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statistical methods in the atmospheric sciences 4th edition: Statistical Methods in the Atmospheric Sciences Daniel S. Wilks, 2019-06-09 Statistical Methods in the Atmospheric Sciences, Fourth Edition, continues the tradition of trying to meet the needs of students, researchers and operational practitioners. This updated edition not only includes expanded sections built upon the strengths of the prior edition, but also provides new content where there have been advances in the field, including Bayesian analysis, forecast verification and a new chapter dedicated to ensemble forecasting. - Provides a strong, yet concise, introduction to applied statistics that is specific to atmospheric science - Contains revised and expanded sections on nonparametric tests, test multiplicity and quality uncertainty descriptors - Includes new sections on ANOVA, quantile regression, the lasso and other regularization methods, regression trees, changepoint detection, ensemble forecasting and exponential smoothing |
statistical methods in the atmospheric sciences 4th edition: Statistical Methods in the Atmospheric Sciences Daniel S. Wilks, 2011-07-04 Statistical Methods in the Atmospheric Sciences, Third Edition, explains the latest statistical methods used to describe, analyze, test, and forecast atmospheric data. This revised and expanded text is intended to help students understand and communicate what their data sets have to say, or to make sense of the scientific literature in meteorology, climatology, and related disciplines. In this new edition, what was a single chapter on multivariate statistics has been expanded to a full six chapters on this important topic. Other chapters have also been revised and cover exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, and time series analysis. There is now an expanded treatment of resampling tests and key analysis techniques, an updated discussion on ensemble forecasting, and a detailed chapter on forecast verification. In addition, the book includes new sections on maximum likelihood and on statistical simulation and contains current references to original research. Students will benefit from pedagogical features including worked examples, end-of-chapter exercises with separate solutions, and numerous illustrations and equations. This book will be of interest to researchers and students in the atmospheric sciences, including meteorology, climatology, and other geophysical disciplines. - Accessible presentation and explanation of techniques for atmospheric data summarization, analysis, testing and forecasting - Many worked examples - End-of-chapter exercises, with answers provided |
statistical methods in the atmospheric sciences 4th edition: Statistical Methods in the Atmospheric Sciences Daniel S. Wilks, 1995 |
statistical methods in the atmospheric sciences 4th edition: Statistical Methods and Calculation Skills Isabel Willemse, 2009 This third edition aims to equip students with the skills to apply statistical analysis and quantitative techniques in research and the working environment where their knowledge can lead to effective decision-making. The book effectively combines theory and practice in providing: A theoretical framework for statistical problem-solving; A practical step-by-step approach to applying methods and calculations; A complete list of outcomes in each unit; Worked examples with detailed explanations; Practice in the form of guided activities and a range of self-test questions. The contents include the collection and presentation of data, descriptive measures, index numbers, regression and correlation analysis, time series, probability and probability distributions, statistical estimation and hypothesis testing. Calculation skills are revised in Part 2, a section that covers technology, elementary calculations, percentages and ratios, equations, graph construction and interest calculations. This edition includes examples and activities which cover not only the business field, but also food and biotechnology, engineering, medicine and environmental studies. |
statistical methods in the atmospheric sciences 4th edition: Statistical Methods in Water Resources D.R. Helsel, R.M. Hirsch, 1993-03-03 Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences. |
statistical methods in the atmospheric sciences 4th edition: OpenIntro Statistics David Diez, Christopher Barr, Mine Çetinkaya-Rundel, 2015-07-02 The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources. |
statistical methods in the atmospheric sciences 4th edition: Statistical Optics Joseph W. Goodman, 2015-05-04 This book discusses statistical methods that are useful for treating problems in modern optics, and the application of these methods to solving a variety of such problems This book covers a variety of statistical problems in optics, including both theory and applications. The text covers the necessary background in statistics, statistical properties of light waves of various types, the theory of partial coherence and its applications, imaging with partially coherent light, atmospheric degradations of images, and noise limitations in the detection of light. New topics have been introduced in the second edition, including: Analysis of the Vander Pol oscillator model of laser light Coverage on coherence tomography and coherence multiplexing of fiber sensors An expansion of the chapter on imaging with partially coherent light, including several new examples An expanded section on speckle and its properties New sections on the cross-spectrum and bispectrum techniques for obtaining images free from atmospheric distortions A new section on imaging through atmospheric turbulence using coherent light The addition of the effects of “read noise” to the discussions of limitations encountered in detecting very weak optical signals A number of new problems and many new references have been added Statistical Optics, Second Edition is written for researchers and engineering students interested in optics, physicists and chemists, as well as graduate level courses in a University Engineering or Physics Department. |
