Call number:
19/M 10.0111
Description / Table of Contents:
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.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.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. Table of contens: ntroduction.- Statistical definitions.- Analysis scheme.- Sequential data assimilation.- Variational inverse problems.- Nonlinear variational inverse problems.- Probabilistic formulation.- Generalized Inverse.- Ensemble methods.- Statistical optimization.- Sampling strategies for the EnKF.- Model errors.- Square root analysis schemes.- Rank issues.- An ocean prediction system.- Estimation in an oil reservoir simulator.- Other EnKF issues.
Type of Medium:
Monograph available for loan
Pages:
X, 279 S.
,
11 schw.-w. Ill., 52 farb. Ill., 1 farb. Fotos, 11 schw.-w. graph. Darst., 51 farb. graph. Darst., 7 schw.-w. Tab
,
235 mm x 155 mm
Edition:
2nd ed.
ISBN:
9783642037108
Classification:
Mathematics
Note:
Erscheinungsjahr in Vorlageform:2009
Location:
Reading room
Branch Library:
GFZ Library
