Principles of data assimilation

• Verfasst von: Park, Seon Ki [VerfasserIn]
• Verfasst von: Zupanski, Milija [VerfasserIn]
• Titel: Principles of data assimilation
• Verf.angabe: Seon Ki Park (Ewha Womans University), Milija Zupanski (Colorado State University)
• Verlagsort: Cambridge ; New York ; Port Melbourne ; New Delhi ; Singapore
• Verlag: Cambridge University Press
• E-Jahr: 2022
• Jahr: [2022]
• Umfang: xiii, 398 Seiten
• Illustrationen: Illustrationen
• Fussnoten: Includes bibliographical references and index
• ISBN: 978-1-108-83176-5
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Online-Ausgabe: Park, Seon Ki, 1961-: Principles of data assimilation. - New York : Cambridge University Press, 2022 |(DLC)2022009538
• RVK-Notation: SK 950
• K10plus-PPN: 180527936X

Abstract

"Data assimilation includes two main components: simulation model and data. The simulation model is defined as a mathematical/numerical system that can simulate an event or a process. In most typical setting the simulation model is a prediction model based on partial differential equations (PDE) that often includes empirical parameters. Data are generally associated with observations made by a measuring instrument, although data could also imply a product obtained by processing observations. Using an example from meteorology, data include observations such as atmospheric temperature and satellite radiances. The goal of data assimilation is to combine the information from a simulation model and data in order to improve the knowledge of the system, described by the simulation model. Apparently, the formulation of data assimilation will depend on interpretation of the knowledge of the system. Before we attempt to clarify a possible interpretation, it is useful to further understand the simulation model and data"--