statistical methods in the atmospheric sciences 4th edition: An Introduction to Dynamic Meteorology James R. Holton, 1979 For advanced undergraduate and beginning graduate students in atmospheric, oceanic, and climate science, Atmosphere, Ocean and Climate Dynamics is an introductory textbook on the circulations of the atmosphere and ocean and their interaction, with an emphasis on global scales. It will give students a good grasp of what the atmosphere and oceans look like on the large-scale and why they look that way. The role of the oceans in climate and paleoclimate is also discussed. The combination of observations, theory and accompanying illustrative laboratory experiments sets this text apart by making it accessible to students with no prior training in meteorology or oceanography. * Written at a mathematical level that is appealing for undergraduates and beginning graduate students * Provides a useful educational tool through a combination of observations and laboratory demonstrations which can be viewed over the web * Contains instructions on how to reproduce the simple but informative laboratory experiments * Includes copious problems (with sample answers) to help students learn the material. |
statistical methods in the atmospheric sciences 4th edition: Fundamentals of Modern Statistical Methods Rand R. Wilcox, 2010-03-10 Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques, even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming the reader has any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research. The second edition of this book includes a number of advances and insights that have occurred since the first edition appeared. Included are new results relevant to medians, regression, measures of association, strategies for comparing dependent groups, methods for dealing with heteroscedasticity, and measures of effect size. |
statistical methods in the atmospheric sciences 4th edition: Introductory Econometrics for Finance Chris Brooks, 2008-05-22 This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details. |
statistical methods in the atmospheric sciences 4th edition: Multivariate Statistical Methods Bryan F.J. Manly, 2004-07-06 Multivariate methods are now widely used in the quantitative sciences as well as in statistics because of the ready availability of computer packages for performing the calculations. While access to suitable computer software is essential to using multivariate methods, using the software still requires a working knowledge of these methods and how they can be used. Multivariate Statistical Methods: A Primer, Third Edition introduces these methods and provides a general overview of the techniques without overwhelming you with comprehensive details. This thoroughly revised, updated edition of a best-selling introductory text retains the author's trademark clear, concise style but includes a range of new material, new exercises, and supporting materials on the Web. New in the Third Edition: Fully updated references Additional examples and exercises from the social and environmental sciences A comparison of the various statistical software packages, including Stata, Statistica, SAS Minitab, and Genstat, particularly in terms of their ease of use by beginners In his efforts to produce a book that is as short as possible and that enables you to begin to use multivariate methods in an intelligent manner, the author has produced a succinct and handy reference. With updated information on multivariate analyses, new examples using the latest software, and updated references, this book provides a timely introduction to useful tools for statistical analysis. |
statistical methods in the atmospheric sciences 4th edition: Principles of Atmospheric Science John E. Frederick, 2008 Providing a comprehensive introduction to atmospheric science, the author identifies the fundamental concepts and principles related to atmospheric science. |
statistical methods in the atmospheric sciences 4th edition: Statistics for Analytical Chemistry Jane C. Miller, James N. Miller, 1992 |
statistical methods in the atmospheric sciences 4th edition: Parameterization Schemes David J. Stensrud, 2009-12-03 Numerical weather prediction models play an increasingly important role in meteorology, both in short- and medium-range forecasting and global climate change studies. The most important components of any numerical weather prediction model are the subgrid-scale parameterization schemes, and the analysis and understanding of these schemes is a key aspect of numerical weather prediction. This book provides in-depth explorations of the most commonly used types of parameterization schemes that influence both short-range weather forecasts and global climate models. Several parameterizations are summarised and compared, followed by a discussion of their limitations. Review questions at the end of each chapter enable readers to monitor their understanding of the topics covered, and solutions are available to instructors at www.cambridge.org/9780521865401. This will be an essential reference for academic researchers, meteorologists, weather forecasters, and graduate students interested in numerical weather prediction and its use in weather forecasting. |
