Japan Geoscience Union Meeting 2018

Presentation information

[EE] Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI22] Data assimilation: A fundamental approach in geosciences

Sun. May 20, 2018 1:45 PM - 3:15 PM Poster Hall (International Exhibition Hall7, Makuhari Messe)

convener:Shin'ya Nakano(The Institute of Statistical Mathematics), Yosuke Fujii(Meteorological Research Institute, Japan Meteorological Agency), SHINICHI MIYAZAKI(京都大学理学研究科, 共同), Takemasa Miyoshi(RIKEN Advanced Institute for Computational Science)

[MGI22-P03] Numerical Weather Prediction Experiments using a Coupled Atmosphere-Ocean Data Assimilation System in JMA/MRI (2)

*Toshiyuki ISHIBASHI1, Takeshi Iriguchi1, Yousuke Fujii1, Tamaki Yasuda1, Yuhei Takaya1, Naoki Saito1, Kazutoshi Onogi1 (1.MRI/JMA)

Keywords:data assimilation, numerical weather prediction, atmosphere ocean coupled data assimilation

An atmosphere-ocean coupled data assimilation system (CDAS) has been developed at the JMA/MRI to investigate feasibility of a CDAS as a future DAS for seamless numerical prediction including both numerical weather prediction (NWP) and numerical seasonal climate prediction (NCP), and for reanalysis of the atmosphere-ocean. Our CDAS (MRI-CDA1) has two features. 1) It composed of the JMA operational systems, the global atmospheric DAS (MRI-NAPEX) based on 4D-Var, the global ocean DAS (MOVE-G2) based on 3D-Var, and the atmosphere- ocean coupled global forecast model (CGCM: JMA/MRI-CGCM2). 2) Coupling strategy is “weak coupling” with two different data assimilation window lengths for the atmosphere and ocean. Here, “weak coupling” denotes the approximation that ignores correlations of atmosphere and ocean background forecast errors. Following the previous report in JpGU-AGU joint meeting 2017 (Ishibashi et al. 2017), we will report basic property of MRI-CDA1 in NWP.