Regional and basin scale applications of ensemble adjustment Kalman filter and 4D-Var ocean data assimilation systems
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields

Dates

to

Document Data
Library
People
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Regional and basin scale applications of ensemble adjustment Kalman filter and 4D-Var ocean data assimilation systems

Filetype[PDF-2.79 MB]



Details:

  • Journal Title:
    Progress in Oceanography
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    The performance of two common approaches to data assimilation, an Ensemble Adjustment Kalman Filter (EAKF) and a 4-dimensional variational (4D-Var) method, is quantified in a popular community ocean model, the Regional Ocean Modeling Systems (ROMS). Two distinct circulation environments are considered: the California Current System (CCS), which is an eastern boundary upwelling regime, and the Indian Ocean (IO) characterized by an equatorial waveguide subject to the energetic seasonal reversals of the Indian and Asian Monsoons. In the case of the CCS, experiments were performed using synthetic observations, so-called Observing System Simulation Experiments (OSSEs). An extensive suite of CCS OSSEs were conducted to explore the performance of both data assimilation approaches to system configuration. For the EAKF, this includes the method for generating the seed ensemble, ensemble size, localization scales, and the length of the assimilation window. In the case of 4D-Var, the influence of assimilation window length, and the formulation of the background error covariance were explored. The performance of the EAKF was found to be influenced most by the size of the ensemble and by the method used to generate the initial seed ensemble where centering of the ensemble was found to yield improvement. For 4D-Var, the assimilation window length is by far the most critical factor, with an increase in system performance as the window length is extended. In general, the EAKF and 4D-Var systems converge to similar solutions over time, which are independent of the starting point. The EAKF employs a First-Guess at Appropriate Time (FGAT) strategy, and some experiments indicate that short FGAT windows can be problematic due to the introduction of frequent initialization shocks. While the EAKF generally out-performs 4D-Var in the OSSEs, analysis of the innovations from the two systems through time indicates that they track each other closely.
  • Keywords:
  • Source:
    Progress in Oceanography, 189, 102450
  • DOI:
  • ISSN:
    0079-6611
  • Format:
  • Publisher:
  • Document Type:
  • Funding:
  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Library
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files
More +

You May Also Like

Checkout today's featured content at staging-noaa.cdc.gov

Version 3.27.1