statistical methods in the atmospheric sciences 4th edition: Data Analysis for the Geosciences Michael W. Liemohn, 2023-10-10 An initial course in scientific data analysis and hypothesis testing designed for students in all science, technology, engineering, and mathematics disciplines Data Analysis for the Geosciences: Essentials of Uncertainty, Comparison, and Visualization is a textbook for upper-level undergraduate STEM students, designed to be their statistics course in a degree program. This volume provides a comprehensive introduction to data analysis, visualization, and data-model comparisons and metrics, within the framework of the uncertainty around the values. It offers a learning experience based on real data from the Earth, ocean, atmospheric, space, and planetary sciences. About this volume: Serves as an initial course in scientific data analysis and hypothesis testing Focuses on the methods of data processing Introduces a wide range of analysis techniques Describes the many ways to compare data with models Centers on applications rather than derivations Explains how to select appropriate statistics for meaningful decisions Explores the importance of the concept of uncertainty Uses examples from real geoscience observations Homework problems at the end of chapters The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. |
statistical methods in the atmospheric sciences 4th edition: Statistical Methods for Psychology David C. Howell, 2013 STATISTICAL METHODS FOR PSYCHOLOGY, 8E, International Edition surveys the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasizes conceptual understanding. This Eighth Edition continues to focus students on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment. New and expanded topics—reflecting the evolving realm of statistical methods—include effect size, meta-analysis, and treatment of missing data. |
statistical methods in the atmospheric sciences 4th edition: Statistics for Research Shirley Dowdy, Stanley Wearden, Daniel Chilko, 2011-09-26 Praise for the Second Edition Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly.—The UMAP Journal Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible for today's statisticians to do more in less time than ever before. The Third Edition of this bestselling text reflects how the changes in the computing environment have transformed the way statistical analyses are performed today. Based on extensive input from university statistics departments throughout the country, the authors have made several important and timely revisions, including: Additional material on probability appears early in the text New sections on odds ratios, ratio and difference estimations, repeated measure analysis, and logistic regression New examples and exercises, many from the field of the health sciences Printouts of computer analyses on all complex procedures An accompanying Web site illustrating how to use SAS® and JMP® for all procedures The text features the most commonly used statistical techniques for the analysis of research data. As in the earlier editions, emphasis is placed on how to select the proper statistical procedure and how to interpret results. Whenever possible, to avoid using the computer as a black box that performs a mysterious process on the data, actual computational procedures are also given. A must for scientists who analyze data, professionals and researchers who need a self-teaching text, and graduate students in statistical methods, Statistics for Research, Third Edition brings the methodology up to date in a very practical and accessible way. |
statistical methods in the atmospheric sciences 4th edition: Mesoscale Meteorology in Midlatitudes Paul Markowski, Yvette Richardson, 2011-09-20 Mesoscale Meteorology in Mid-Latitudes presents the dynamics of mesoscale meteorological phenomena in a highly accessible, student-friendly manner. The book's clear mathematical treatments are complemented by high-quality photographs and illustrations. Comprehensive coverage of subjects including boundary layer mesoscale phenomena, orographic phenomena and deep convection is brought together with the latest developments in the field to provide an invaluable resource for mesoscale meteorology students. Mesoscale Meteorology in Mid-Latitudes functions as a comprehensive, easy-to-use undergraduate textbook while also providing a useful reference for graduate students, research scientists and weather industry professionals. Illustrated in full colour throughout Covers the latest developments and research in the field Comprehensive coverage of deep convection and its initiation Uses real life examples of phenomena taken from broad geographical areas to demonstrate the practical aspects of the science |
statistical methods in the atmospheric sciences 4th edition: Python Recipes for Earth Sciences Martin H. Trauth, 2024-10-07 Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. Codes are available online through GitHub. |
