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Author: Manfred Mudelsee
Publisher: Springer Science & Business Media
ISBN: 9048194822
Category : Science
Languages : en
Pages : 474
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Book Description
Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.
Author: Manfred Mudelsee
Publisher: Springer Science & Business Media
ISBN: 9048194822
Category : Science
Languages : en
Pages : 474
Get Book
Book Description
Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.
Author: Zhihua Zhang
Publisher: Springer
ISBN: 3319673408
Category : Science
Languages : en
Pages : 287
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Book Description
This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.
Author: Victor Privalsky
Publisher: Springer Nature
ISBN: 3030580555
Category : Science
Languages : en
Pages : 253
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Book Description
This book gives the reader the basic knowledge of the theory of random processes necessary for applying to study climatic time series. It contains many examples in different areas of time series analysis such as autoregressive modelling and spectral analysis, linear extrapolation, simulation, causality, relations between scalar components of multivariate time series, and reconstructions of climate data. As an important feature, the book contains many practical examples and recommendations about how to deal and how not to deal with applied problems of time series analysis in climatology or any other science where the time series are short.
Author: Helmut Pruscha
Publisher: Springer Science & Business Media
ISBN: 3642320848
Category : Mathematics
Languages : en
Pages : 179
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Book Description
The book presents the application of statistical methods to climatological data on temperature and precipitation. It provides specific techniques for treating series of yearly, monthly and daily records. The results’ potential relevance in the climate context is discussed. The methodical tools are taken from time series analysis, from periodogram and wavelet analysis, from correlation and principal component analysis, and from categorical data and event-time analysis. The applied models are - among others - the ARIMA and GARCH model, and inhomogeneous Poisson processes. Further, we deal with a number of special statistical topics, e.g. the problem of trend-, season- and autocorrelation-adjustment, and with simultaneous statistical inference. Programs in R and data sets on climate series, provided at the author’s homepage, enable readers (statisticians, meteorologists, other natural scientists) to perform their own exercises and discover their own applications.
Author: Chester F. Ropelewski
Publisher: Cambridge University Press
ISBN: 1108573371
Category : Science
Languages : en
Pages : 391
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Book Description
Sensational images and stories about variations in Earth's climate and their impacts on society are pervasive in the media. The scientific basis for these stories is often not understood by the general public, nor even by those with a scientific background in fields other than climate science. This book is a comprehensive resource that will enable the reader to understand and appreciate the significance of the flood of climate information. It is an excellent non-mathematical resource for learning the fundamentals of climate analysis, as well as a reference for non-climate experts that need to use climate information and data. The focus is on the basics of the climate system, how climate is observed and how the observations are transformed into datasets useful for monitoring the climate. Each chapter contains Discussion Questions. This is an invaluable textbook on climate analysis for advanced students, and a reference textbook for researchers and practitioners.
Author: Manfred Mudelsee
Publisher: Cambridge University Press
ISBN: 1107033187
Category :
Languages : en
Pages : 213
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Book Description
The risks posed by climate change and its effect on climate extremes are an increasingly pressing societal problem. This book provides an accessible overview of the statistical analysis methods which can be used to investigate climate extremes and analyse potential risk. The statistical analysis methods are illustrated with case studies on extremes in the three major climate variables: temperature, precipitation, and wind speed. The book also provides datasets and access to appropriate analysis software, allowing the reader to replicate the case study calculations. Providing the necessary tools to analyse climate risk, this book is invaluable for students and researchers working in the climate sciences, as well as risk analysts interested in climate extremes.
Author: Nina Golyandina
Publisher: CRC Press
ISBN: 9781420035841
Category : Mathematics
Languages : en
Pages : 322
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Book Description
Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing. However, despite the promise it holds for time series applications in other disciplines, SSA is not widely known among statisticians and econometrists, and although the basic SSA algorithm looks simple, understanding what it does and where its pitfalls lay is by no means simple. Analysis of Time Series Structure: SSA and Related Techniques provides a careful, lucid description of its general theory and methodology. Part I introduces the basic concepts, and sets forth the main findings and results, then presents a detailed treatment of the methodology. After introducing the basic SSA algorithm, the authors explore forecasting and apply SSA ideas to change-point detection algorithms. Part II is devoted to the theory of SSA. Here the authors formulate and prove the statements of Part I. They address the singular value decomposition (SVD) of real matrices, time series of finite rank, and SVD of trajectory matrices. Based on the authors' original work and filled with applications illustrated with real data sets, this book offers an outstanding opportunity to obtain a working knowledge of why, when, and how SSA works. It builds a strong foundation for successfully using the technique in applications ranging from mathematics and nonlinear physics to economics, biology, oceanology, social science, engineering, financial econometrics, and market research.
