Articles | Volume 15, issue 4
Nonlin. Processes Geophys., 15, 503–521, 2008

Special issue: Predictability in Earth Sciences

Nonlin. Processes Geophys., 15, 503–521, 2008

  01 Jul 2008

01 Jul 2008

Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF

A. Carrassi1,2, A. Trevisan3, L. Descamps4, O. Talagrand4, and F. Uboldi5 A. Carrassi et al.
  • 1Royal Meteorological Institute of Belgium – RMI, Bruxelles, Belgium
  • 2Dept. of Physics – University of Ferrara, Ferrara, Italy
  • 3Istituto di Scienze dell'Atmosfera e del Clima (ISAC) – Consiglio Nazionale delle Ricerche (CNR), Largo Gobetti 101, Bologna, Italy
  • 4Laboratoire de Météorologie Dynamique, École Normale Supérieure, Paris, France
  • 5Consultant, Novate Milanese, Italy

Abstract. A hybrid scheme obtained by combining 3DVar with the Assimilation in the Unstable Subspace (3DVar-AUS) is tested in a QG model, under perfect model conditions, with a fixed observational network, with and without observational noise. The AUS scheme, originally formulated to assimilate adaptive observations, is used here to assimilate the fixed observations that are found in the region of local maxima of BDAS vectors (Bred vectors subject to assimilation), while the remaining observations are assimilated by 3DVar. The performance of the hybrid scheme is compared with that of 3DVar and of an EnKF. The improvement gained by 3DVar-AUS and the EnKF with respect to 3DVar alone is similar in the present model and observational configuration, while 3DVar-AUS outperforms the EnKF during the forecast stage. The 3DVar-AUS algorithm is easy to implement and the results obtained in the idealized conditions of this study encourage further investigation toward an implementation in more realistic contexts.