http://www.cnr.it/ontology/cnr/individuo/prodotto/ID45104
Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF (Articolo in rivista)
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- Label
- Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF (Articolo in rivista) (literal)
- Anno
- 2008-01-01T00:00:00+01:00 (literal)
- Alternative label
Carrassi A., Trevisan A., Descamps L., Talagrand O., Uboldi F. (2008)
Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF
in Nonlinear processes in geophysics
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Carrassi A., Trevisan A., Descamps L., Talagrand O., Uboldi F. (literal)
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- Rivista
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- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- ISAC-CNR Bologna
Royal Meteorological Institute of Belgium
Laboratoire de Meteorologie Dynamique, Ecole Normale Superieure, Paris
(literal)
- Titolo
- Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF (literal)
- 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. (literal)
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