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Data Assimilation For Atmospheric Oceanic And Hydrologic Applications

Author: Seon Ki Park
Publisher: Springer
ISBN: 3319434152
Size: 31.91 MB
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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.

Data Assimilation For The Geosciences

Author: Steven James Fletcher
Publisher: Elsevier
ISBN: 0128044845
Size: 70.25 MB
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Data Assimilation for the Geosciences: From Theory to Application brings together all of the mathematical,statistical, and probability background knowledge needed to formulate data assimilation systems in one place. It includes practical exercises for understanding theoretical formulation and presents some aspects of coding the theory with a toy problem. The book also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to the atmosphere, oceans, as well as the land surface and other geophysical situations. It offers a comprehensive presentation of the subject, from basic principles to advanced methods, such as Particle Filters and Markov-Chain Monte-Carlo methods. Additionally, Data Assimilation for the Geosciences: From Theory to Application covers the applications of data assimilation techniques in various disciplines of the geosciences, making the book useful to students, teachers, and research scientists. Includes practical exercises, enabling readers to apply concepts in a theoretical formulation Offers explanations for how to code certain parts of the theory Presents a step-by-step guide on how, and why, data assimilation works and can be used

Data Assimilation

Author: Geir Evensen
Publisher: Springer Science & Business Media
ISBN: 3642037119
Size: 59.36 MB
Format: PDF
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This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.

Data Assimilation

Author: William Lahoz
Publisher: Springer Science & Business Media
ISBN: 9783540747031
Size: 41.80 MB
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Data assimilation methods were largely developed for operational weather forecasting, but in recent years have been applied to an increasing range of earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observations and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation).

Data Assimilation For The Earth System

Author: Richard Swinbank
Publisher: Springer Science & Business Media
ISBN: 9781402015939
Size: 42.37 MB
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Proceedings of the NATO Advanced Study Institute, Acquafredda, Maratea, Italy from 19 May to 1 June 2002

Dynamic Data Assimilation

Author: John M. Lewis
Publisher: Cambridge University Press
ISBN: 0521851556
Size: 10.96 MB
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Dynamic data assimilation is the assessment, combination and synthesis of observational data, scientific laws and mathematical models to determine the state of a complex physical system, for instance as a preliminary step in making predictions about the system's behaviour. The topic has assumed increasing importance in fields such as numerical weather prediction where conscientious efforts are being made to extend the term of reliable weather forecasts beyond the few days that are presently feasible. This book is designed to be a basic one-stop reference for graduate students and researchers. It is based on graduate courses taught over a decade to mathematicians, scientists, and engineers, and its modular structure accommodates the various audience requirements. Thus Part I is a broad introduction to the history, development and philosophy of data assimilation, illustrated by examples; Part II considers the classical, static approaches, both linear and nonlinear; and Part III describes computational techniques. Parts IV to VII are concerned with how statistical and dynamic ideas can be incorporated into the classical framework. Key themes covered here include estimation theory, stochastic and dynamic models, and sequential filtering. The final part addresses the predictability of dynamical systems. Chapters end with a section that provides pointers to the literature, and a set of exercises with instructive hints.

