scholarly journals Application of a data-assimilation model to variability of Pacific sardine spawning and survivor habitats with ENSO in the California Current System

2012 ◽  
Vol 117 (C3) ◽  
pp. n/a-n/a ◽  
Author(s):  
Hajoon Song ◽  
Arthur J. Miller ◽  
Sam McClatchie ◽  
Edward D. Weber ◽  
Karen M. Nieto ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Current System ◽  
California Current ◽  
California Current System ◽  
Pacific Sardine ◽  
Assimilation Model

Data assimilation of physical and chlorophyll a observations in the California Current System using two biogeochemical models

2017 ◽  
Vol 109 ◽  
pp. 55-71 ◽  
Author(s):  
Jann Paul Mattern ◽  
Hajoon Song ◽  
Christopher A. Edwards ◽  
Andrew M. Moore ◽  
Jerome Fiechter
Keyword(s):  
Data Assimilation ◽  
Chlorophyll A ◽  
Current System ◽  
California Current ◽  
California Current System ◽  
Biogeochemical Models

Application of 4D-Variational data assimilation to the California Current System

2009 ◽  
Vol 48 (1-3) ◽  
pp. 69-92 ◽  
Author(s):  
G. Broquet ◽  
C.A. Edwards ◽  
A.M. Moore ◽  
B.S. Powell ◽  
M. Veneziani ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Current System ◽  
California Current ◽  
Variational Data Assimilation ◽  
California Current System

scholarly journals Weak constraint four-dimensional variational data assimilation in a model of the California Current System

2016 ◽  
Vol 2 (2) ◽  
pp. 171-192 ◽  
Author(s):  
William J. Crawford ◽  
Polly J. Smith ◽  
Ralph F. Milliff ◽  
Jerome Fiechter ◽  
Christopher K. Wikle ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Ocean Circulation ◽  
Hierarchical Modeling ◽  
Current System ◽  
California Current ◽  
Model Errors ◽  
Strong Constraint ◽  
California Current System ◽  
Twin Model ◽  
Error Covariance

Abstract. A new approach is explored for computing estimates of the error covariance associated with the intrinsic errors of a numerical forecast model in regions characterized by upwelling and downwelling. The approach used is based on a combination of strong constraint data assimilation, twin model experiments, linear inverse modeling, and Bayesian hierarchical modeling. The resulting model error covariance estimates Q are applied to a model of the California Current System using weak constraint four-dimensional variational (4D-Var) data assimilation to compute estimates of the ocean circulation. The results of this study show that the estimates of Q derived following our approach lead to demonstrable improvements in the model circulation estimates and isolate regions where model errors are likely to be important and that have been independently identified in the same model in previously published work.

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