Ensemble of Data Assimilations - EDA

An Ensemble of Data Assimilations (EDA) is an ensemble of independent 4D-Var data assimilations which aims to:

The EDA analyses are generated by randomly perturbing the main analysis error sources according to their estimated accuracy:

Differences between pairs of analyses (and forecast) fields have the statistical characteristics of analysis (and forecast) error. 


Fig511.A: An idealized schematic showing how the 12 hour assimilation window used by 4D-Var (left part of the diagram) modifies the initial trajectories of the members of the ensemble of data assimilations EDA (in blue) to reflect the information from the assimilated observations (black dots with error bars).  The analysis trajectories (in green) have taken into account the new observations and thus are confined within a narrower ensemble.  Assimilating the new observations reduces the spread.  Also a bias has been corrected by reducing the magnitude of some of the largest values in the original ensemble.


At the end of the assimilation window the ensemble of data assimilations EDA is used to provide:

The advantages of the ensemble of data assimilations EDA system are:

A disadvantage of the current ensemble of data assimilations EDA system is:

Additional Sources of Information

(Note: In older material there may be references to issues that have subsequently been addressed)