statistical methods in the atmospheric sciences 4th edition: Statistics Michael J. Crawley, 2005-05-06 Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R. |
statistical methods in the atmospheric sciences 4th edition: Analysis of Climate Variability Hans v. Storch, Antonio Navarra, 2013-11-11 EUROPEAN SCHOOl OF CLiMATOlOGY AND NATURAL HAZARDS The training of scientific and technical personnel and the development of highly qualified scientists are, and have always been, among the important concerns of the European Commission. Advanced training is an important requirement for the implementation of a common EU policy in science and technology. The European School of Climatology and Natural Hazards was started as apart of the training and education activities of the European Programme on Climatology and Natural Hazards (EPOCH), and is continued under the subsequent research programme (ENVIRONMENT 1990-1994). The school consists of annual courses on specialised subjects within re search in climatology and natural hazards, and is open to graduating, grad uate and post graduate students in these fields. Each of the courses is organized in cooperation with a European Institu tion involved in the current research programme, and is aimed at giving to the students formal lectures and participation in informal discussions with leading researchers. The present volume is based on the lectures given at the course held on the island of Elba from the 30th October to the 6th of November 1993 on Statistical Analysis of Climate Variability. It features selected and extended presentations, and represents an important contribution to advanced studies in climate statistical analysis, supplementing more traditional texts. I trust that all those involved in research related to climate change and climate variability will appreciate this work and will benefit from the com prehensive and state-of-the-art information it provides. |
statistical methods in the atmospheric sciences 4th edition: The Cambridge Dictionary of Statistics B. S. Everitt, 2006-08-17 If you use statistics and need easy access to simple, reliable definitions and explanations of modern statistical concepts, then look no further than this dictionary. Over 3600 terms are defined, covering medical, survey, theoretical, and applied statistics, including computational aspects. Entries are provided for standard and specialized statistical software. In addition, short biographies of over 100 important statisticians are given. Definitions provide enough mathematical detail to clarify concepts and give standard formulae when these are helpful. The majority of definitions then give a reference to a book or article where the user can seek further or more specialized information, and many are accompanied by graphical material to aid understanding. |
statistical methods in the atmospheric sciences 4th edition: Multivariate Statistical Methods Bryan F. J. Manly, 2017-09-30 Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis. |
statistical methods in the atmospheric sciences 4th edition: Introduction to Probability and Statistics for Engineers and Scientists Sheldon M. Ross, 1987 Elements of probability; Random variables and expectation; Special; random variables; Sampling; Parameter estimation; Hypothesis testing; Regression; Analysis of variance; Goodness of fit and nonparametric testing; Life testing; Quality control; Simulation. |
statistical methods in the atmospheric sciences 4th edition: Probability and Statistical Inference Robert V. Hogg, Elliot A. Tanis, 1988 This user-friendly introduction to the mathematics of probability and statistics (for readers with a background in calculus) uses numerous applications--drawn from biology, education, economics, engineering, environmental studies, exercise science, health science, manufacturing, opinion polls, psychology, sociology, and sports--to help explain and motivate the concepts. A review of selected mathematical techniques is included, and an accompanying CD-ROM contains many of the figures (many animated), and the data included in the examples and exercises (stored in both Minitab compatible format and ASCII). Empirical and Probability Distributions. Probability. Discrete Distributions. Continuous Distributions. Multivariable Distributions. Sampling Distribution Theory. Importance of Understanding Variability. Estimation. Tests of Statistical Hypotheses. Theory of Statistical Inference. Quality Improvement Through Statistical Methods. For anyone interested in the Mathematics of Probability and Statistics. |
statistical methods in the atmospheric sciences 4th edition: Atmospheric Science John M. Wallace, Peter V. Hobbs, 2006-03-24 Atmospheric Science, Second Edition, is the long-awaited update of the classic atmospheric science text, which helped define the field nearly 30 years ago and has served as the cornerstone for most university curricula. Now students and professionals alike can use this updated classic to understand atmospheric phenomena in the context of the latest discoveries, and prepare themselves for more advanced study and real-life problem solving. This latest edition of Atmospheric Science, has been revamped in terms of content and appearance. It contains new chapters on atmospheric chemistry, the Earth system, the atmospheric boundary layer, and climate, as well as enhanced treatment of atmospheric dynamics, radiative transfer, severe storms, and global warming. The authors illustrate concepts with full-color, state-of-the-art