000			01863nam a22002297a 4500
003			OSt
005			20241211115637.0
008			190220b ||||| |||| 00| 0 eng d
020			_a9781611974539
040			_cSIAM _aICTS-TIFR
050			_aQA378.5
100			_aMark Asch
245			_aData assimilation _b: methods, algorithms, and applications
260			_aUSA: _bSIAM, _c[c2016]
300			_a306 p
490			_aFundamentals of Algorithms
505			_aPart I: Basic methods and algorithms for data assimilation Chapter 1: Introduction to data assimilation and inverse problems Chapter 2: Optimal control and variational data assimilation Chapter 3: Statistical estimation and sequential data assimilation Part II: Advanced methods and algorithms for data assimilation Chapter 4: Nudging methods Chapter 5: Reduced methods Chapter 6: The ensemble Kalman filter Chapter 7: Ensemble variational methods Part III: Applications and case studies Chapter 8: Applications in environmental sciences Chapter 9: Applications in atmospheric sciences Chapter 10: Applications in geosciences Chapter 11: Applications in medicine, biology, chemistry, and physical sciences Chapter 12: Applications in human and social sciences
520			_aData 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.
700			_aMarc Bocquet
700			_aMaëlle Nodet
942			_2lcc _cBK
999			_c2328 _d2328