Data Assimilation: The Ensemble Kalman Filter

Data Assimilation: The Ensemble Kalman Filter

2007 | 280 Pages | ISBN: 354038300X | PDF | 12 MB

Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should be easy to follow, are given throughout the book. The codes used in several of the data assimilation experiments are available on a web page. In particular, this webpage contains a complete ensemble Kalman filter assimilation system, which forms an ideal starting point for a user who wants to implement the ensemble Kalman filter with his/her own dynamical model. The focus on ensemble methods, such as the ensemble Kalman filter and smoother, also makes it a solid reference to the derivation, implementation and application of such techniques. Much new material, in particular related to the formulation and solution of combined parameter and state estimation problems and the general properties of the ensemble algorithms, is available here for the first time.


[Fast Download] Data Assimilation: The Ensemble Kalman Filter

Ebooks related to "Data Assimilation: The Ensemble Kalman Filter" :
Image Processing and Acquisition using Python
The Technology of Binaural Listening (Modern Acoustics and Signal Processing)
Theoretical Foundations of Digital Imaging Using MATLAB
Signal Processing: A Mathematical Approach, Second Edition
Noise and Vibration Analysis: Signal Analysis and Experimental Procedures
Bootstrap Techniques for Signal Processing
Morphological Image Analysis: Principles and Applications (2nd edition)
Real-Time Digital Signal Processing: Fundamentals, Implementations and Applications, 3rd Edition
Intelligent Multimedia Data Hiding: New Directions
Digital Signal Processing Techniques and Applications in Radar Image Processing
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.