Abstract
Sequential data assimilation methods have proven useful for many applications in meteorology and oceanography. For example are most operational weather prediction systems applying a sequential data assimilation technique where observations are “assimilated” into the model whenever they are available.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Evensen, G. (2002). Sequential Data Assimilation for Nonlinear Dynamics: The Ensemble Kalman Filter. In: Pinardi, N., Woods, J. (eds) Ocean Forecasting. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-22648-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-662-22648-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-08754-7
Online ISBN: 978-3-662-22648-3
eBook Packages: Springer Book Archive