Coverart for item
The Resource Data assimilation for atmospheric, oceanic and hydrologic applications, (Vol. III), Seon Ki Park, Liang Xu, editors

Data assimilation for atmospheric, oceanic and hydrologic applications, (Vol. III), Seon Ki Park, Liang Xu, editors

Label
Data assimilation for atmospheric, oceanic and hydrologic applications, (Vol. III)
Title
Data assimilation for atmospheric, oceanic and hydrologic applications
Title number
(Vol. III)
Statement of responsibility
Seon Ki Park, Liang Xu, editors
Contributor
Editor
Subject
Language
eng
Summary
This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation
Member of
Cataloging source
N$T
Dewey number
550.015118
Index
index present
LC call number
QC809.M37
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Park, Seon Ki
  • Xu, Liang
http://library.link/vocab/subjectName
  • Earth sciences
  • Geophysics
  • Environment
  • Math. Appl. in Environmental Science
  • Calculus of Variations and Optimal Control; Optimization
  • Simulation and Modeling
  • Atmospheric Sciences
  • Oceanography
Label
Data assimilation for atmospheric, oceanic and hydrologic applications, (Vol. III), Seon Ki Park, Liang Xu, editors
Instantiates
Publication
Note
Includes index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Preface; In Memory of Yoshi; References; Reminiscences on Dr. Yoshi Sasaki; References; Photos with Prof. Sasaki and JMA's Condolences to His Wife; Yoshi's NRL Monterey Connection; Reference; Yoshi, My Mentor; Contents; Contributors; Variational Data Assimilation: Optimization and Optimal Control; 1 Introduction; 1.1 Historical Perspective; 1.2 Variational Methods in Meteorology: A Perspective; 1.3 Variational Methods in Meteorology: The Optimization Theory View Point; 2 Ingredients of a Variational Method; 2.1 Definition of a Variational Method; 3 Variational Analysis
  • 4 Optimal Control Techniques4.1 General Results; 4.2 Control of the Initial Condition; 4.3 Control of the Boundary; 5 Weak Constraints in Variational Data Assimilation; 5.1 Three Basic Methods in Constrained Optimization; 5.2 Direct Control of the Error in VDA; 5.3 Weak Constraint: Control of Systematic Error; 5.4 Example: Saint-Venant's Equations; 6 Second Order Methods; 6.1 Sensitivity analysis; 6.2 Sensitivity in the Presence of Data; 7 Sensitivity with Respect to Sources; 7.1 Identification of the Fields; 7.2 Formulation of the Sensitivity Problem; 8 Incremental Methods
  • 8.1 Description of the Method9 Developments in Variational Data Assimilation in Last 2 Decades; 9.1 Estimation of Background and Observation Error Covariances; 9.2 Observation Error Covariance; 10 Hybrid Data Assimilation; 11 Numerical Experiments; 11.1 Burgers Model; 11.2 Shallow Water Equations Model; 12 Outlook of Modern Data Assimilation Topics; 12.1 Data Assimilation Applied to Other Fields; 12.2 Further Applications of Variational Data Assimilation; References; 2 Data Assimilation for Coupled Modeling Systems; Abstract; 1 Introduction; 2 Motivation; 3 Challenges; 3.1 Control Variable
  • 3.2 Forecast Error Covariance3.3 High-Dimensional State Vector; 3.4 Non-gaussian Errors; 3.5 Spatiotemporal Scales; 4 Two-Component Coupled System Data Assimilation; 5 Structure of Coupled Forecast Error Covariance; 6 Summary and Future; Acknowledgements; References; 3 Representer-Based Variational Data Assimilation Systems: A Review; Abstract; 1 Introduction; 2 Systems; 2.1 IOM; 2.1.1 Implementation; 2.1.2 Applications; 2.2 NAVDAS-AR; 2.2.1 Implementation; 2.2.2 Applications; 2.3 NCOM 4D-Var; 2.3.1 Implementation; 2.3.2 Applications; 2.4 ROMS 4D-Var; 2.4.1 Implementation; 2.4.2 Applications
