An ensemble adjustment Kalman filter for data assimilation
JL Anderson - Monthly weather review, 2001 - journals.ametsoc.org
A theory for estimating the probability distribution of the state of a model given a set of
observations exists. This nonlinear filtering theory unifies the data assimilation and …
observations exists. This nonlinear filtering theory unifies the data assimilation and …
Model error representation in an operational ensemble Kalman filter
PL Houtekamer, HL Mitchell… - Monthly Weather …, 2009 - journals.ametsoc.org
Abstract Since 12 January 2005, an ensemble Kalman filter (EnKF) has been used
operationally at the Meteorological Service of Canada to provide the initial conditions for the …
operationally at the Meteorological Service of Canada to provide the initial conditions for the …
[HTML][HTML] Constraining chaos: Enforcing dynamical invariants in the training of reservoir computers
Drawing on ergodic theory, we introduce a novel training method for machine learning
based forecasting methods for chaotic dynamical systems. The training enforces dynamical …
based forecasting methods for chaotic dynamical systems. The training enforces dynamical …
On the equivalence between Kalman smoothing and weak‐constraint four‐dimensional variational data assimilation
The fixed‐interval Kalman smoother produces optimal estimates of the state of a system over
a time interval, given observations over the interval, together with a prior estimate of the state …
a time interval, given observations over the interval, together with a prior estimate of the state …
Comparison of local ensemble transform Kalman filter, 3DVAR, and 4DVAR in a quasigeostrophic model
Local ensemble transform Kalman filter (LETKF) data assimilation, three-dimensional
variational data assimilation (3DVAR), and four-dimensional variational data assimilation …
variational data assimilation (3DVAR), and four-dimensional variational data assimilation …
Treating strong adjoint sensitivities in tropical eddy‐permitting variational data assimilation
A variational data assimilation system has been implemented for the tropical Pacific Ocean
using an eddy‐permitting regional implementation of the MITgcm. The adjoint assimilation …
using an eddy‐permitting regional implementation of the MITgcm. The adjoint assimilation …
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks
Drawing on ergodic theory, we introduce a novel training method for machine learning
based forecasting methods for chaotic dynamical systems. The training enforces dynamical …
based forecasting methods for chaotic dynamical systems. The training enforces dynamical …
Bred vectors of the Zebiak–Cane model and their potential application to ENSO predictions
The breeding method is used to obtain the bred vectors (BV) of the Zebiak–Cane (ZC)
atmosphere–ocean coupled model. Bred vectors represent a nonlinear, finite-time extension …
atmosphere–ocean coupled model. Bred vectors represent a nonlinear, finite-time extension …
Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing non-linearity
We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR
with respect to two traditional methods (4DVAR and ETKF) and an ensemble transform …
with respect to two traditional methods (4DVAR and ETKF) and an ensemble transform …
Variational assimilation
O Talagrand - Data assimilation: making sense of observations, 2010 - Springer
The expression variational assimilation designates a class of assimilation algorithms in
which the fields to be estimated are explicitly determined as minimizers of a scalar function …
which the fields to be estimated are explicitly determined as minimizers of a scalar function …