ࡱ> SUR R/%bjbj.>! ff8LEt-aaaaa" ,------f/2---aaT.-!!!aa,!,!!V*@;+a W)* ,D-0t-*T2 v2;+22$;+dO!M--"!t-2f s: Japan National report 2009 by S. Ishizaki & M. Kamachi Background The main Japanese contribution, as assimilation centers, to JCOMM/ET-OOFS and GODAE Ocean View consists of the Japan Meteorological Agency operational systems for ocean weather forecasting and ocean climate (El Nino and seasonal) forecasting, and research groups such as MOVE/MRI.COM by MRI for both of ocean weather and climate. JMA and MRI MOVE/MRI.COM System Background JMA: Operational ocean activities in Japan is pursued by the Japan Meteorological Agency (JMA) for ocean monitoring/nowcasting/forecasting. JMA has started to provide daily operational nowcasting and forecasting datasets from 2008 for the open ocean using the Multivariate Ocean Variational Estimation with MRI Community Ocean Model (MOVE/MRI.COM) system. MOVE/MRI.COM provides the main Japan operational contribution to GODAE. The products are now available through JMA homepage. MRI: MOVE/MRI.COM Systems for operational ocean forecasting and operational ocean initialization for ElNino and seasonal forecasting in JMA have been developed at MRI. MOVE/MRI.COM has 6 configurations: WNP (western North Pacific, 0.1 degree), NP (North Pacific, 0.5 degree), G (Global, 1 degree), Cst (coastal, 1-2 km), C (Global_Coupled atmosphere and ocean 3DVAR, 1 degree) and Adj (adjoint version of WNP, 01 degree). 1. Input Data MOVE/MRI.COM uses 6-hourly forcing data from the JMA operational NWP output and reanalyses (JRA25/JCDAS). MOVE/MRI.COM assimilates in situ profile data delivered in GTS (GTSPP for R&D). These messages include VOS XBTs, Argo and TAO/Triton data. Both temperature and salinity data are assimilated. MOVE/MRI.COM uses variational QC procedure (Fujii & Kamachi, 2005). Altimeter data from the Jason-2 and Envisat satellites are also assimilated in MOVE/MRI.COM. MOVE/MRI.COM uses sea surface temperature dataset MGDSST (Japan GHRSST) from ships and drifting and moored buoys, together with AVHRR, AMSR-E data. 2. Data serving Assimilation and prediction products are open through through JMA web pages. 3. Model The model is the Meteorological Research Institute Community Ocean Model (MRI.COM; Ishikawa et al. 2005), which is 3-D, z-s hybrid coordinate model that solves primitive equations. The model can be multi-nested at various resolutions. Accompanying data assimilation system is the Meteorological Research Institute Ocean Variational Estimation System (MOVE), which is based on 3DVAR (Fujii & Kamachi, 2003a,b,c, Usui et al., 2006). Currently, a 1/10 degree version has been developed for the western North Pacific region (MOVE/MRI.COM-WNP; Usui et al. 2006) and it will be implemented as an operational system of JMA by 2008. The surface forcing for the model is taken from the operational outputs from JMA operational nowcast/forecast system (or may be coupled to the atmospheric model in the future). For nowcast, we make a full use of GTS, MGDSST (Japan GHRSST), Satellite Altimeter (Jason, Envisat). The global version has 1 degree, North Pacific one 0.5, and 0.1 degree, and future coastal one 1-2 km. 4. Assimilation method The MOVE/MRI.COM data assimilation scheme has been developed from the 3DVAR-IAU scheme originally devised by Fujii & Kamachi (2003a,b,c). The scheme deals efficiently with multivariate (T-S) coupled EOF vertical modal decomposition and horizontal Gaussian offdiagonal elements of the background error covariance matrix (Fujii & Kamachi, 2003a,b) with a new nonlinear descent method (POPULAR) by Fujii & Kamachi (2003c) and nonlinear constraints especially variational QC (Fujii & Kamachi, 2005). 5. Assimilation products and dissemination Selected parts of output of MOVE/MRI.COM state variables are made available on the JMA web sites. MRI has done reanalysis projects (WNP: 1993 to 2008+; NP and G: 1948-2008+). 6. Systems MOVE/MRI.COM systems have various 50 level nested models which will subsequently be introduced to the operational suite: western North Pacific configuration with a grid spacing of 0.1 degree; North Pacific with 0.5 degree; Global with 1 degree; and future Japan coastal configurations with 1 km grids. 7. Links with GODAE pilot projects (Argo, GHRSST) MOVE/MRI.COM assimilates both temperature and salinity profiles from Argo floats. Climatological velocity fields are compared. The assimilation result recovers well the frontal and velocity structures in the mid-depth derived from Argo data. Some other assessments of impact have been carried out, and further work in this area is anticipated. MOVE/MRI.COM also assimilates MGDSST (Japan operational GHRSST). 8. Internal metrics and intercomparison plans Verification/validation has been done, from 1993 to 2008, according to GODAE North Pacific Metrics (Kamachi and Minato, 2001). The intercomparison in the North Pacific partly was done with the cooperation of IPRC/APDRC. Global version of the MOVE/MRI.COM submitted the data to the Intercomparison of global ocean under CLIVAR/GSOP. 9. Users and external metrics The targeted users are ocean research community especially for water mass analyses in ocean climate research. MRI will start to provide output, as a boundary condition, to regional forecasting system by the Japan Weather Association (JWA). See document part submitted to Ming Ji. 10. Reanalysis activities MRI have done reanalysis projects (WNP: 1993 to 2008+; NP and G: 1948-2008+) 11. Computing ressources The MRI supercomputing facilities consist of an NEC SX-6 with 32 nodes (248 cpu). It will be replaced in 2009. JMA has HITAC SR11000 with 50 nodes (400 cpu) for OOFS. References Fujii, Y. & M. Kamachi (2003a): A reconstruction of observed profiles in the sea east of Japan using vertical coupled temperature-salinity EOF modes. J. Oceanogr., vol. 59, 173-186. Fujii Y. & M. Kamachi (2003b): Three dimensional analysis of temperature and salinity in the equatorial Pacific using a variational method with vertical coupled temperature-Salinity empirical orthogonal function modes. J. of Geophys. Res., 108(C9): 3297, doi: 10.1029/2002JC001745. Fujii Y. & M. Kamachi (2003c): A nonlinear quasi-Newton method without inversion of a first-guess covariance matrix in variational analyses. Tellus, 55A: 450-454. Ishikawa, I., H. Tsujino, M. Hirabara, H. Nakano, T. Yasuda & H. Ishizaki (2005): Meteorological Research Institute Community Ocean Model (MRI.COM) Manual. Kamachi, M. & S. Minato (2001): Pacific Inter-Comparison (Internal Metrics), Handout in the International Workshop on GODAE with Focus on the Pacific, IPRC, University of Hawaii, 18pp. Usui,Y., Y. Fujii, S. Ishizaki, H. Tsujino, T. Yasuda, M. Kamachi (2006): Introduction of the Meteorological Research Institute Multi-Variate Ocean Variational Estimation System (MOVE-System). Advances in Space Res., 37, 806-822. Usui, N., H. Tsujino, Y. Fujii and M. Kamachi (2007): Short-range prediction experiments of the Kuroshio path variabilities south of Japan, Ocean Dynamics, vol.56, 607-623, DOI 10.1007/s10236-006-0084-z Usui, N., H. Tsujino, Y. Fujii, M. Kamachi (2008): Generation of a trigger meander for the 2004 Kuroshio large meander. J. Geophys. 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