Land Surface Observation Modeling And Data Assimilation

Author: Shunlin Liang
Publisher: World Scientific
ISBN: 981447262X
Size: 14.52 MB
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This book is unique in its ambitious and comprehensive coverage of earth system land surface characterization, from observation and modeling to data assimilation, including recent developments in theory and techniques, and novel application cases. The contributing authors are active research scientists, and many of them are internationally known leading experts in their areas, ensuring that the text is authoritative. This book comprises four parts that are logically connected from data, modeling, data assimilation integrating data and models to applications. Land data assimilation is the key focus of the book, which encompasses both theoretical and applied aspects with various novel methodologies and applications to the water cycle, carbon cycle, crop monitoring, and yield estimation. Readers can benefit from a state-of-the-art presentation of the latest tools and their usage for understanding earth system processes. Discussions in the book present and stimulate new challenges and questions facing today's earth science and modeling communities. Contents:Observation:Remote Sensing Data Products for Land Surface Data Assimilation System Application (Yunjun Yao, Shunlin Liang and Tongren Xu)Second-Generation Polar-Orbiting Meteorological Satellites of China: The Fengyun 3 Series and Its Applications in Global Monitoring (Peng Zhang)NASA Satellite and Model Land Data Services: Data Access Tutorial (Suhung Shen, Gregory Leptoukh and Hongliang Fang)Modeling:Land Surface Process Study and Modeling in Drylands and High-Elevation Regions (Yingying Chen and Kun Yang)Review of Parameterization and Parameter Estimation for Hydrologic Models (Soroosh Sorooshian and Wei Chu)Data Assimilation:Assimilating Remote Sensing Data into Land Surface Models: Theory and Methods (Xin Li and Yulong Bai)Estimating Model and Observation Error Covariance Information for Land Data Assimilation Systems (Wade T Crow)Inflation Adjustment on Error Covariance Matrices for Ensemble Kalman Filter Assimilation (Xiaogu Zheng, Guocan Wu, Xiao Liang and Shupeng Zhang)A Review of Error Estimation in Land Data Assimilation Systems (Yulong Bai, Xin Li and Qianlong Chai)An Introduction to Multi-scale Kalman Smoother-Based Framework and Its Application to Data Assimilation (Daniel E Salas and Xu Liang)Application:Overview of the North American Land Data Assimilation System (NLDAS) (Youlong Xia, Brian A Cosgrove, Michael B Ek, Justin Sheffield, Lifeng Luo, Eric F Wood, Kingtse Mo and the NLDAS team)Soil Moisture Data Assimilation for State Initialization of Seasonal Climate Prediction (Wenge Ni-Meister)Assimilation of Remote Sensing Data and Crop Simulation Models for Agricultural Study: Recent Advances and Future Directions (Hongliang Fang, Shunlin Liang and Gerrit Hoogenboom)Simultaneous State-Parameter Estimation for Hydrologic Modeling Using Ensemble Kalman Filter (Xianhong Xie) Readership: Graduate students and scientists in remote sensing, hydrology, ecology, environment and other earth sciences. Keywords:Data Assimilation;Uncertainties;Land Surface Processes;Satellite Data;Dynamic ModelsKey Features:The contribution authors are a group of leading experts international in those areasIt elaborates on the state-of-the-art land data assimilation, from theoretical derivations to current application problemsIt provides the latest development of satellite data and products, and presents novel applications of data assimilation for water cycle, crop monitoring and yield estimation

Operational Oceanography In The 21st Century

Author: Andreas Schiller
Publisher: Springer Science & Business Media
ISBN: 9789400703322
Size: 29.65 MB
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Over the past decade the significant advances in real-time ocean observing systems, ocean modelling, ocean data assimilation and super-computing has seen the development and implementation of operational ocean forecast systems of the global ocean. At the conclusion of the Global Ocean Data Assimilation Experiment (GODAE) in 2008 ocean analysis and forecasting services were being supported by 12 international centres. This book is about ocean forecasting - a maturing field which remains an active area of research, and includes such topics as ocean predictability, observing system design, high resolution ocean modelling and ocean data assimilation. It presents the introduction to ocean forecasting which provides a foundation for new opportunities in areas of coupled bio-geochemical forecasting and coupled atmosphere-wave-ocean forecasting. The book describes an updated account of research and development to improve forecast systems, determining how best to service the marine user community with forecast information as well as demonstrating impact to their applications. It also discusses operational centres that are now supporting a range of real-time ocean services including online graphical and data products for their user communities and their feedback on the quality of information. The contents of this book are aimed at early career scientists and professionals with an interest in operational oceanography and related ocean science. There are excellent opportunities for exciting careers in the emerging field of operational oceanography in order to address current and future challenges as well as provide the supporting services to a rapidly growing user community.

Land Surface Remote Sensing In Continental Hydrology

Author: Nicolas Baghdadi
Publisher: Elsevier
ISBN: 0081011814
Size: 50.69 MB
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The continental hydrological cycle is one of the least understood components of the climate system. The understanding of the different processes involved is important in the fields of hydrology and meteorology. In this volume the main applications for continental hydrology are presented, including the characterization of the states of continental surfaces (water state, snow cover, etc.) using active and passive remote sensing, monitoring the Antarctic ice sheet and land water surface heights using radar altimetry, the characterization of redistributions of water masses using the GRACE mission, the potential of GNSS-R technology in hydrology, and remote sensing data assimilation in hydrological models. This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD) , engineers and scientists, specialists in remote sensing applied to hydrology. Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of Earth observation data. Provides clear and concise descriptions of modern remote sensing methods Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications Provides chapters on physical principles, measurement, and data processing for each technique described Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made