Advanced Data Assimilation for Geosciences
Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012
Series: Lecture Notes of the Les Houches Summer School;
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Product details:
- Publisher OUP Oxford
- Date of Publication 30 October 2014
- ISBN 9780198723844
- Binding Hardback
- No. of pages608 pages
- Size 254x186x35 mm
- Weight 1340 g
- Language English
- Illustrations 169 b/w illustrations 0
Categories
Short description:
This book gathers notes from lectures given during a three-week summer school on the fundamentals and the most recent developments of geophysical data assimilation.
MoreLong description:
Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography, atmospheric chemistry, and extensions to other geophysical sciences. The physical complexity and the high dimensionality of geophysical systems have led the community of geophysics to make significant contributions to the fundamental theory of data assimilation.
This book gathers notes from lectures and seminars given by internationally recognized scientists during a three-week school held in the Les Houches School of physics in 2012, on theoretical and applied data assimilation. It is composed of (i) a series of main lectures, presenting the fundamentals of the most commonly used methods, and the information theory background required to understand and evaluate the role of observations; (ii) a series of specialized lectures, addressing various aspects of data assimilation in detail, from the most recent developments of the theory to the specificities of various thematic applications.
Overall, this is a well-edited, timely book, and all science and engineering libraries should order a copy for their students and researchers.
Table of Contents:
PART I - KEY LECTURES
4D-VAR: four dimensional variational assimilation
Four-dimensional variational data assimilation
Introduction to the Kalman filter
Smoothers
Observation influence diagnostic of a data assimilation system
Observation impact on the short range forecast
PART II - SPECIALIZED LECTURES
Background error covariances: estimation and specification
Observation error specifications
Errors. A posteriori diagnostics
Error dynamics in ensemble Kalman filter systems: Localization
Short-range error statistics in an ensemble Kalman filter
Error dynamics in ensemble Kalman filter systems: System error
Particle filters for the geosciences
Second order methods for error propagation in variational data assimilation
Adjoints by automatic differentiation
Assimilation of images
Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation
Selected topics in multiscale data assimilation
Data assimilation in meteorology
An introduction to inverse modelling and parameter estimation for atmospheric and oceanic sciences
Greenhouse gas fluxes inversion
Data assimilation in atmospheric chemistry and air quality
Combining models and data in large-scale oceanography: examples from the consortium for Estimating the Circulation and Climate of the Ocean (ECCO)
Data assimilation in coastal oceanography: IS4DVAR in the Regional Ocean Modeling System (ROMS)
Data assimilation in glaciology