  • 3 SummaryAcknowledgements; References; Adjoint-Free 4D Variational Data Assimilation into Regional Models; 1 Introduction; 2 Variational Data Assimilation; 2.1 Adjoint Methods; 2.2 Adjoint-Free Methods; 3 a4dVar and 4dVar Assimilation of Real Data in the Adriatic Sea; 3.1 Model and Data; 3.2 Assimilation Parameters; 3.3 Comparison with 4dVar; 4 a4dVar Analysis of Simulated Wave Data in the Chukchi Sea; 4.1 The WAM Model and Simulated Data; 4.2 Comparison with Sequential Method; 5 Summary and Discussion; References
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9783319434155
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-43415-5
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
ocn967342375
Label
Data assimilation for atmospheric, oceanic and hydrologic applications, (Vol. III), Seon Ki Park, Liang Xu, editors
Publication
Note
Includes index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Preface; In Memory of Yoshi; References; Reminiscences on Dr. Yoshi Sasaki; References; Photos with Prof. Sasaki and JMA's Condolences to His Wife; Yoshi's NRL Monterey Connection; Reference; Yoshi, My Mentor; Contents; Contributors; Variational Data Assimilation: Optimization and Optimal Control; 1 Introduction; 1.1 Historical Perspective; 1.2 Variational Methods in Meteorology: A Perspective; 1.3 Variational Methods in Meteorology: The Optimization Theory View Point; 2 Ingredients of a Variational Method; 2.1 Definition of a Variational Method; 3 Variational Analysis
  • 4 Optimal Control Techniques4.1 General Results; 4.2 Control of the Initial Condition; 4.3 Control of the Boundary; 5 Weak Constraints in Variational Data Assimilation; 5.1 Three Basic Methods in Constrained Optimization; 5.2 Direct Control of the Error in VDA; 5.3 Weak Constraint: Control of Systematic Error; 5.4 Example: Saint-Venant's Equations; 6 Second Order Methods; 6.1 Sensitivity analysis; 6.2 Sensitivity in the Presence of Data; 7 Sensitivity with Respect to Sources; 7.1 Identification of the Fields; 7.2 Formulation of the Sensitivity Problem; 8 Incremental Methods
  • 8.1 Description of the Method9 Developments in Variational Data Assimilation in Last 2 Decades; 9.1 Estimation of Background and Observation Error Covariances; 9.2 Observation Error Covariance; 10 Hybrid Data Assimilation; 11 Numerical Experiments; 11.1 Burgers Model; 11.2 Shallow Water Equations Model; 12 Outlook of Modern Data Assimilation Topics; 12.1 Data Assimilation Applied to Other Fields; 12.2 Further Applications of Variational Data Assimilation; References; 2 Data Assimilation for Coupled Modeling Systems; Abstract; 1 Introduction; 2 Motivation; 3 Challenges; 3.1 Control Variable
  • 3.2 Forecast Error Covariance3.3 High-Dimensional State Vector; 3.4 Non-gaussian Errors; 3.5 Spatiotemporal Scales; 4 Two-Component Coupled System Data Assimilation; 5 Structure of Coupled Forecast Error Covariance; 6 Summary and Future; Acknowledgements; References; 3 Representer-Based Variational Data Assimilation Systems: A Review; Abstract; 1 Introduction; 2 Systems; 2.1 IOM; 2.1.1 Implementation; 2.1.2 Applications; 2.2 NAVDAS-AR; 2.2.1 Implementation; 2.2.2 Applications; 2.3 NCOM 4D-Var; 2.3.1 Implementation; 2.3.2 Applications; 2.4 ROMS 4D-Var; 2.4.1 Implementation; 2.4.2 Applications
  • 3 SummaryAcknowledgements; References; Adjoint-Free 4D Variational Data Assimilation into Regional Models; 1 Introduction; 2 Variational Data Assimilation; 2.1 Adjoint Methods; 2.2 Adjoint-Free Methods; 3 a4dVar and 4dVar Assimilation of Real Data in the Adriatic Sea; 3.1 Model and Data; 3.2 Assimilation Parameters; 3.3 Comparison with 4dVar; 4 a4dVar Analysis of Simulated Wave Data in the Chukchi Sea; 4.1 The WAM Model and Simulated Data; 4.2 Comparison with Sequential Method; 5 Summary and Discussion; References
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9783319434155
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-43415-5
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
ocn967342375

Library Locations

Processing Feedback ...