TY - JOUR
T1 - Fast data assimilation using a nonlinear Kalman filter and a model surrogate
T2 - An application to the Columbia River estuary
AU - Frolov, Sergey
AU - Baptista, António M.
AU - Leen, Todd K.
AU - Lu, Zhegdong
AU - van der Merwe, Rudolph
N1 - Funding Information:
The National Science Foundation (ACI-0121475, OCE-0424602) and National Oceanic and Atmospheric Administration (AB133F-04-CN-0033) provided financial support for this research. Any statements, opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the federal sponsors, and no official endorsement should be inferred.
PY - 2009/10
Y1 - 2009/10
N2 - A fast and adjoint-free nonlinear data assimilation (DA) system was developed to simulate 3D baroclinic circulation in estuaries, leveraging two recently developed technologies: (1) a nonlinear model surrogate that executes forward simulation three orders of magnitude faster than a forward numerical circulation code and (2) a nonlinear extension to the reduced-dimension Kalman filter that estimates the state of the model surrogate. The noise sources in the Kalman filter were calibrated using empirical cross-validation and accounted for errors in model and model forcing. The DA system was applied to assimilate in situ measurements of water levels, salinities, and temperatures in simulations of the Columbia River estuary. To validate the DA results, we used a combination of cross-validation studies, process-oriented studies, and tests of statistical and dynamical consistency. The validation studies showed that DA improved the representation of several important processes in the estuary, including nonlinear tidal propagation, salinity intrusion, estuarine residual circulation, heat balance, and response of the estuary to coastal winds.
AB - A fast and adjoint-free nonlinear data assimilation (DA) system was developed to simulate 3D baroclinic circulation in estuaries, leveraging two recently developed technologies: (1) a nonlinear model surrogate that executes forward simulation three orders of magnitude faster than a forward numerical circulation code and (2) a nonlinear extension to the reduced-dimension Kalman filter that estimates the state of the model surrogate. The noise sources in the Kalman filter were calibrated using empirical cross-validation and accounted for errors in model and model forcing. The DA system was applied to assimilate in situ measurements of water levels, salinities, and temperatures in simulations of the Columbia River estuary. To validate the DA results, we used a combination of cross-validation studies, process-oriented studies, and tests of statistical and dynamical consistency. The validation studies showed that DA improved the representation of several important processes in the estuary, including nonlinear tidal propagation, salinity intrusion, estuarine residual circulation, heat balance, and response of the estuary to coastal winds.
KW - Coastal margin circulation
KW - Columbia River estuary
KW - Data assimilation
KW - Unstructured grid modeling
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U2 - 10.1016/j.dynatmoce.2008.10.004
DO - 10.1016/j.dynatmoce.2008.10.004
M3 - Article
AN - SCOPUS:68749116583
SN - 0377-0265
VL - 48
SP - 16
EP - 45
JO - Dynamics of Atmospheres and Oceans
JF - Dynamics of Atmospheres and Oceans
IS - 1-3
ER -