Variational Assimilation of Meteorological Observations With the Adjoint Vorticity Equation. I: Theory

By O. Talagrand, P. Courtier. 2007

715 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/366f189322f3e5da5e0c3f5faffb74e3af043109

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Citations in the corpus

An adaptive covariance inflation error correction algorithm for ensemble filters (2007, methodology): “Variational methods (Le Dimet and Talagrand, 1986; Talagrand and Courtier, 1987; Derber, 1989), on the other hand, continue to require significant expert knowledge for the development of tangent linear and adjoint versions of models and forward observation operators (Geiring et al., 2005).”
Data Assimilation for Numerical Weather Prediction: A Review (2009, methodology): “Penenko and Obratsov (1976) used adjoint data assimilation to perform simple experiments on a linear model (see Talagrand and Courtier 1987), while Derber (1985) used it in his Ph.”
Finite-frequency sensitivity kernels for global seismic wave propagation based upon adjoint methods (2008, methodology): “Adjoint methods have been popular in the fields of meteorology and exploration geophysics for many years (e.g. Chavent et al. 1975; Tarantola 1984; Gauthier et al. 1986; Mora 1987, 1988; Talagrand & Courtier 1987; Luo & Schuster 1991).”
Seismic tomography of the southern California crust based on spectral‐element and adjoint methods (2010, methodology): “This approach has been utilized in many studies (e.g. Chavent et al. 1975; Bamberger et al. 1982; McMechan 1982; Talagrand & Courtier 1987).”
Spectral-Element and Adjoint Methods in Seismology (2008, neutral): “[60] generalized the calculation of the derivative of a misfit function by introducing the concept of an ‘adjoint’ calculation.”
Seismic imaging: From classical to adjoint tomography (2012, methodology): “…by computational advancement, and potentially inspired by the success of adjoint methods in meteorological (e.g., Courtier and Talagrand, 1987; Talagrand and Courtier, 1987) and geodynamical (e.g., Bunge et al., 2003) applications, (Tromp et al., 2005) made important connections among…”
Lagrangian data assimilation for river hydraulics simulations (2006, positive): “Variational data assimilation [15,24] is based on optimal control theory [17] and consists in identifying the con-trol vector k that minimizes a cost function measuring the discrepancy between the state variable of the model and data obtained from the observation of the physical system.”
A review of operational methods of variational and ensemble‐variational data assimilation (2017, methodology): “Var has been the workhorse of DA for many years (Le Dimet and Talagrand, 1986; Talagrand and Courtier, 1987; Thepaut and Courtier, 1991; Zupanski, 1997; Rabier et al., 2000; Rawlins et al., 2007).”
Beyond Gaussian Statistical Modeling in Geophysical Data Assimilation (2010, methodology): “The gradient of the cost function to be minimized can be efficiently computed by optimal control techniques (Le Dimet and Talagrand 1986; Talagrand and Courtier 1987; Courtier and Talagrand 1987).”