, which is to be a promising future perspective on the theoretical understanding of the data assimilation.

Free Research Field

応用数学・数理流体力学