A Comparison of Variational and Ensemble-Based Data Assimilation Systems for Reanalysis of Sparse Observations

By J. Whitaker, Gilbert P. Compo, Jean-Noel Thepaut. 2009

87 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/4bb2b2fc54d50298d10e628afc274542a884be7e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. J. Whitaker
2. M. Buehner
3. Thomas M. Hamill
4. Jeffrey L. Anderson
5. Geir Evensen
6. H. Mitchell
7. C. Snyder
8. P. Houtekamer

In Global and Planetary Change

1. J. Whitaker
2. M. Buehner
3. Thomas M. Hamill
4. H. Mitchell
5. C. Snyder
6. Jeffrey L. Anderson
7. P. Houtekamer
8. Geir Evensen

Citations in the corpus

• Surface heat flux estimation with the ensemble Kalman smoother: Joint estimation of state and parameters (2012, background): “These approaches do not suffer from the VDA models deficiencies and have some unique characteristics: (1) they are much easier to formulate and employ compared to the variational techniques, (2) they directly provides statistical information on the accuracy of its estimates, (3) they can easily gene”
• Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction (2013, background): “Whitaker et al., 2009; Buehner et al., 2010a, b; Miyoshi et al., 2010; Zhang et al., 2011) perspectives.”
• The Twentieth Century Reanalysis Project (2009, methodology): “…generating reliable reanalyses of these earlier periods using only surface observations and more advanced data assimilation methods such as the Ensemble Kalman Filter (Whitaker et al., 2004; Anderson et al., 2005; Compo et al., 2006) or 4D-Var assimilation (Thépaut, 2006; Whitaker et al., 2009).”
• Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part I: Description and Single-Observation Experiments (2010, result): “Yang et al. (2009) compared the LETKF with 3D-Var and 4D-Var in idealized experiments with a quasigeostrophic Unauthenticated | Downloaded 11/22/21 02:20 AM UTC model and also obtained similar quality results from the 4D-Var and LETKF, which were both better than those obtained with 3D-Var.”