The ECCO High-Resolution Global-Ocean State Estimation
Initiative

ARC: Bob Ciotti, Chris Henze, and Jim Taft
JPL: Benny Cheng, Ichiro Fukumori, Tong Lee, and Dimitris Menemenlis
MIT: Alistair Adcroft, Patrick Heimbach, Chris Hill
SIO: Armin Koehl and Detlef Stammer
UW:  Jinlun Zhang

During the past four years, the consortium for Estimating
the Circulation and Climate of the Ocean (ECCO) has
demonstrated the feasibility and utility of providing
global, sustained, dynamically reasonable estimates of
the full three-dimensional, time-varying oceanic state.
Remotely-sensed (altimeter, scatterometer, ocean
temperature, and gravity) and in-situ (temperature and
salinity profilers, mooring, drifter, and float) data and
advanced estimation methods (adjoint model, Kalman
filter, and Rauch-Tung-Striebel smoother) are used to
constrain a state-of-the-art numerical ocean model and to
produce best estimates of the large-scale oceanic
circulation.  These estimates are made available in
near-real-time and are being used for a wide variety of
scientific and operational applications.

The ECCO experience has shown that it is possible to
carry out these computations and that the resulting
estimates possess significant value.  Unfortunately, the
computational demands for such a system are enormous,
limiting the existing ECCO products to rather coarse
resolutions (30 to 100-km horizontal grids). With this
limited resolution it is not possible to adequately
represent the many small-scale features of the oceanic
circulation (western boundary currents, eddies,
convection, etc.) that are important both for climate
studies and for operational applications.  To address
this deficiency and to more fully utilize the available
satellite and in-situ data, NASA is committing
significant new computational resources to the ECCO
project.  This presentation will review existing ECCO
products and applications and summarize the motivation,
objectives, and status of the ECCO high-resolution ocean
state estimation initiative.

http://www.ecco-group.org