Principles of Data Assimilation

Park, Seon Ki / Zupanski, Milija | Cambridge University Press | 2022년 9월 출판

https://www.cambridge.org/us/academic/subjects/earth-and-environmental-science/atmospheric-science-and-meteorology/principles-data-assimilation

[책 소개]

이 책은 박선기 교수(이화여대)와 Zupanski 박사(콜로라도주립대)가 각각 20여년 동안 자료동화를 강의해 온 내용을 바탕으로 출판한 학부 고학년 및 대학원생을 위한 교과서이다. 많은 예제와 응용 사례, 알고리즘 및 코드를 담고 있어 학생뿐만 아니라 자료동화 분야의 연구자들에게 참고서로도 유용하다.

    ● Includes exercises and worked examples throughout, to facilitate hands-on learning of data assimilation methods for readers

    ● Provides a unique perspective to show how practical requirements of data assimilation often impact the direction of theoretical development

    ● Introduces alternative views of data assimilation based on Shannon information theory that can benefit future development of data assimilation methods

[목차]

Part I. General Background

      1. Data assimilation: general background

      2. Probability and Bayesian approach

      3. Filters and smoothers

Part II. Practical Tools

      4. Tangent linear and adjoint model 

      5. Automatic differentiation

      6. Numerical minimization process

Part III. Methods and Issues

      7. Variational data assimilation 

      8. Ensemble and hybrid data assimilation

      9. Coupled data assimilation

      10. Dynamics and data assimilation

Part IV. Applications

      11. Sensitivity analysis and adaptive observation 

      12. Satellite data assimilation

Part V. Appendices

Appendix A Linear Algebra and Functional Analysis 

Appendix B Discretization of Partial Differential Equations 

Appendix C Lab Practice I 

Appendix D Lab Practice I 

Index

[저자 소개]

Park, Seon Ki (박선기, 이화여자대학교 기후·에너지시스템공학과 교수)

Zupanski, Milija (Senior Research Scientist, Colorado State University/CIRA, USA)