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

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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 adaptive observations, sensitivity analysis, parameter estimation and AI applications. The book is useful to individual researchers as well as graduate students for a reference in the field of data assimilation.

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Keywords

• Hybrid Data Assimilation
• Kalman Filter
• Monte Carlo Method
• Artificial Intelligence Application
• Wiener Polynomial Chaos Expansion

Table of contents (26 chapters)

Front Matter

Data Assimilation for Chaotic Dynamics

• Alberto Carrassi, Marc Bocquet, Jonathan Demaeyer, Colin Grudzien, Patrick Raanes, Stéphane Vannitsem

Multifidelity Data Assimilation for Physical Systems

• Andrey A. Popov, Adrian Sandu

Filtering with One-Step-Ahead Smoothing for Efficient Data Assimilation

• Boujemaa Ait-El-Fquih, Ibrahim Hoteit

Sparsity-Based Kalman Filters for Data Assimilation

• Wei Kang, Liang Xu

Perturbations by the Ensemble Transform

• Kazuo Saito, Le Duc, Takumi Matsunobu, Takuya Kurihana

Stochastic Representations for Model Uncertainty in the Ensemble Data Assimilation System

• Sujeong Lim, Seon Ki Park

Second-Order Methods in Variational Data Assimilation

• François-Xavier Le Dimet, Victor Shutyaev

Statistical Parameter Estimation for Observation Error Modelling: Application to Meteor Radars

• Elizabeth A. Satterfield, Joanne A. Waller, David D. Kuhl, Dan Hodyss, Karl W. Hoppel, Stephen D. Eckermann et al.

Observability Gramian and Its Role in the Placement of Observations in Dynamic Data Assimilation

• S. Lakshmivarahan, John M. Lewis, Sai Kiran Reddy Maryada

Placement of Observations for Variational Data Assimilation: Application to Burgers’ Equation and Seiche Phenomenon

• John M. Lewis, S. Lakshmivarahan, S. K. R. Maryada

Analysis, Lateral Boundary, and Observation Impacts in a Limited Area Model

• Clark Amerault

Assimilation of In-Situ Observations

• Patricia M. Pauley, Bruce Ingleby

GNSS-RO Sounding in the Troposphere and Stratosphere

• Benjamin Ruston, Neill Bowler, Sean Healy, Hui Shao

Impact of Assimilating the Special Radiosonde Observations on COAMPS Arctic Forecasts During the Year of Polar Prediction

• Xiaodong Hong, James D. Doyle, Daniel P. Tyndall

Images Assimilation: An Ocean Perspective

• François-Xavier Le Dimet, Hans E. Ngodock, Innocent Souopgui

Sensitivity Analysis in Ocean Acoustic Propagation

• Hans E. Ngodock, Matthew J. Carrier, Josette Fabre, Robert Zingarelli, Scott Smith, Innocent Souopgui

Difficulty with Sea Surface Height Assimilation When Relying on an Unrepresentative Climatology

• John J. Osborne, Matthew J. Carrier, Hans E. Ngodock

Theoretical and Practical Aspects of Strongly Coupled Aerosol-Atmosphere Data Assimilation

• Ting-Chi Wu, Milija Zupanski, Anton Kliewer, Lewis Grasso, Leah D. Grant

Improving Near-Surface Weather Forecasts with Strongly Coupled Land–Atmosphere Data Assimilation

• Zhaoxia Pu

Editors and Affiliations

Climate and Energy Systems 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 Founding Director of the Severe Storm Research Center and the Center for Climate/Environment Change Prediction Research at the Ewha Womans University in Seoul, Korea. He obtained a Ph.D. in Meteorology from the University of Oklahoma and M.S. and B.S. in Meteorology from the Seoul National University, Korea. He had worked as a research scientist at the University of Oklahoma, University of Maryland and NASA/Goddard Space Flight Center. His research focuses on storm- and meso-scale meteorology, hydrometeorology, and parameter estimation and data assimilation to improve numerical weather/climate prediction.

Liang Xu is the Head of Atmospheric Dynamics & Prediction Branch and a Meteorologist at the Marine Meteorology Division, Naval Research Laboratory in Monterey, California, USA. He leads a fully integrated research program encompassing all aspects of numerical weather prediction and data assimilation, focusing on critical issues related to the analysis and prediction of atmospheric processes and phenomena within the Navy's Earth System Prediction Capability. He and his team have developed, tested, and transitioned to the Fleet Numerical Meteorology and Oceanographic Center (FNMOC), an operational global atmospheric 4DVar data assimilation system.

Bibliographic Information

• Book Title : Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
• Editors : Seon Ki Park, Liang Xu
• DOI : https://doi.org/10.1007/978-3-030-77722-7
• Publisher : Springer Cham
• eBook Packages : Earth and Environmental Science , Earth and Environmental Science (R0)
• Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
• Hardcover ISBN : 978-3-030-77721-0 Published: 10 November 2021
• Softcover ISBN : 978-3-030-77724-1 Published: 11 November 2022
• eBook ISBN : 978-3-030-77722-7 Published: 09 November 2021
• Edition Number : 1
• Number of Pages : XXI, 705
• Number of Illustrations : 15 b/w illustrations, 224 illustrations in colour
• Topics : Monitoring/Environmental Analysis , Optimization , Computer Applications , Oceanography