University of Oxford, World Scientific Publishing, Singapore,
London, 2000, 253 pp. - ISBN 981-02-2740-X
This book is aimed at graduate students and at post-doctoral and other researchers who need to solve inverse problems for atmospheric measurements. The intention is both to provide a well-founded background to the inverse problem and its solution, with which the student will develop a good intuition about the nature of the problem, and to give practical recipes for solving real problems. It has developed from various courses that I have given over many years, including informal seminars.
The usual approach to solving an atmospheric retrieval problem will consist of several stages: design a forward model to describe the instrument and the physics of the measurement; determine the criterion by which a solution is acceptable as valid; construct a numerical method to find a solution which satisfies the criterion; carry out an error analysis; validate the process by reference to inteal diagnostics and independent measurements; and finally attempt to understand how the result obtained is related to reality and examine how much information has been obtained.
Contents.
Preface.
Introduction.
Information Aspects.
Error Analysis and Characterisation.
Optimal Linear Inverse Methods.
Optimal Methods for Non-linear Inverse Problems.
Approximations, Short Cuts and Ad-hoc Methods.
The Kalman Filter.
Global Data Assimilation.
Numerical Methods for Forward Models and Jacobians.
Construction and Use of Prior Constraints.
Designing an Observing System.
Testing and Validating an Observing System.
Appendices. Bibliography. Index
This book is aimed at graduate students and at post-doctoral and other researchers who need to solve inverse problems for atmospheric measurements. The intention is both to provide a well-founded background to the inverse problem and its solution, with which the student will develop a good intuition about the nature of the problem, and to give practical recipes for solving real problems. It has developed from various courses that I have given over many years, including informal seminars.
The usual approach to solving an atmospheric retrieval problem will consist of several stages: design a forward model to describe the instrument and the physics of the measurement; determine the criterion by which a solution is acceptable as valid; construct a numerical method to find a solution which satisfies the criterion; carry out an error analysis; validate the process by reference to inteal diagnostics and independent measurements; and finally attempt to understand how the result obtained is related to reality and examine how much information has been obtained.
Contents.
Preface.
Introduction.
Information Aspects.
Error Analysis and Characterisation.
Optimal Linear Inverse Methods.
Optimal Methods for Non-linear Inverse Problems.
Approximations, Short Cuts and Ad-hoc Methods.
The Kalman Filter.
Global Data Assimilation.
Numerical Methods for Forward Models and Jacobians.
Construction and Use of Prior Constraints.
Designing an Observing System.
Testing and Validating an Observing System.
Appendices. Bibliography. Index