Dynamic Data Assimilation: A Least Squares Approach

By J. M. Lewis, S. Lakshmivarahan, S. Dhall. 2006

378 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a2df81501355bb88da989b0c55ec90daecc77787

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Citations in the corpus

Fast derivatives of likelihood functionals for ODE based models using adjoint-state method (2016, methodology): “s and that of Bayesian inference is the paper (Martin et al., 2012). Meteorology is probably the ﬁeld where the relationship between differential models and stochastic processes is the most advanced (Lewis et al., 2006). The third and probably rather inﬂuential reason is that the results presented i”
Development of a Four-Dimensional Variational Assimilation System for Coastal Data Assimilation around Japan (2015, methodology): “…and numerical models to obtain the statistically best estimate of the ocean state, has been widely used for various purposes such as ocean monitoring, forecast, and reanalysis (e.g., Bennett 1992, 2002; Ghil and Malanotte-Rizzoli 1991; Wunsch 1996; Talagrand 1997; Lewis et al. 2006; Evensen 2007).”
Data assimilation for nonlinear problems by ensemble Kalman filter with reparameterization (2009, methodology): “Gaussianity of the probability density is a basic assumption for all Kalman filter based methods, so while an advantage of theMonte Carlo method is the capability of actually propagating realizations of arbitrary probability distributions, Kalman filter updating considers only the first two moments ”
Least Square Data Assimilation for Identification of the Point Source Emissions (2012, methodology): “…source from n observed concentration measurements li’s is based on minimizing the sum of square of residuals represented by the function J as (LEWIS et al. 2006): J x; qð Þ ¼ Xn i¼1 e2i ¼ Xn i¼1 li qai xð Þ½ 2; ð3Þ subject to the constraints q [ 0 and x‘ 6 x 6 xu where x = (x, y) is a…”
On the Sensitivity Equations of Four-Dimensional Variational (4D-Var) Data Assimilation (2008, methodology): “An in-depth presentation of the data assimilation techniques used in NWP may be found in the books of Jazwinski (1970), Daley (1991), Kalnay (2002), and Lewis et al. (2006).”
CONVECTIVE-SCALE WARN-ON-FORECAST SYSTEM: A vision for 2020 (2009, background): “New assimilation methodologies for use when the number of observations is larger than the numbe r of model grid points should also be evaluated (Lewis et al. 2006).”