SCRIPPS OCEANOGRAPHY
  • University of California-San Diego
  • 9500 Gilman Drive
  • La Jolla CA 92093-0532 USA
  • Tel: 1-858-534-0000
  • Fax: 1-858-534-0000

CASE Short-term State Estimation (CASE-STSE)

The CASE-STSE (Short-term state estimate) setup is inherited from the 4-year long-term state estimate (CASE-LTSE) by Matthew Mazloff. The model domain ranges from approximately 28N to 40N and 130W to 114W, and has 1/16 of a degree resolution (~7km) and 72 vertical levels. The MITgcm, ocean circulation model is least-squares fit to all available ocean observations in the region of the California Current System (CCS). This is accomplished iteratively through the adjoint method. The result is a physically realistic estimate of the ocean state.

CASE-STSE assimilates available observations within an assimilation window of one to three months and produces analysis and 30-day forecasts of the ocean state. The observations used include Spray glider profiles, High-Resolution XBT profiles, Argo profiles, and satellite SSH and SST. The monthly state estimates are initialized from HYCOM/NCODA global analysis and the initial conditions, atmospheric forcing, and lateral open boundary conditions are adjusted to improve the model match to the observations in a free forward run. To test the state estimates, model forecasts are initialized from each the end of each monthly state estimate and use climatological forcings and boundary conditions.

CASE-STSE is being produced by Ganesh Gopalakrishnan, and the results are available from Jan 2011 till Jun 2016. This work is funded by the Climate Observations and Monitoring Program, National Oceanic and Atmospheric Administration, U.S. Department of Commerce.

Results:
CASE STSE Solutions
CCS Upwelling Indices from CASE STSE

You are encouraged to use our results, but please be aware of the disclaimer and terms of use. Some data are preliminary and may not be suited to your needs. Please do not use images from this website without permission.

Contact: Bruce Cornuelle , Ganesh Gopalakrishnan