2017 / xviii + 306 pages / softcover / ISBN 978-1-611974-53-9 List Price $84.00 / SIAM Member Price $58.80 / Order Code FA11
Keywords: data assimilation, inverse problems, Kalman filters, adjoint methods, ensemble methods
Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasizing “why” and not just “how.” Methods and diagnostics are emphasized, enabling readers to readily apply them to their own field of study.
Readers will find
The core audience is advanced undergraduate and early graduate students in applied mathematics, environmental sciences, and any domain (engineering, social science, biology, etc.) that deals with inverse problems related to physical measurements. A strong potential audience is practicing researchers and engineers engaged in (partial) differential equation–based data assimilation, inverse problems, optimization, and optimal control.
About the Authors
Mark Asch is a full professor of mathematics at Université de Picardie Jules Verne. His research deals with data assimilation and inverse problems in environmental and underwater acoustics. He has taught statistics and data analysis at undergraduate and graduate levels for over 20 years. He currently leads an action theme in the Belmont Forum’s Data Management and e-Infrastructure initiative, and is a co-organizer of the BDEC (Big Data and Extreme-Scale Computing) consortium. Previously, he was program manager for Mathematics, Computer Science, HPC, and Big Data at the French National Research Agency (ANR), and prior to that, scientific officer for mathematics and e-infrastructures at the French ministry of research.
Marc Bocquet is professor, senior scientist, and deputy director of the Environment Research Center (CEREA) at École des Ponts ParisTech. He is chair of the Statistics for Analysis, Modelling and Assimilation group of the Pierre-Simon Laplace Institute (IPSL). Prior to 2002, he worked in the theoretical physics center of the University of Oxford, the physics department of the University of Warwick, and the theoretical physics institute of the French Alternative Energies and Atomic Energy Commission in Saclay. He is Associate Editor for the Quarterly Journal of the Royal Meteorological Society.
Maëlle Nodet is an associate professor in applied mathematics at Grenoble University. Her research interests are data assimilation methods, inverse problems, sensitivity analysis, control, optimal transport, and imaging applied to various geoscience fields. She is strongly involved in teaching and outreach activities, particularly in developing and promoting active, problem-based, and student-centered learning.
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