imagery and cover a vast amount of new information in the field. Extensive numerical and qualitative exercises help students apply basic physical principles to atmospheric problems. There are also biographical footnotes summarizing the work of key scientists, along with a student companion website that hosts climate data; answers to quantitative exercises; full solutions to selected exercises; skew-T log p chart; related links, appendices; and more. The instructor website features: instructor's guide; solutions to quantitative exercises; electronic figures from the book; plus supplementary images for use in classroom presentations. Meteorology students at both advanced undergraduate and graduate levels will find this book extremely useful. - Full-color satellite imagery and cloud photographs illustrate principles throughout - Extensive numerical and qualitative exercises emphasize the application of basic physical principles to problems in the atmospheric sciences - Biographical footnotes summarize the lives and work of scientists mentioned in the text, and provide students with a sense of the long history of meteorology - Companion website encourages more advanced exploration of text topics: supplementary information, images, and bonus exercises |
statistical methods in the atmospheric sciences 4th edition: A First Course in Bayesian Statistical Methods Peter D. Hoff, 2010-11-19 A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run as-is allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods. |
statistical methods in the atmospheric sciences 4th edition: Statistics in a Nutshell Sarah Boslaugh, 2012-11-15 A clear and concise introduction and reference for anyone new to the subject of statistics. |
statistical methods in the atmospheric sciences 4th edition: Downscaling Techniques for High-Resolution Climate Projections Rao Kotamarthi, Katharine Hayhoe, Linda O. Mearns, Donald Wuebbles, Jennifer Jacobs, Jennifer Jurado, 2021-02-11 Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for policy makers and practitioners interested in climate risk and resilience. |
statistical methods in the atmospheric sciences 4th edition: Atmospheric Rivers F. Martin Ralph, Michael D. Dettinger, Jonathan J. Rutz, Duane E. Waliser, 2020-07-11 This book is the standard reference based on roughly 20 years of research on atmospheric rivers, emphasizing progress made on key research and applications questions and remaining knowledge gaps. The book presents the history of atmospheric-rivers research, the current state of scientific knowledge, tools, and policy-relevant (science-informed) problems that lend themselves to real-world application of the research—and how the topic fits into larger national and global contexts. This book is written by a global team of authors who have conducted and published the majority of critical research on atmospheric rivers over the past years. The book is intended to benefit practitioners in the fields of meteorology, hydrology and related disciplines, including students as well as senior researchers. |
statistical methods in the atmospheric sciences 4th edition: Applied Data Mining Paolo Giudici, 2005-09-27 Data mining can be defined as the process of selection, explorationand modelling of large databases, in order to discover models andpatterns. The increasing availability of data in the currentinformation society has led to the need for valid tools for itsmodelling and analysis. Data mining and applied statistical methodsare the appropriate tools to extract such knowledge from data.Applications occur in many different fields, including statistics,computer science, machine learning, economics, marketing andfinance. This book is the first to describe applied data mining methodsin a consistent statistical framework, and then show how they canbe applied in practice. All the methods described are eithercomputational, or of a statistical modelling nature. Complexprobabilistic models and mathematical tools are not used, so thebook is accessible to a wide audience of students and industryprofessionals. The second half of the book consists of nine casestudies, taken from the author's own work in industry, thatdemonstrate how the methods described can be applied to realproblems. Provides a solid introduction to applied data mining methods ina consistent statistical framework Includes coverage of classical, multivariate and Bayesianstatistical methodology Includes many recent developments such as web mining,sequential Bayesian analysis and memory based reasoning Each statistical method described is illustrated with real lifeapplications Features a number of detailed case studies based on appliedprojects within industry Incorporates discussion on software used in data mining, withparticular emphasis on SAS Supported by a website featuring data sets, software andadditional material Includes an extensive bibliography and pointers to furtherreading within the text Author has many years experience teaching introductory andmultivariate statistics and data mining, and working on appliedprojects within industry A valuable resource for advanced undergraduate and graduatestudents of applied statistics, data mining, computer science andeconomics, as well as for professionals working in industry onprojects involving large volumes of data - such as in marketing orfinancial risk management. |
