Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
Published on 23. August 2016
Book
Paperback/Softback
XIX, 730 pages
978-3-662-51023-0 (ISBN)
Description
This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
More details
Edition
Softcover reprint of the original 1st ed. 2013
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Illustrations
99 s/w Abbildungen, 170 farbige Abbildungen
XIX, 730 p. 269 illus., 170 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 38 mm
Weight
1255 gr
ISBN-13
978-3-662-51023-0 (9783662510230)
DOI
10.1007/978-3-642-35088-7
Schweitzer Classification
Other editions
Additional editions
SEON KI PARK | Liang Xu
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
Book
06/2013
Springer
€213.99
Shipment within 7-9 days
Content
A Review on the Theory and Methodologies of Estimation for Dynamical Systems.- Nudging Methods: A Critical Overview.- Markov Chain Monte Carlo Methods: Theory and Applications.- Information Content in Data Assimilation.- A Question of Adequacy of Observations in Variational Data Assimilation.- Quantifying Observation Impact for a Limited Area Atmospheric Forecast Model.- Skewness of the Prior through Position Errors and Its Impact on Data Assimilation.- Background Error Correlation Modeling with Diffusion Operator.- The Adjoint Sensitivity Guidance to Diagnosis and Tuning of Error Covariance Parameters.- Treating Nonlinearities in Data-Space Variational Assimilation.- Linearized Physics for Data Assimilation at ECMWF.- Recent Applications in Representer-Based Variational Data Assimilation.