Assimilation Of Remote Sensing Data Into Earth System Models
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Assimilation Of Remote Sensing Data Into Earth System Models
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Author : Jean-Christophe Calvet
language : en
Publisher: MDPI
Release Date : 2019-11-20
Assimilation Of Remote Sensing Data Into Earth System Models written by Jean-Christophe Calvet and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Science categories.
In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean–atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean–atmosphere, land–atmosphere, and soil–vegetation data assimilation.
Assimilation Of Remote Sensing Data Into Earth System Models
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Author : Jean-Christophe Calvet
language : en
Publisher:
Release Date : 2019
Assimilation Of Remote Sensing Data Into Earth System Models written by Jean-Christophe Calvet and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Science (General) categories.
In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean-atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean-atmosphere, land-atmosphere, and soil-vegetation data assimilation.
Data Assimilation For The Earth System
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Author : Richard Swinbank
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Data Assimilation For The Earth System written by Richard Swinbank and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology. Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites. This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.
Land Surface Observation Modeling And Data Assimilation
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Author : Shunlin Liang
language : en
Publisher: World Scientific
Release Date : 2013
Land Surface Observation Modeling And Data Assimilation written by Shunlin Liang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Science categories.
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.
Advances In Land Remote Sensing
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Author : Shunlin Liang
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-11
Advances In Land Remote Sensing written by Shunlin Liang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-11 with Technology & Engineering categories.
It collects the review papers of the 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS). It systematically summarizes the past achievements and identifies the frontier issues as the research agenda for the near future. It covers all aspects of land remote sensing, from sensor systems, physical modeling, inversion algorithms, to various applications.
The Application Of Neural Networks In The Earth System Sciences
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Author : Vladimir M. Krasnopolsky
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-14
The Application Of Neural Networks In The Earth System Sciences written by Vladimir M. Krasnopolsky and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-14 with Science categories.
This book brings together a representative set of Earth System Science (ESS) applications of the neural network (NN) technique. It examines a progression of atmospheric and oceanic problems, which, from the mathematical point of view, can be formulated as complex, multidimensional, and nonlinear mappings. It is shown that these problems can be solved utilizing a particular type of NN – the multilayer perceptron (MLP). This type of NN applications covers the majority of NN applications developed in ESSs such as meteorology, oceanography, atmospheric and oceanic satellite remote sensing, numerical weather prediction, and climate studies. The major properties of the mappings and MLP NNs are formulated and discussed. Also, the book presents basic background for each introduced application and provides an extensive set of references. “This is an excellent book to learn how to apply artificial neural network methods to earth system sciences. The author, Dr. Vladimir Krasnopolsky, is a universally recognized master in this field. With his vast knowledge and experience, he carefully guides the reader through a broad variety of problems found in the earth system sciences where neural network methods can be applied fruitfully. (...) The broad range of topics covered in this book ensures that researchers/graduate students from many fields (...) will find it an invaluable guide to neural network methods.” (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) “Vladimir Krasnopolsky has been the “founding father” of applying computation intelligence methods to environmental science; (...) Dr. Krasnopolsky has created a masterful exposition of a young, yet maturing field that promises to advance a deeper understanding of best modeling practices in environmental science.” (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) “Vladimir Krasnopolsky has written an important and wonderful book on applications of neural networks to replace complex and expensive computational algorithms within Earth System Science models. He is uniquely qualified to write this book, since he has been a true pioneer with regard to many of these applications. (...) Many other examples of creative emulations will inspire not just readers interested in the Earth Sciences, but any other modeling practitioner (...) to address both theoretical and practical complex problems that may (or will!) arise in a complex system." ” (Prof. Eugenia Kalnay, University of Maryland, USA)
Data Assimilation
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Author : William Lahoz
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-23
Data Assimilation written by William Lahoz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-23 with Science categories.
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).
Remote Sensing Advances For Earth System Science
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Author : Diego Fernández-Prieto
language : en
Publisher: Springer
Release Date : 2016-01-13
Remote Sensing Advances For Earth System Science written by Diego Fernández-Prieto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-13 with Technology & Engineering categories.
This book presents cutting-edge remote sensing research, outlining the advanced use of European Space Agency (ESA) satellite data in the context of climate change. The ESA, through its Support to Science Element (STSE) Programme, funds a network of young post-doc scientists pursuing 2-year cutting-edge research projects in the field of remote sensing. This “Changing Earth Science Network” focuses on the exploitation of Earth Observation (EO) data to address major issues concerning the broader context of climate change in five scientific research domains: the oceans, atmosphere, cryosphere, land and solid earth.
Remote Sensing And Climate Modeling Synergies And Limitations
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Author : Martin Beniston
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-11
Remote Sensing And Climate Modeling Synergies And Limitations written by Martin Beniston and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-11 with Science categories.
1 2 Michel M. VERSTRAETE and Martin BENISTON 1 Space Applications Institute, EC Joint Research Centre, Ispra, Italy 2 Department of Geography, University of Fribourg, Switzerland This volume contains the proceedings ofthe workshop entitled “Satellite Remote Sensing and Climate Simulations: Synergies and Limitations” that took place in Les Diablerets, Switzerland, September 20–24, 1999. This international scientific conference aimed at addressing the current and pot- tial role of satellite remote sensing in climate modeling, with a particular focus on land surface processes and atmospheric aerosol characterization. Global and regional circulation models incorporate our knowledge ofthe dynamics ofthe Earth's atmosphere. They are used to predict the evolution of the weather and climate. Mathematically, this system is represented by a set ofpartial differential equations whose solution requires initial and bo- dary conditions. Limitations in the accuracy and geographical distribution of these constraints, and intrinsic mathematical sensitivity to these conditions do not allow the identification of a unique solution (prediction). Additional observations on the climate system are thus used to constrain the forecasts of the mathematical model to remain close to the observed state ofthe system.
Quantitative Remote Sensing Of Land Surfaces
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Author : Shunlin Liang
language : en
Publisher: John Wiley & Sons
Release Date : 2005-03-11
Quantitative Remote Sensing Of Land Surfaces written by Shunlin Liang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-03-11 with Technology & Engineering categories.
Processing the vast amounts of data on the Earth's land surface environment generated by NASA's and other international satellite programs is a significant challenge. Filling a gap between the theoretical, physically-based modelling and specific applications, this in-depth study presents practical quantitative algorithms for estimating various land surface variables from remotely sensed observations. A concise review of the basic principles of optical remote sensing as well as practical algorithms for estimating land surface variables quantitatively from remotely sensed observations. Emphasizes both the basic principles of optical remote sensing and practical algorithms for estimating land surface variables quantitatively from remotely sensed observations Presents the current physical understanding of remote sensing as a system with a focus on radiative transfer modelling of the atmosphere, canopy, soil and snow Gathers the state of the art quantitative algorithms for sensor calibration, atmospheric and topographic correction, estimation of a variety of biophysical and geoph ysical variables, and four-dimensional data assimilation