statistical methods in the atmospheric sciences 4th edition: An Introduction to Atmospheric Physics David G. Andrews, 2010 A quantitative introduction to the Earth's atmosphere for intermediate-advanced undergraduate and graduate students, with an emphasis on underlying physical principles. This edition has been brought completely up-to-date, and now includes a new chapter on the physics of climate change which builds upon material introduced in earlier chapters, giving the student a broad understanding of some of the physical concepts underlying this most important and topical subject. In contrast to many other books on atmospheric science, the emphasis is on the underlying physics. Atmospheric applications are developed mainly in the problems given at the end of each chapter. The book is an essential resource for all students of atmospheric physics as part of an atmospheric science, meteorology, physics, Earth science, planetary science, or applied mathematics course--Provided by publisher. |
statistical methods in the atmospheric sciences 4th edition: The Handbook of International Humanitarian Law Dieter Fleck, 2013-08-29 This fully updated third edition of The Handbook of International Humanitarian Law sets out an international manual of humanitarian law accompanied by case analysis and extensive explanatory commentary by a team of distinguished and internationally renowned experts. The new edition takes account of recent developments in the law, including the 2010 amendments to the ICC Statute, the progressive evolution of customary law, and new jurisprudence from national and international courts and tribunals. It sheds light on controversial topics like direct participation in hostilities; air and missile warfare; belligerent occupation; operational detention; and the protection of the environment in armed conflict. The book also addresses the growing need to consider the interface between international humanitarian law and human rights, as well as other branches of international law, both during armed conflicts and in post-conflict situations. The commentary both deepens reflection on such innovations, and critically reconsiders views expressed in earlier editions to provide a contemporary analysis of this changing field. Renowned international lawyers offer a broad spectrum of legal opinions, restating the law in this area, which is applicable worldwide. Particular attention is paid to problems of application of the law in recent military campaigns, which are assessed and interpreted in a practice-oriented manner. Based on best-practice rules of global importance, this book gives invaluable guidance to practitioners and scholars of this important body of law. |
statistical methods in the atmospheric sciences 4th edition: Atmosphere, Ocean and Climate Dynamics John Marshall, R. Alan Plumb, 2007-12-19 For advanced undergraduate and beginning graduate students in atmospheric, oceanic, and climate science, Atmosphere, Ocean and Climate Dynamics is an introductory textbook on the circulations of the atmosphere and ocean and their interaction, with an emphasis on global scales. It will give students a good grasp of what the atmosphere and oceans look like on the large-scale and why they look that way. The role of the oceans in climate and paleoclimate is also discussed. The combination of observations, theory and accompanying illustrative laboratory experiments sets this text apart by making it accessible to students with no prior training in meteorology or oceanography.* Written at a mathematical level that is appealing for undergraduates andbeginning graduate students* Provides a useful educational tool through a combination of observations andlaboratory demonstrations which can be viewed over the web* Contains instructions on how to reproduce the simple but informativelaboratory experiments* Includes copious problems (with sample answers) to help students learn thematerial. |
statistical methods in the atmospheric sciences 4th edition: Methods and Applications of Statistics in the Atmospheric and Earth Sciences Narayanaswamy Balakrishnan, 2012-11-19 Explore the classic and cutting-edge quantitative methods for understanding environmental science research Based on the multifaceted 16-volume Encyclopedia of Statistical Sciences, Second Edition, Methods and Applications of Statistics in the Atmospheric and Earth Sciences offers guidance on the application of statistical methods for conducting research in these fields of study. With contributions from more than 100 leading experts in academia and industry, this volume combines key articles from the Encyclopedia with newly developed topics addressing some of the more critical issues, including pollution, droughts, and volcanic activity. Readers will gain a thorough understanding of cutting-edge methods for the acquisition and analysis of data across a wide range of subject areas, from geophysics, geology, and biogeography to meteorology, forestry, agriculture, animal science, and ornithology. The book features new and updated content on quantitative methods and their use in understanding the latest topics in social research, including: Drought Analysis and Forecasting Childhood Obesity Ranked Set Sampling Methodology for Environmental Data Species Richness and Shared Species Richness Geographic Information Systems Each contribution offers authoritative yet easily accessible coverage of statistical concepts. With updated references and discussion of emerging topics, readers are provided with the various statistical methods, techniques, strategies, and applications that are essential for tackling critical issues in environmental science research. Featuring a balance of classical and cutting-edge methodologies, Methods and Applications of Statistics in the Atmospheric and Earth Sciences is an excellent resource for researchers, professionals, and students in the fields of sociology, psychology, philosophy, education, political science, and the related disciplines who would like to learn about the uses of statistics in gathering, reporting, and analyzing data. |
