Semi Lagrangian Advection Methods And Their Applications In Geoscience


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Semi-Lagrangian Advection Methods and Their Applications in Geoscience


Semi-Lagrangian Advection Methods and Their Applications in Geoscience

Author: Steven J. Fletcher

language: en

Publisher: Elsevier

Release Date: 2019-11-18


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Semi-Lagrangian Advection Methods and Their Applications in Geoscience provides a much-needed resource on semi-Lagrangian theory, methods, and applications. Covering a variety of applications, the book brings together developments of the semi-Lagrangian in one place and offers a comparison of semi-Lagrangian methods with Eulerian-based approaches. It also includes a chapter dedicated to difficulties of dealing with the adjoint of semi-Lagrangian methods and illustrates the behavior of different schemes for different applications. This allows for a better understanding of which schemes are most efficient, stable, consistent, and likely to introduce the minimum model error into a given problem. Beneficial for students learning about numerical approximations to advection, researchers applying these techniques to geoscientific modeling, and practitioners looking for the best approach for modeling, Semi-Lagrangian Advection Methods and Their Applications in Geoscience fills a crucial gap in numerical modeling and data assimilation in geoscience. - Provides a single resource for understanding semi-Lagrangian methods and what is involved in its application - Includes exercises and codes to supplement learning and create opportunities for practice - Includes coverage of adjoints, examining the advantages and disadvantages of different approaches in multiple coordinate systems and different discretizations - Includes links to numerical datasets and animations to further enhance understanding

Data Assimilation for the Geosciences


Data Assimilation for the Geosciences

Author: Steven J. Fletcher

language: en

Publisher: Elsevier

Release Date: 2022-11-16


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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

Water Quality Modelling for Rivers and Streams


Water Quality Modelling for Rivers and Streams

Author: Marcello Benedini

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-02-11


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The main objective of the Water Framework Directive in the European countries is to achieve a “good status” of all the water bodies, in the integrated management of river basins. In order to assess the impact of improvement measures, water quality models are necessary. During the previous decades the progress in computer technology and computational methods has supported the development of advanced mathematical models for pollutant transport in rivers and streams. This book is intended to provide the fundamental knowledge needed for a deeper understanding of these models and the development of new ones, which will fulfil future quality requirements in water resources management. This book focuses on the fundamentals of computational techniques required in water quality modelling. Advection, dispersion and concentrated sources or sinks of contaminants lead to the formulation of the fundamental differential equation of pollutant transport. Its integration, according to appropriate initial and boundary conditions and with the knowledge of the velocity field, allows for pollutant behaviour to be assessed in the entire water body. An analytical integration is convenient only in one-dimensional approach with considerable simplification. Integration in the numerical field is useful for taking into account particular aspects of water body and pollutants. To ensure their reliability, the models require accurate calibration and validation, based on proper data, taken from direct measurements. In addition, sensitivity and uncertainty analysis are also of utmost importance. All the above items are discussed in detail in the 21 chapters of the book, which is written in a didactic form for professionals and students.