Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Subscribe and save

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Buy Now

eBook EUR 160.49

Softcover Book EUR 210.99

Hardcover Book EUR 210.99

Tax calculation will be finalised at checkout

Other ways to access

About this book

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.

Similar content being viewed by others

Acoustic Data Assimilation: Concepts and Examples

Ocean Wave Modeling from Satellite Images Using Data Assimilation

OpenDA-NEMO framework for ocean data assimilation

Keywords

• Data Assimilation
• Variational Method
• Adjoint Method
• Sensitivity Analysis
• Kalman Filter
• Monte Carlo Method
• Targeting Observation

Table of contents (24 chapters)

Front Matter

Variational Data Assimilation: Optimization and Optimal Control

• François-Xavier Le Dimet, Ionel M. Navon, Răzvan Ştefănescu

Data Assimilation for Coupled Modeling Systems

• Milija Županski

Representer-Based Variational Data Assimilation Systems: A Review

• Boon S. Chua, Liang Xu

Adjoint-Free 4D Variational Data Assimilation into Regional Models

• M. Yaremchuk, P. Martin, G. Panteleev, C. Beattie, A. Koch

Convergence of a Class of Weak Solutions to the Strong Solution of a Linear Constrained Quadratic Minimization Problem: A Direct Proof Using Matrix Identities

• S. Lakshmivarahan

Information Quantification for Data Assimilation

• Sarah King, Wei Kang, Liang Xu, Nancy L. Baker

Quantification of Forecast Uncertainty and Data Assimilation Using Wiener’s Polynomial Chaos Expansion

• Junjun Hu, S. Lakshmivarahan, John M. Lewis

The Treatment, Estimation, and Issues with Representation Error Modelling

• Daniel Hodyss, Elizabeth Satterfield

Soil Moisture Data Assimilation

• Viviana Maggioni, Paul R. Houser

Surface Data Assimilation and Near-Surface Weather Prediction over Complex Terrain

• Zhaoxia Pu

Recent Developments in Bottom Topography Mapping Using Inverse Methods

• Edward D. Zaron

The Impact of Doppler Wind Lidar Measurements on High-Impact Weather Forecasting: Regional OSSE and Data Assimilation Studies

• Zhaoxia Pu, Lei Zhang, Shixuan Zhang, Bruce Gentry, David Emmitt, Belay Demoz et al.

A Three-Dimensional Variational Radar Data Assimilation Scheme Developed for Convective Scale NWP

• Jidong Gao

Data Assimilation Experiments of Refractivity Observed by JMA Operational Radar

• Hiromu Seko, Ei-ichi Sato, Hiroshi Yamauchi, Toshitaka Tsuda

Assessment of Radiative Effect of Hydrometeors in Rapid Radiative Transfer Model in Support of Satellite Cloud and Precipitation Microwave Data Assimilation

• Peiming Dong, Wei Han, Wei Li, Shuanglong Jin

Toward New Applications of the Adjoint Sensitivity Tools in Data Assimilation

• Dacian N. Daescu, Rolf H. Langland

GPS PWV Assimilation with the JMA Nonhydrostatic 4DVAR and Cloud Resolving Ensemble Forecast for the 2008 August Tokyo Metropolitan Area Local Heavy Rainfalls

• Kazuo Saito, Yoshinori Shoji, Seiji Origuchi, Le Duc

Validation and Operational Implementation of the Navy Coastal Ocean Model Four Dimensional Variational Data Assimilation System (NCOM 4DVAR) in the Okinawa Trough

• Scott Smith, Hans Ngodock, Matthew Carrier, Jay Shriver, Philip Muscarella, Innocent Souopgui

Stratospheric and Mesospheric Data Assimilation: The Role of Middle Atmospheric Dynamics

• Saroja Polavarapu, Manuel Pulido

Editors and Affiliations

Environmental Science and Engineering, Ewha Womans University, Seoul, Korea (Republic of)

Marine Meteorology Division, Naval Research Laboratory, Monterey, USA

About the editors

Seon Ki Park is Professor of Environmental Science and Engineering and Director of the Severe Storm Research Center at the Ewha Womans University in Seoul, Korea. He obtained a Ph.D. in Meteorology from the University of Oklahoma, M.S. and B.S. in Meteorology from the Seoul National University, Korea. He had worked as a research scientist at University of Oklahoma, University of Maryland and NASA/Goddard Space Flight Center.

Liang Xu is a meteorologist in the data assimilation section, Marine Meteorology Division, Naval Research Laboratory in Monterey, CA. In the past several years, Dr. Xu and his team have been developing, testing, and transitioning the US Navy’s weak constraint mesoscale atmospheric four dimensional variational (4D-Var) data assimilation system, COAMPS-AR, to operation. He is also working on the data assimilation aspects of the land surface processes.

Bibliographic Information

• Book Title : Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)
• Editors : Seon Ki Park, Liang Xu
• DOI : https://doi.org/10.1007/978-3-319-43415-5
• Publisher : Springer Cham
• eBook Packages : Earth and Environmental Science , Earth and Environmental Science (R0)
• Copyright Information : Springer International Publishing Switzerland 2017
• Hardcover ISBN : 978-3-319-43414-8 Published: 09 January 2017
• Softcover ISBN : 978-3-319-82818-3 Published: 07 July 2018
• eBook ISBN : 978-3-319-43415-5 Published: 26 December 2016
• Edition Number : 1
• Number of Pages : XXXVI, 553
• Number of Illustrations : 61 b/w illustrations, 155 illustrations in colour
• Topics : Math. Appl. in Environmental Science , Calculus of Variations and Optimal Control; Optimization , Simulation and Modeling , Atmospheric Sciences , Oceanography