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Author : Sebastian Reich,Colin Cotter
Publisher : Cambridge University Press
Page : 308 pages
File Size : 50,9 Mb
Release : 2015-05-14
Category : Computers
ISBN : 9781107069398
This book covers key ideas and concepts. It is an ideal introduction for graduate students in any field where Bayesian data assimilation is applied.
Author : Andy Pole,Mike West,Jeff Harrison
Publisher : CRC Press
Page : 432 pages
File Size : 51,8 Mb
Release : 2018-10-08
Category : Business & Economics
ISBN : 9781482267433
Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unify the concepts, model forms, and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series, including how to identify, structure, explain observed behavior, model structures and behaviors, and interpret analyses to make informed forecasts Illustrate concepts such as component decomposition, fundamental model forms including trends and cycles, and practical modeling requirements for routine change and unusual events Conduct all analyses in the BATS computer programs, furnishing online that program and the more than 50 data sets used in the text The result is a clear presentation of the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations. Accessible to undergraduates, this unique volume also offers complete guidelines valuable to researchers, practitioners, and advanced students in statistics, operations research, and engineering.
Author : Kody Law,Andrew Stuart,Konstantinos Zygalakis
Publisher : Springer
Page : 242 pages
File Size : 53,8 Mb
Release : 2015-09-05
Category : Mathematics
ISBN : 9783319203256
This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathematics, either through a lecture course, or through self-study.
Author : Mike West,Jeff Harrison
Publisher : Springer Science & Business Media
Page : 720 pages
File Size : 52,5 Mb
Release : 2013-06-29
Category : Mathematics
ISBN : 9781475793659
In this book we are concerned with Bayesian learning and forecast ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel opment has involved thorough investigation of mathematical and sta tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.
Author : Peter Jan Van Leeuwen,Yuan Cheng,Sebastian Reich
Publisher : Springer
Page : 118 pages
File Size : 48,7 Mb
Release : 2015-07-22
Category : Mathematics
ISBN : 9783319183473
This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.
Author : Mark Asch,Marc Bocquet,Maelle Nodet
Publisher : SIAM
Page : 306 pages
File Size : 41,6 Mb
Release : 2016-12-29
Category : Mathematics
ISBN : 9781611974546
Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasizing ?why? and not just ?how.? Methods and diagnostics are emphasized, enabling readers to readily apply them to their own field of study. Readers will find a comprehensive guide that is accessible to nonexperts; numerous examples and diverse applications from a broad range of domains, including geophysics and geophysical flows, environmental acoustics, medical imaging, mechanical and biomedical engineering, economics and finance, and traffic control and urban planning; and the latest methods for advanced data assimilation, combining variational and statistical approaches.
Author : Troy Vettese,Drew Pendergrass
Publisher : Verso Books
Page : 241 pages
File Size : 41,7 Mb
Release : 2024-04-23
Category : Political Science
ISBN : 9781804290385
"Empowers readers to write their own recipes for a future in peril: an exercise in democracy few books have dared to undertake." –Andreas Malm, author of How to Blow Up a Pipeline A plan to save the earth and bring the good life to all In this thrilling and capacious book, Troy Vettese and Drew Pendergrass challenge the inertia of capitalism and the left alike and propose a radical plan to address climate disaster and guarantee the good life for all. Consumption in the Global North can’t continue unabated, and we must give up the idea that humans can fully control the Earth through technological “fixes” which only wreak further havoc. Rather than allow the forces of the free market to destroy the planet, we must strive for a post-capitalist society able to guarantee the good life the entire planet. This plan, which they call Half-Earth Socialism, means we must: • rewild half the Earth to absorb carbon emissions and restore biodiversity • pursue a rapid transition to renewable energy, paired with drastic cuts in consumption by the world’s wealthiest populations • enact global veganism to cut down on energy and land use • inaugurate worldwide socialist planning to efficiently and equitably manage production • welcome the participation of everyone—even you! Accompanied by a climate-modelling website inviting readers to design their own “half earth,” Vettese and Pendergrass offer us a visionary way forward—and our only hope for a future.
