GFDL Ocean Data Assimilation Experiment

GFDL ODA: An improved ocean state product

The main goal of the Ocean Data Assimilation Experiment project is to develop a state-of-the-art data assimilation system that incorporates near-realtime data with which they can provide the community a high quality ocean state product. This assimilation system consists of an Ensemble Filter applied to GFDL's second generation fully coupled climate model (CM2.1, Delworth et al. [2006]). The ocean component of the coupled data assimilation (CDA) is the fourth version of the Modular Ocean Model (MOM4, Griffies et al. [2004]) configured with 50 vertical levels (22 levels of 10-m thickness each in the top 220 m) and 1 horizontal B-grid resolution, telescoping to 1/3 meridional spacing by 1 near the equator. For more information please see their website (http://www.gfdl.noaa.gov/ocean-data-assimilation).

ECDA v3.1: Monthly Ensemble Means (ECDA) v3.1 1961-2012 This version is being used to produce the initial conditions for IPCC/AR5 near-term predictions.

ECDA v2.0 Monthly Ensemble Means (ECDA) v2.0 1979-2007 Data provided here are interpolated onto a latitude/longitude grid. The provider offers data on their native tripolar grid.

Recent Publications:
  Chang, Y.-S., S. Zhang, A. Rosati, T. Delworth, and W. F. Stern, March 2012: An assessment of oceanic variability for 1960-2010 from the GFDL ensemble coupled data assimilation, Climate Dynamic, Accepted.
  Zhang, Shaoqing, M. Winton, A. Rosati, T. Delworth and B. Huang, 2012: Impact of Enthalpy-Based Ensemble Filtering Sea-Ice Data Assimilation on Decadal Predictions: Simulation with a Conceptual Pycnocline Prediction Model. Journal of Climate. in press.
  Chang, Y-S, Anthony Rosati, and Shaoqing Zhang, February 2011: A construction of pseudo salinity profiles for the global ocean: Method and evaluation. Journal of Geophysical Research, 116, C02002, DOI:10.1029/2010JC006386.
  Chang, Y-S, Shaoqing Zhang, and Anthony Rosati, July 2011: Improvement of salinity representation in an ensemble coupled data assimilation system using pseudo salinity profiles. Geophysical Research Letters, 38, L13609, DOI:10.1029/2011GL048064.
  Zhang, Shaoqing, January 2011: Impact of observation-optimized model parameters on decadal predictions: Simulation with a simple pycnocline prediction model. Geophysical Research Letters, 38, L02702, DOI:10.1029/2010GL046133.
  Zhang, Shaoqing, Z Liu, Anthony Rosati, and Thomas L Delworth, January 2012: A study of enhancive parameter correction with coupled data assimilation for climate estimation and prediction using a simple coupled model. Tellus A, 64, 10963, DOI:10.3402/tellusa.v64i0.10963. PDF
  Zhang, Shaoqing, January 2011: Impact of observation-optimized model parameters on decadal predictions: Simulation with a simple pycnocline prediction model. Geophysical Research Letters, 38, L02702, DOI:10.1029/2010GL046133.
  Zhang, Shaoqing, December 2011:A study of impacts of coupled model initial shocks and state-parameter optimization on climate predictions using a simple pycnocline prediction model. Journal of Climate, 24(23), DOI:10.1175/JCLI-D-10-05003.1. PDF

Variables
mixed layer depth (m), precipitation minus evaporation (m s-1), river water flux (m s-1) , surface heat flux (W m-2), salinity (psu), zonal wind stress (N m-2), meridional wind stress (N m-2), potential temperature (K), eastward sea water velocity (m s-1), northward sea water velocity (m s-1), upward Sea water velocity (m s-1) [ECDA v2.0 only]
Zonal Global by 1 deg
Meridional 81.5S to 89.5N by varies; 1 or less
Vertical T, S, U & V on 50 levels:5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 155 165 175 185 195 205 215 225 236.1 250.6 270.6 298.3 335.7 384.6 446.9 524.2 617.7 728.8 858.4 1007.3 1175.8 1364.4 1573 1801.3 2048.8 2314.9 2598.5 2898.4 3213.2 3541.3 3881.2 4230.6 4587.7 4950.4 5316.4  
Temporal v3.1: Jan 1961 to Dec 2010 by 1 month ; v2.0: Jan 1979 to Dec 2007 by 1 month
Static? yes
Volume 288 Kb / month / level
Server public:
Source http://www.gfdl.noaa.gov/ocean-data-assimilation 
Acquired Nov 12, 2013
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