Ocean State Estimation by 4D-VAR Data Assimilation using ARGO Data S Ocean State Estimation by 4D-VAR Data Assimilation using ARGO Data S. Masuda, T.Awaji,N.Sugiura,H.Igarashi,Y.Ishikawa,Q.Jiang,K.Takeuchi Four-dimensional Variational (4D-VAR) ocean data assimilation system is used to produce time-varying model/data syntheses. The result is a dynamically self-consistent estimate of ocean state. It has greater information and forecast potential than do models or data alone (e.g., Stammer et al., 2002; Masuda et al., 2003).

Data Assimilation System Masuda et al. (2003)

Cost Function

Assimilated Data Surface data Subsurface data ・Reynolds SST (10daily) ・FNMOC; T, S (monthly) ・TAO/TRITON/PIRATA; T, S (monthly) from NOAA ・ARGO buoy; T, S (monthly) from Coriolis Data Centre ・WOD98 climatologies; T, S (monthly)

Subsurface Data without ARGO Buoys 2000 2002 T S

Subsurface Data with ARGO Buoys 2000 2002 T S

Subsurface Data with ARGO Buoys 2000 2002 T S

Data Assimilation Experiment Assimilation period; 2000-2002 EXP.1 Simulation EXP.2 Assimilation with whole the data (FNMOC,ARGO,…) EXP.3 Assimilation with only Reynolds SST and WOD98

Salinity Distribution at 26.8sq (Jan;2002) Exp.1:Simulation Exp.2:Assimilation Exp.2-Exp.1:Difference

Salinity Distribution at 26.8sq (Jan;2002) The NPIW water extends southward Exp.1:Simulation Exp.2:Assimilation ～O(0.1psu) Exp.2-Exp.1:Difference

Subarctic Water Mass Distribution at 47oN (Jul;2002) Exp.1:Simulation Exp.2:Assimilation

Subarctic Water Mass Distribution at 47oN (Jul;2002) Dichothermal structure Mesothermal structure Exp.1:Simulation Exp.2:Assimilation Oyashio Recirculation

WOCE Revisit Data at 47oN q 47ºN P1 Revisit（1999） Suga et al. (2002) 26 sq 27 160ºE 160ºW 180ºE 140ºW Dichothermal structure Mesothermal structure Suga et al. (2002)

Estimated Subsurface Circulation in the North Pacific Ocean (Jul; 2002) 26.2sq 26.6sq

Estimated Subsurface Circulation in the North Pacific Ocean (Jul; 2002) 26.2sq 26.6sq

HydroBase Climatological Map at 26.6sq HydroBase po.temp & circulation Suga et al. (2003)

Estimated Northward Heat Transport (2000-2002 annual mean) Exp.1 Exp.1 Exp.2 Exp.2

Impact of Interannual Subsurface Observations (ARGO,FNMOC…) Exp.2(assimilation) – Exp.3(assimilation without ARGO, FNMOC…)

Impact of Interannual Subsurface Observations (ARGO,FNMOC…) Exp.2 – Exp.3

Impact of Interannual Subsurface Observations (vertical section 30oW) 26.8sq Exp.2 – Exp.3

Concluding Remarks Estimates of the dynamical state for 2000-2002 . Dynamically consistent time-varying data set with realistic features (e.g. NPIW, subarctic water masses) is obtained. The impacts of ARGO, FNMOC…data are striking particularly in the North Atlantic region (and the Bering Sea) at 26.8sq in this assimilation experiment. The ARGO buoy is promising. (We hope data coverage for all over the world ocean like for the North Atlantic.)

Future Work Long-term assimilation experiment Information of recent observations can improve the quality of reanalysis data for the past.

Future Work 2 Is velocity information from ARGO buoys available as an assimilation element? Iwao et al. (2003)

Time Change of the Costs

Computational Efficiency 31CPU, 57.4GFOPS on the Earth Simulator. 1 iteration (3.5yr) ～４hours　　　　

Longitude-time Distribution of T at 300m (40oN) Observed data Simulation Estimated result  2002 2000 Pacific Atlantic year

SST Distribution (Jul;2002)

Net Heat Flux Distribution (Jan;2002) Difference

Net Heat Flux Distribution (Jul;2002) Difference

Subarctic Water Mass Distribution at 47oN (Jul;2002) Dichothermal structure Exp.2:Assimilation Mesothermal

Estimated Subsurface Circulation at 26.6sq (North Pacific Ocean; 2002) Exp.2:January Exp.2July

Estimated Subsurface Circulation at 26.8sq (North Pacific Ocean; 2002) Exp.2:January Exp.2July

Estimated Northward Heat Transport (24oN; 2000-2002) Exp.1 Exp.1 Exp.2 Exp.2

Previous study using our 4D-VAR ocean data assimilation system Target: Estimates of the dynamical state for Climatological Seasonal Cycle 　 (a)Dynamically consistent time-varying data set with realistic features of the global ocean circulation. (b)Sensitivity experiment for the NPIW (water mass analysis). (c)Manifestation of the advantage of a 4D-VAR method ( a nudging method).  Sugiura et al. (PCFD,2003), Masuda et al. (GRL,2003), Awaji et al. (JO,2003)

Results of ODA experiment for climatological seasonal cycle (b)Sensitivity experiment (a)Reanalysis data set Masuda et al. (2003)

1996-1999 Experment   WOD01 Reanalysis MOM3

SST distribution in the Pacific region

Nino3 SST Assimilation rmsd:0.69K Simulation rmsd:1.60K

Net Heat Flux distribution in the Pacific region

Wind stress curl distribution in the Pacific region

Longitude-time distribution of SST Simulation Observation Assimilation

Longitude-time distribution of the various variables (Assimilation)

Latitude-time distribution of the SSH anomaly Averaged 120E-170E; as heat content of off-equatorial region

Latitude-time distribution of the wind curl Averaged 120E-170E; Ekman pumping of off-equatorial region 　Sensitivity experiment !!

Longitude-time distribution of the equatorial Kelvin waves and of the 1st mode equatorial Rossby waves

Velocity & Temperature distribution (onset period)

Coupled Data assimilation （RR２００２） Atmospheric data assimilation system (now constructing) Ocean data assimilation system + ice model CFES coupling system

High resolution data assimilation (Assimilation) Fwd high resolution Bkw low resolution (e.g., Kohl and Willebrand, 2003) ? Bkw high resolution Cost averaging

Longitude-time distribution of the equatorial Kelvin waves and of the 1st mode equatorial Rossby waves Eq 　5S(inverted) Eq