Author: Zhihua Zhang
Publisher: Elsevier
ISBN: 0128005831
Category : Science
Languages : en
Pages : 494
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Book Description
Mathematical and Physical Fundamentals of Climate Change is the first book to provide an overview of the math and physics necessary for scientists to understand and apply atmospheric and oceanic models to climate research. The book begins with basic mathematics then leads on to specific applications in atmospheric and ocean dynamics, such as fluid dynamics, atmospheric dynamics, oceanic dynamics, and glaciers and sea level rise. Mathematical and Physical Fundamentals of Climate Change provides a solid foundation in math and physics with which to understand global warming, natural climate variations, and climate models. This book informs the future users of climate models and the decision-makers of tomorrow by providing the depth they need. Developed from a course that the authors teach at Beijing Normal University, the material has been extensively class-tested and contains online resources, such as presentation files, lecture notes, solutions to problems and MATLab codes. Includes MatLab and Fortran programs that allow readers to create their own models Provides case studies to show how the math is applied to climate research Online resources include presentation files, lecture notes, and solutions to problems in book for use in classroom or self-study
Author: Claude Duchon
Publisher: John Wiley & Sons
ISBN: 9780470971994
Category : Science
Languages : en
Pages : 0
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Book Description
Time Series Analysis in Meteorology and Climatology provides an accessible overview of this notoriously difficult subject. Clearly structured throughout, the authors develop sufficient theoretical foundation to understand the basis for applying various analytical methods to a time series and show clearly how to interpret the results. Taking a unique approach to the subject, the authors use a combination of theory and application to real data sets to enhance student understanding throughout the book. This book is written for those students that have a data set in the form of a time series and are confronted with the problem of how to analyse this data. Each chapter covers the various methods that can be used to carry out this analysis with coverage of the necessary theory and its application. In the theoretical section topics covered include; the mathematical origin of spectrum windows, leakage of variance and understanding spectrum windows. The applications section includes real data sets for students to analyse. Scalar variables are used for ease of understanding for example air temperatures, wind speed and precipitation. Students are encouraged to write their own computer programmes and data sets are provided to enable them to recognize quickly whether their programme is working correctly- one data set is provided with artificial data and the other with real data where the students are required to physically interpret the results of their periodgram analysis. Based on the acclaimed and long standing course at the University of Oklahoma and part of the RMetS Advancing Weather and Climate Science Series, this book is distinct in its approach to the subject matter in that it is written specifically for readers in meteorology and climatology and uses a mix of theory and application to real data sets.
Author: Jennifer L. Castle
Publisher: Now Publishers
ISBN: 9781680837087
Category : Business & Economics
Languages : en
Pages : 190
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Book Description
Climate Econometrics: An Overview provides a review of the research in this new and growing field. The structure of the monograph is as follows: First, section 2 describes econometric methods for empirical climate modeling that can account for wide-sense non-stationarity, namely both stochastic trends and location shifts, with possibly large outliers, as well as dynamics and non-linearities. Section 3 considers hazards confronting empirical modeling of nonstationary time-series data using an example where a counter-intuitive finding is hard to resolve. The framework has a clear subject-matter theory, so is not mere 'data mining', yet the empirical result flatly contradicts the well-based theory. Section 4 provides a brief excursion into climate science, mainly concerned with the composition of the Earth's atmosphere and the role of CO2 as a greenhouse gas. Section 5 considers the consequences, both good and bad, of the Industrial Revolution raising living standards beyond the wildest dreams of those living in the 17th century, but leading to dangerous levels of CO2 emissions from using fossil fuels and consider applications of climate econometrics against that background. Section 6 illustrates the approach by modeling past climate variability over the Ice Ages. Section 7 models UK annual CO2 emissions over 1860-2017 to walk through the stages of modeling empirical time series that manifest all the problems of wide-sense non-stationarity. Section 8 concludes and summarizes a number of other empirical applications.
