Principles of Data Assimilation
Principles of Data Assimilation
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Summary
Based on over twenty years of teaching courses in data assimilation, this textbook is for advanced students and early career researchers in meteorology, oceanography, hydrology, environmental science, and atmospheric science. It offers a new perspective on data assimilation based on a unique combination of practical and theoretical aspects.
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Principles of Data Assimilation by Seon Ki Park
Data assimilation is theoretically founded on probability, statistics, control theory, information theory, linear algebra, and functional analysis. At the same time, data assimilation is a very practical subject, given its goal of estimating the posterior probability density function in realistic high-dimensional applications. This puts data assimilation at the intersection between the contrasting requirements of theory and practice. Based on over twenty years of teaching courses in data assimilation, Principles of Data Assimilation introduces a unique perspective that is firmly based on mathematical theories, but also acknowledges practical limitations of the theory. With the inclusion of numerous examples and practical case studies throughout, this new perspective will help students and researchers to competently interpret data assimilation results and to identify critical challenges of developing data assimilation algorithms. The benefit of information theory also introduces new pathways for further development, understanding, and improvement of data assimilation methods.
Seon Ki Park is Professor of Meteorology at Ewha Womans University, Seoul, Korea. His research focuses on storm-scale to meso-scale analysis, parameter estimation, and data assimilation to improve numerical weather and climate prediction. He co-edited a series of four volumes titled Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (2009, 2013, 2017, 2021). Milija Zupanski is Senior Research Scientist at Colorado State University, Fort Collins. He is a principal developer of two four-dimensional variational data assimilation systems and the Maximum Likelihood Ensemble Filter. His research focuses on data assimilation development and applications, including the atmosphere, land surface, aerosols, and combustion.
| SKU | Unavailable |
| ISBN 13 | 9781108831765 |
| ISBN 10 | 1108831761 |
| Title | Principles of Data Assimilation |
| Author | Seon Ki Park |
| Condition | Unavailable |
| Publisher | Cambridge University Press |
| Year published | 2022-09-29 |
| Number of pages | 400 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |