DATA ASSIMILATION
341
odels’ large dimension and their
com
eir application. However, existing
pro
sensible
(ide
Although methods of data assimilation are well known, their
implementation is often hampered by the m
plex nonlinearities. Many approximations have been put forth that
render their implementation feasible and practical. The near real-time
assimilation system of the Consortium for “Estimating the Circulation and
Climate of the Ocean” (ECCO) employs a hierarchy of such approximations
to maximize utilization of observations.
The fidelity and scope of these and other analyses lend themselves to
various studies in ocean circulation and th
ducts are in certain respects yet incomplete. The present near real-time
ECCO estimates utilize a simplification by only estimating errors resulting
from uncertainties in wind forcing. Other ECCO estimates also estimate
errors in diabatic forcing and uncertainties in some of the model parameters.
However, there are many other model error sources that have not yet been
addressed. Expanding the estimated suite of process noise remains a central
task in further improving ECCO and other assimilation estimates.
For the approximate Kalman filter and RTS smoother, such extension
requires an explicit modeling of the process noise that is physically
ntification of operator G in Eq 1) and in identifying an effective
approximation (partition and state reduction operators and basis set B and B
in Eq 32) that would resolve the corresponding errors in the model state. An
effective basis set not only has a small dimension but must also form
closed dynamic system (Eq 31 approximated as Eq 32). Understanding the
nature of the modeled system is imperative to such design.
a
on of the Consortium for Estimating the Circulation
nd Climate of the Ocean (ECCO) funded by the National Oceanographic
References
. E. Davis, and C. B. Fandry, 1976: A technique for objective analysis and
graphic experiments applied to MODE-73, Deep-Sea Res., 23, 559-582.
7.
This study is a contributi
a
Partnership Program. This work was carried out in part at the Jet Propulsion
Laboratory (JPL), California Institute of Technology, under contract with the
National Aeronautics and Space Administration.
Bretherton, F. P., R
design of oceano
Cane, M. A., 1984: Modeling sea level during El Niño, J. Phys. Oceanogr, 14, 1864-1874.
Cohn, S. E., 1997: An introduction to estimation theory, J. Met. Soc. Japan, 75, 257-288.
ess
Dickey, J. O., S. L. Marcus, O. de Viron, and I. Fukumori, 2002: Recent Earth oblaten
7
variations: Unraveling climate and postglacial rebound effects, Science, 298, 1975-19
Acknowledgements
341
odels’ large dimension and their
com
eir application. However, existing
pro
sensible
(ide
Although methods of data assimilation are well known, their
implementation is often hampered by the m
plex nonlinearities. Many approximations have been put forth that
render their implementation feasible and practical. The near real-time
assimilation system of the Consortium for “Estimating the Circulation and
Climate of the Ocean” (ECCO) employs a hierarchy of such approximations
to maximize utilization of observations.
The fidelity and scope of these and other analyses lend themselves to
various studies in ocean circulation and th
ducts are in certain respects yet incomplete. The present near real-time
ECCO estimates utilize a simplification by only estimating errors resulting
from uncertainties in wind forcing. Other ECCO estimates also estimate
errors in diabatic forcing and uncertainties in some of the model parameters.
However, there are many other model error sources that have not yet been
addressed. Expanding the estimated suite of process noise remains a central
task in further improving ECCO and other assimilation estimates.
For the approximate Kalman filter and RTS smoother, such extension
requires an explicit modeling of the process noise that is physically
ntification of operator G in Eq 1) and in identifying an effective
approximation (partition and state reduction operators and basis set B and B
in Eq 32) that would resolve the corresponding errors in the model state. An
effective basis set not only has a small dimension but must also form
closed dynamic system (Eq 31 approximated as Eq 32). Understanding the
nature of the modeled system is imperative to such design.
a
on of the Consortium for Estimating the Circulation
nd Climate of the Ocean (ECCO) funded by the National Oceanographic
References
. E. Davis, and C. B. Fandry, 1976: A technique for objective analysis and
graphic experiments applied to MODE-73, Deep-Sea Res., 23, 559-582.
7.
This study is a contributi
a
Partnership Program. This work was carried out in part at the Jet Propulsion
Laboratory (JPL), California Institute of Technology, under contract with the
National Aeronautics and Space Administration.
Bretherton, F. P., R
design of oceano
Cane, M. A., 1984: Modeling sea level during El Niño, J. Phys. Oceanogr, 14, 1864-1874.
Cohn, S. E., 1997: An introduction to estimation theory, J. Met. Soc. Japan, 75, 257-288.
ess
Dickey, J. O., S. L. Marcus, O. de Viron, and I. Fukumori, 2002: Recent Earth oblaten
7
variations: Unraveling climate and postglacial rebound effects, Science, 298, 1975-19
Acknowledgements