[PDF] Data Assimilation For Atmospheric Oceanic And Hydrologic Applications Vol Iii eBook

Author : Seon Ki Park
Publisher : Springer
Page : 576 pages
File Size : 36,16 MB
Release : 2016-12-26
Category : Science
ISBN : 3319434152

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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 : Seon Ki Park
Publisher : Springer Science & Business Media
Page : 736 pages
File Size : 42,66 MB
Release : 2013-05-22
Category : Science
ISBN : 3642350887

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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 : Seon Ki Park
Publisher : Springer Nature
Page : 707 pages
File Size : 43,14 MB
Release : 2021-11-09
Category : Science
ISBN : 3030777227

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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.

Author : Seon Ki Park
Publisher : Cambridge University Press
Page : 413 pages
File Size : 36,84 MB
Release : 2022-09-29
Category : Science
ISBN : 1108831761

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

Author : Mehdi Khaki
Publisher : Springer Nature
Page : 292 pages
File Size : 42,85 MB
Release : 2020-01-02
Category : Science
ISBN : 3030373754

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This book presents the fundamentals of data assimilation and reviews the application of satellite remote sensing in hydrological data assimilation. Although hydrological models are valuable tools to monitor and understand global and regional water cycles, they are subject to various sources of errors. Satellite remote sensing data provides a great opportunity to improve the performance of models through data assimilation.

Author : John M. Lewis
Publisher : Cambridge University Press
Page : 601 pages
File Size : 35,79 MB
Release : 2006-08-03
Category : Mathematics
ISBN : 0521851556

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Publisher description

Author : Liping Di
Publisher : Springer Nature
Page : 418 pages
File Size : 34,53 MB
Release : 2021-04-12
Category : Science
ISBN : 3030663876

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This volume collects and presents the fundamentals, tools, and processes of utilizing geospatial information technologies to process remotely sensed data for use in agricultural monitoring and management. The issues related to handling digital agro-geoinformation, such as collecting (including field visits and remote sensing), processing, storing, archiving, preservation, retrieving, transmitting, accessing, visualization, analyzing, synthesizing, presenting, and disseminating agro-geoinformation have never before been systematically documented in one volume. The book is edited by International Conference on Agro-Geoinformatics organizers Dr. Liping Di (George Mason University), who coined the term “Agro-Geoinformatics” in 2012, and Dr. Berk Üstündağ (Istanbul Technical University) and are uniquely positioned to curate and edit this foundational text. The book is composed of eighteen chapters that can each stand alone but also build on each other to give the reader a comprehensive understanding of agro-geoinformatics and what the tools and processes that compose the field can accomplish. Topics covered include land parcel identification, image processing in agricultural observation systems, databasing and managing agricultural data, crop status monitoring, moisture and evapotranspiration assessment, flood damage monitoring, agricultural decision support systems and more.

Author : Sivaramakrishnan Lakshmivarahan
Publisher : Springer
Page : 278 pages
File Size : 41,33 MB
Release : 2016-10-21
Category : Computers
ISBN : 3319399977

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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 : Axel Hutt
Publisher : Frontiers Media SA
Page : 116 pages
File Size : 39,93 MB
Release : 2019-08-16
Category :
ISBN : 2889459853

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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.