Author : Michel Bergmann,Laurent Cordier,Traian Iliescu
Publisher : Frontiers Media SA
Page : 178 pages
File Size : 47,7 Mb
Release : 2023-01-05
Category : Science
ISBN : 9782832510704
Author : Bertrand Chapron,Dan Crisan,Darryl Holm,Etienne Mémin,Anna Radomska
Publisher : Springer Nature
Page : 347 pages
File Size : 53,9 Mb
Release : 2023-11-04
Category : Mathematics
ISBN : 9783031400940
This open access proceedings volume brings selected, peer-reviewed contributions presented at the Third Stochastic Transport in Upper Ocean Dynamics (STUOD) 2022 Workshop, held virtually and in person at the Imperial College London, UK, September 26–29, 2022. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Computer Science and Automatic Control (INRIA) and the French Research Institute for Exploitation of the Sea (IFREMER). The project aims to deliver new capabilities for assessing variability and uncertainty in upper ocean dynamics. It will provide decision makers a means of quantifying the effects of local patterns of sea level rise, heat uptake, carbon storage and change of oxygen content and pH in the ocean. Its multimodal monitoring will enhance the scientific understanding of marine debris transport, tracking of oil spills and accumulation of plastic in the sea. All topics of these proceedings are essential to the scientific foundations of oceanography which has a vital role in climate science. Studies convened in this volume focus on a range of fundamental areas, including: Observations at a high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity; Large scale numerical simulations; Data-based stochastic equations for upper ocean dynamics that quantify simulation error; Stochastic data assimilation to reduce uncertainty. These fundamental subjects in modern science and technology are urgently required in order to meet the challenges of climate change faced today by human society. This proceedings volume represents a lasting legacy of crucial scientific expertise to help meet this ongoing challenge, for the benefit of academics and professionals in pure and applied mathematics, computational science, data analysis, data assimilation and oceanography.
Author : Seon Ki Park,Liang Xu
Publisher : Springer Nature
Page : 707 pages
File Size : 43,8 Mb
Release : 2021-11-09
Category : Science
ISBN : 9783030777227
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 : Daniel Sanz-Alonso,Andrew Stuart,Armeen Taeb
Publisher : Cambridge University Press
Page : 227 pages
File Size : 41,6 Mb
Release : 2023-08-10
Category : Computers
ISBN : 9781009414326
A clear and concise mathematical introduction to the subjects of inverse problems and data assimilation, and their inter-relations.
Author : National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Ocean Studies Board,Board on Atmospheric Sciences and Climate,Committee on Developing a U.S. Research Agenda to Advance Subseasonal to Seasonal Forecasting
Publisher : National Academies Press
Page : 351 pages
File Size : 48,8 Mb
Release : 2016-08-22
Category : Science
ISBN : 9780309388801
As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.
Author : Andrew J. Majda
Publisher : Springer
Page : 91 pages
File Size : 49,7 Mb
Release : 2016-09-14
Category : Mathematics
ISBN : 9783319322179
This volume is a research expository article on the applied mathematics of turbulent dynamical systems through the paradigm of modern applied mathematics. It involves the blending of rigorous mathematical theory, qualitative and quantitative modeling, and novel numerical procedures driven by the goal of understanding physical phenomena which are of central importance to the field. The contents cover general framework, concrete examples, and instructive qualitative models. Accessible open problems are mentioned throughout. Topics covered include: · Geophysical flows with rotation, topography, deterministic and random forcing · New statistical energy principles for general turbulent dynamical systems, with applications · Linear statistical response theory combined with information theory to cope with model errors · Reduced low order models · Recent mathematical strategies for online data assimilation of turbulent dynamical systems as well as rigorous results for finite ensemble Kalman filters The volume will appeal to graduate students and researchers working mathematics, physics and engineering and particularly those in the climate, atmospheric and ocean sciences interested in turbulent dynamical as well as other complex systems.
Author : Michael R. Berthold,Ad Feelders,Georg Krempl
Publisher : Springer Nature
Page : 601 pages
File Size : 40,5 Mb
Release : 2020-04-22
Category : Computers
ISBN : 9783030445843
This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.
Author : Alik Ismail-Zadeh,Fabio Castelli,Dylan Jones,Sabrina Sanchez
Publisher : Cambridge University Press
Page : 369 pages
File Size : 47,9 Mb
Release : 2023-06-30
Category : Mathematics
ISBN : 9781009180405
A comprehensive reference on data assimilation and inverse problems, and their applications across a broad range of geophysical disciplines, ideal for researchers and graduate students. It highlights the importance of data assimilation for understanding dynamical processes of the Earth and its space environment, and summarises recent advances.
