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


Book Description

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.




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


Book Description

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.




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


Book Description

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.




Applications of Data Assimilation and Inverse Problems in the Earth Sciences


Book Description

A comprehensive reference on data assimilation and inverse problems, and their applications across a broad range of geophysical disciplines, ideal for researchers and graduate students. It highlights the importance of data assimilation for understanding dynamical processes of the Earth and its space environment, and summarises recent advances.




Introduction to Ocean Circulation and Modeling


Book Description

Introduction to Ocean Circulation and Modeling provide basics for physical oceanography covering ocean properties, ocean circulations and their modeling. First part of the book explains concepts of oceanic circulation, geostrophy, Ekman, Sverdrup dynamics, Stommel and Munk problems, two-layer dynamics, stratification, thermal and salt diffusion, vorticity/instability, and so forth. Second part highlights basic implementation framework for ocean models, discussion of different models, and their unique differences from the common framework with basin-scale modeling, regional modeling, and interdisciplinary modeling at different space and time scales. Features: Covers ocean properties, ocean circulations and their modeling. Explains the centrality of a rotating earth and its implications for ocean and atmosphere in a simple manner. Provides basic facts of ocean dynamics. Illustrative diagrams for clear understanding of key concepts. Outlines interdisciplinary and complex models for societal applications. The book aims at Senior Undergraduate Students, Graduate Students and Researchers in Ocean Science and Engineering, Ocean Technology, Physical Oceanography, Ocean Circulation, Ocean Modeling, Dynamical Oceanography and Earth Science.







Principles of Data Assimilation


Book Description

A unique combination of both theoretical and practical aspects of data assimilation with examples and exercises for students.







Data Assimilation and Control: Theory and Applications in Life Sciences


Book Description

The understanding of complex systems is a key element to predict and control the system’s dynamics. To gain deeper insights into the underlying actions of complex systems today, more and more data of diverse types are analyzed that mirror the systems dynamics, whereas system models are still hard to derive. Data assimilation merges both data and model to an optimal description of complex systems’ dynamics. The present eBook brings together both recent theoretical work in data assimilation and control and demonstrates applications in diverse research fields.




Forecast Error Correction using Dynamic Data Assimilation


Book Description

This book introduces the reader to a new method of data assimilation with deterministic constraints (exact satisfaction of dynamic constraints)—an optimal assimilation strategy called Forecast Sensitivity Method (FSM), as an alternative to the well-known four-dimensional variational (4D-Var) data assimilation method. 4D-Var works with a forward in time prediction model and a backward in time tangent linear model (TLM). The equivalence of data assimilation via 4D-Var and FSM is proven and problems using low-order dynamics clarify the process of data assimilation by the two methods. The problem of return flow over the Gulf of Mexico that includes upper-air observations and realistic dynamical constraints gives the reader a good idea of how the FSM can be implemented in a real-world situation.