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Author: National Research Council
Publisher: National Academies Press
ISBN: 0309045363
Category : Science
Languages : en
Pages : 89
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Book Description
This volume explores and evaluates the development, multiple applications, and usefulness of four-dimensional (space and time) model assimilations of data in the atmospheric and oceanographic sciences and projects their applicability to the earth sciences as a whole. Using the predictive power of geophysical laws incorporated in the general circulation model to produce a background field for comparison with incoming raw observations, the model assimilation process synthesizes diverse, temporarily inconsistent, and spatially incomplete observations from worldwide land, sea, and space data acquisition systems into a coherent representation of an evolving earth system. The book concludes that this subdiscipline is fundamental to the geophysical sciences and presents a basic strategy to extend the application of this subdiscipline to the earth sciences as a whole.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309045363
Category : Science
Languages : en
Pages : 89
Get Book
Book Description
This volume explores and evaluates the development, multiple applications, and usefulness of four-dimensional (space and time) model assimilations of data in the atmospheric and oceanographic sciences and projects their applicability to the earth sciences as a whole. Using the predictive power of geophysical laws incorporated in the general circulation model to produce a background field for comparison with incoming raw observations, the model assimilation process synthesizes diverse, temporarily inconsistent, and spatially incomplete observations from worldwide land, sea, and space data acquisition systems into a coherent representation of an evolving earth system. The book concludes that this subdiscipline is fundamental to the geophysical sciences and presents a basic strategy to extend the application of this subdiscipline to the earth sciences as a whole.
Author: National Aeronautics and Space Adm Nasa
Publisher: Independently Published
ISBN: 9781730953972
Category :
Languages : en
Pages : 96
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Book Description
This is the final technical report for the project entitled: "High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems," funded at NPAC by the DAO at NASA/GSFC. First, the motivation for the project is given in the introductory section, followed by the executive summary of major accomplishments and the list of project-related publications. Detailed analysis and description of research results is given in subsequent chapters and in the Appendix. Makivic, Miloje S. Goddard Space Flight Center
Author: John Charles Derber
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 332
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Book Description
Author: Sivaramakrishnan Lakshmivarahan
Publisher: Springer
ISBN: 3319399977
Category : Computers
Languages : en
Pages : 270
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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.
Author: Seon Ki Park
Publisher: Springer Science & Business Media
ISBN: 3642350887
Category : Science
Languages : en
Pages : 730
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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.
Author: Mark Asch
Publisher: SIAM
ISBN: 1611974542
Category : Mathematics
Languages : en
Pages : 306
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Book Description
Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasizing ?why? and not just ?how.? Methods and diagnostics are emphasized, enabling readers to readily apply them to their own field of study. Readers will find a comprehensive guide that is accessible to nonexperts; numerous examples and diverse applications from a broad range of domains, including geophysics and geophysical flows, environmental acoustics, medical imaging, mechanical and biomedical engineering, economics and finance, and traffic control and urban planning; and the latest methods for advanced data assimilation, combining variational and statistical approaches.
Author: Lisa Neef
Publisher:
ISBN: 9780494396315
Category :
Languages : en
Pages : 400
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Book Description
This thesis examines the application of three methods of so-called four-dimensional data assimilation to dynamical models where there exists a timescale separation between vortical motion and (relatively fast) inertia-gravity waves. Using a highly simplified dynamical model which admits one nonlinear vortical mode and one inertia-gravity wave, we evaluate the relative strengths and weaknesses of linearization-based and ensemble-based sequential assimilation (i.e. two varieties of the Kalman filter), and four-dimensional variational assimilation (4DVAR). The first part of this study is concerned with balanced flow, or flow where vortical motion dominates and inertial/gravitational motion is "slaved" to the dominant flow. The goal of assimilation in this context is to recover the true balanced state, without the excitation of spurious inertia-gravity waves. It is shown that the excitation of spurious waves becomes more difficult to control as the nonlinearity of the assimilation system is increased, for example by decreasing observation frequency. If not enough components of the true state are observed or observations are infrequent relative to the nonlinearity of the model, the explicit evolution of error covariances using a tangent-linear model can easily become quite inaccurate, which results in a highly unstable assimilation cycle wherein spurious waves are excited and not controlled. Both ensemble-based and implicit variational covariance models offer improvements, but these are themselves limited by error due to sampling and non-Gaussianity of the ensemble and by the tendency to settle into local minima of a non-quadratic cost function. The analysis is then extended to dynamical regimes where the inertia-gravity wave becomes more important to the evolution of the system as a whole, either by increasing its magnitude, decreasing the timescale separation, or increasing the coupling between fast and slow modes. It is found that recovery of either mode from observations that contain both timescales benefits from the four-dimensional estimation of error statistics. The ability to extract both modes from observations which contain both timescales of motion depends both on the estimated fast-slow covariances, as well as the estimated error variance ascribed to the gravity wave. Recovery of a non-negligible inertia-gravity wave is found to be possible with the Kalman filter, and more so if an ensemble is used to estimate covariances, but extremely difficult for variational assimilation. It is also found that accuracy of the assimilation for the different regimes of balance/imbalance can be weakened considerably as systematic model error is added and increased. Some typical modifications designed to counter systematic error are shown to alleviate some of these problems, but also increase the excitation of spurious imbalance.
Author: Richard Swinbank
Publisher: Springer Science & Business Media
ISBN: 9781402015939
Category : Mathematics
Languages : en
Pages : 394
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Book Description
Proceedings of the NATO Advanced Study Institute, Acquafredda, Maratea, Italy from 19 May to 1 June 2002
Author: Steven J. Fletcher
Publisher: Elsevier
ISBN: 0323972535
Category : Science
Languages : en
Pages : 1130
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Book Description
Data Assimilation for the Geosciences: From Theory to Application, Second Edition brings together all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place. It includes practical exercises enabling readers to apply theory in both a theoretical formulation as well as teach them how to code the theory with toy problems to verify their understanding. It also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to land surface, the atmosphere, ocean and other geophysical situations. The second edition of Data Assimilation for the Geosciences has been revised with up to date research that is going on in data assimilation, as well as how to apply the techniques. The new edition features an introduction of how machine learning and artificial intelligence are interfacing and aiding data assimilation. In addition to appealing to students and researchers across the geosciences, this now also appeals to new students and scientists in the field of data assimilation as it will now have even more information on the techniques, research, and applications, consolidated into one source. Includes practical exercises and solutions enabling readers to apply theory in both a theoretical formulation as well as enabling them to code theory Provides the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place New to this edition: covers new topics such as Observing System Experiments (OSE) and Observing System Simulation Experiments; and expanded approaches for machine learning and artificial intelligence
Author: John M. Lewis
Publisher: Cambridge University Press
ISBN: 0521851556
Category : Mathematics
Languages : en
Pages : 601
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Book Description
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