Articles | Volume 21, issue 4
Nonlin. Processes Geophys., 21, 745–762, 2014
https://doi.org/10.5194/npg-21-745-2014

Special issue: Ensemble methods in geophysical sciences

Nonlin. Processes Geophys., 21, 745–762, 2014
https://doi.org/10.5194/npg-21-745-2014

Research article 14 Jul 2014

Research article | 14 Jul 2014

Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM)

N. Gustafsson1 and J. Bojarova2 N. Gustafsson and J. Bojarova
  • 1Swedish Meteorological and Hydrological Institute, 60176 Norrköping, Sweden
  • 2Norwegian Meteorological Institute, P.O. Box 43 Blindern, 0313 Oslo, Norway

Abstract. A four-dimensional ensemble variational (4D-En-Var) data assimilation has been developed for a limited area model. The integration of tangent linear and adjoint models, as applied in standard 4D-Var, is replaced with the use of an ensemble of non-linear model states to estimate four-dimensional background error covariances over the assimilation time window. The computational costs for 4D-En-Var are therefore significantly reduced in comparison with standard 4D-Var and the scalability of the algorithm is improved.

The flow dependency of 4D-En-Var assimilation increments is demonstrated in single simulated observation experiments and compared with corresponding increments from standard 4D-Var and Hybrid 4D-Var ensemble assimilation experiments. Real observation data assimilation experiments carried out over a 6-week period show that 4D-En-Var outperforms standard 4D-Var as well as Hybrid 4D-Var ensemble data assimilation with regard to forecast quality measured by forecast verification scores.