Impact of the Digital Filter as a Weak Constraint in the Preoperational 4DVAR Assimilation System of Météo-France
By Pierre Gauthier, Jean-Noel Thepaut. 2001
170 citations recorded by the source corpus.
Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/3fb940be6b8dfa669fcffc713c4580b846d6169a
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Citations in the corpus
- Four-Dimensional Variational Data Assimilation for WRF : Formulation and Preliminary Results (2009, methodology): “Following ECMWF, several operational centers implemented 4D-Var in their operational applications, including Meteo-France ( Gauthier and Thepaut 2001 ), the Met Office (Lorenc and Rawlins 2005; Rawlins et al. 2007), the Japan Meteorological Agency (Honda et al. 2005), and Environment Canada (Gauthie”
- The potential of high‐density observations for numerical weather prediction: A study with simulated observations (2003, methodology): “In addition, an incremental digital- lter initialization (Lynch et al. 1997; Gauthier and Thépaut 2001) is used to remove spurious gravity waves.”
- The potential of the ensemble Kalman filter for NWP—a comparison with 4D‐Var (2003, methodology): “In variational assimilation methods, balance is usually introduced through additional ‘slow’ penalties (Gauthier and Thépaut 2001), or explicitly through the design of the covariance model.”
- The ERA5 global reanalysis (2020, background): “For simplicity in Equation (4), one term with minor effect, Jc, has been omitted; this is a digital filter for reducing gravity waves in the increments (Gauthier and Thépaut, 2001).”
- Data Assimilation for Numerical Weather Prediction: A Review (2009, methodology): “…numerical weather prediction centers starting with European Centre for MediumRange Weather Forecasts (ECMWF), (Rabier et al. 2000; Klinker et al. 2000) while a similar system was operational at Meteo-France in 2000 (Janiskova et al. 1999; Gauthier and Thepaut 2001; Desroziers et al. 2003).”