A Member of ECCO Consortium (JPL | MIT | SIO) Home | Help  

Research Synopsis

Seasonal-to-interannual changes in ocean circulation are studied from assimilating observations with a global ocean circulation model.

Scientific Objective:

Our immediate interest concerns the description and understanding of processes underlying changes observed in the tropical Pacific Ocean during the TOPEX/POSEIDON mission (1992 to present), in particular, the 1997-99 El Nino-La Nina event.


A state-of-the-art assimilation system is being employed consisting of

  • As complete a set of extant observations as possible
  • A global high-resolution primitive equation model with advanced physics and numerics
  • Advanced assimilation schemes based on estimation and control
  • theory.

The primary observation used in the assimilation is altimetric sea level measurements from TOPEX/POSEIDON. Altimetric data provide the most extensive spatial and temporal sampling of the ocean. Other data being used in our studies include XBTs, current meter measurements, drifters, floats, CTDs, satellite sea surface temperatures, tide gauges, bottom pressure measurements, and air-sea flux estimates from the NCEP reanalysis project.


Our model is based on the MIT Ocean General Circulation Model (MITgcm) which has the following characteristics relevant to this project:

  • primitive equation model
  • modules for advanced mixing schemes (GM, KPP)
  • continuous topography ("lopped-cells")
  • multi-threaded message passing interface
  • compatibility with the Tangent Linear and Adjoint Model Compiler

The model is configured to best resolve the upper ocean circulation of the tropics. The model domain covers the globe (80S to 80N) with a 1-deg zonal and meridional resolution, telescoping to a 1/3-degree latitudinal resolution within 20-deg of the equator. The model has 46-levels, 15 of which are within the top 150m at 10m resolution.

Assimilation Scheme:

Dual Kalman filter and adjoint assimilation schemes are employed. The two approaches compliment each other's strengths. The Kalman filter will be used primarily for

  • Routine (semi-operational) assimilation at the highest possible resolution, and
  • Calibration of prior errors (weights)

The adjoint method will allow

  • Periodic optimization stricter than the approximate Kalman filter
  • Physical sensitivity analyses of key processes