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Tony Lee NASA Jet Propulsion Laboratory, California Institute of Technology

Major Activities of US GODAE: potential utility by IMBER. Tony Lee NASA Jet Propulsion Laboratory, California Institute of Technology . ECCO: Estimation of the Circulation & Climate of the Ocean. SODA: Simple Ocean Data Assimilation.

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Tony Lee NASA Jet Propulsion Laboratory, California Institute of Technology

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  1. Major Activities of US GODAE: potential utility by IMBER Tony Lee NASA Jet Propulsion Laboratory, California Institute of Technology • ECCO: Estimation of the Circulation & Climate of the Ocean. • SODA: Simple Ocean Data Assimilation. • GODAS: NOAA NCEP Global Ocean Data Assimilation System. • NOAA GFDL assimilation. • NASA GMAO/GSFC assimilation. • HYCOM: Hybrid Coordinate Ocean Model/assimilation system. • US Naval Research Laboratory assimilation.

  2. Applications of US-GODAE products • Climate diagnostic studies (e.g., ocean heat content change). • Initialization of coupled model prediction (e.g., ENSO forecast). • Mesoscale ocean nowcast/forecast (e.g., HYCOM, NRL). • Evaluation of observing system. • Model improvement. • Providing lateral boundary conditions for regional & coastal analysis systems (3 CODAE projects funded under US NOPP). • Drive biogeochemical models. Different assimilation methods • 3-D: sequential methods such as OI, Kalman filters, 3-D VAR. • 4-D: adjoint (4DVAR), RTS smoother, Green’s functions

  3. Characteristics of US-GODAE systems

  4. Characteristics of US-GODAE systems (cont’d) T – Temperature S – Salinity SSH – Sea Surface Height

  5. Global ocean analysis synthesized diverse data sets ECCO example present

  6. Comparison with independent data: SODA zonal velocity at 0N, 140W SODA 10m TAOOBS 50m 100m 150m

  7. Filtered Estimate Smoothed Estimate Smoothed Estimate Filter Correction time Model Physics Most sequential analysis solutions (including those by Kalman Filters) do not evolve in a physically consistent manner. Smoothers (RTS smoother, 4DVAR, among others) are solutions. Sequential update of model state cause problems in budget closure and vertical exchange of properties.

  8. An example of spurious vertical exchange due to sequential update of model state: problems may be hidden in the physical state, but emerges in biogeochemical applications. CO2 flux during ENSO inferred from a Kalman filter estimation (physically inconsistent) is unrealistically large (left), but that based on Kalman filter-smoother (physically consistent) is reasonable (right). Kalman Filtered estimate Kalman-filter/smoother estimate (Galen McKinley, 2002)

  9. These limitations can be alleviated by using 4-D methods (e.g., adjoint, RTS smoother, Green’s functions) that produce estimates satisfying model equations exactly (e.g., ECCO products).

  10. ECCO online passive tracer tool potentially useful to IMBER users: both forward and “backward” (adjoint), based on full adection & diffusion. Example: origin & pathway of NINO3 surface waters (Fukumori et al. 2004)

  11. ECCO-2 undertakes physically consistent assimilation at eddy-permitting resolution; meets IMBER’s need better Global Green’s function assimilation available this fall; southern-ocean adjoint assimilation in progress

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