statistical methods in the atmospheric sciences 4th edition: Storm and Cloud Dynamics William R. Cotton, George Bryan, Susan C. van den Heever, 2010-12-21 Storm and Cloud Dynamics focuses on the dynamics of clouds and of precipitating mesoscale meteorological systems. Clouds and precipitating mesoscale systems represent some of the most important and scientifically exciting weather systems in the world. These are the systems that produce torrential rains, severe winds including downburst and tornadoes, hail, thunder and lightning, and major snow storms. Forecasting such storms represents a major challenge since they are too small to be adequately resolved by conventional observing networks and numerical prediction models. - Provides a complete treatment of clouds integrating the analysis of air motions with cloud structure, microphysics, and precipitation mechanics - Describes and explains the basic types of clouds and cloud systems that occur in the atmosphere-fog, stratus, stratocumulus, altocumulus, altostratus, cirrus, thunderstorms, tornadoes, waterspouts, orographically induced clouds, mesoscale convection complexes, hurricanes, fronts, and extratropical cyclones - Summarizes the fundamentals, both observational and theoretical, of atmospheric dynamics, thermodynamics, cloud microphysics, and radar meteorology, allowing each type of cloud to be examined in depth - Integrates the latest field observations, numerical model simulations, and theory - Supplies a theoretical treatment suitable for the advanced undergraduate or graduate level, as well as post-graduate |
statistical methods in the atmospheric sciences 4th edition: Heatwaves Glenn McGregor, 2024-10-09 Distinctively, this book brings together an end-to-end understanding of heatwaves, that is, a consideration of their causes, consequences for human and natural systems and societal responses to them in the form of adaptation and mitigation actions. It advocates for recognizing the heatwave imperative and emphasizes that “heatwaves matter”. Together, the individual chapters make the point that “knowing heatwaves” from a holistic interdisciplinary perspective will assist with efforts towards heatwave risk reduction and building resilience to what is probably the most pervasive of a range of climate hazards. The book will be of interest to upper level undergraduate and taught postgraduate students and researchers in geography, climatology, environmental, atmospheric and population health sciences as well as climate and health researchers, urban planners, policy makers and the informed public with an interest in climate and society issues. |
statistical methods in the atmospheric sciences 4th edition: Common Errors in Statistics (and How to Avoid Them) Phillip I. Good, James W. Hardin, 2011-09-20 Praise for the Second Edition All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice. —Journal of Applied Statistics . . . a very engaging and valuable book for all who use statistics in any setting. —CHOICE . . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well. —MAA Reviews Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research. The Third Edition has been considerably expanded and revised to include: A new chapter on data quality assessment A new chapter on correlated data An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs Revamped exercises with a stronger emphasis on solutions An extended chapter on report preparation New sections on factor analysis as well as Poisson and negative binomial regression Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences. |
statistical methods in the atmospheric sciences 4th edition: Statistical Analysis of Empirical Data Scott Pardo, 2020-05-04 Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek guidance in defending their statistical decision-making in the worlds of research and practice. It is devoted to helping students and scholars find the information they need to select data analytic methods, and to speak knowledgeably about their statistical research processes. Each chapter opens with a conundrum relating to the selection of an analysis, or to explaining the nature of an analysis. Throughout the chapter, the analysis is described, along with some guidance in justifying the choices of that particular method. Designed to offer statistical knowledge to the non-specialist, this volume can be used in courses on research methods, or for courses on statistical applications to biological, medical, life, social, or physical sciences. It will also be useful to academic and industrial researchers in engineering and in the physical sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education in calculus. However, a brief review of fundamental concepts of probability and statistics, together with a primer on some concepts in elementary calculus and matrix algebra, is included. R code and sample datasets are provided. |
statistical methods in the atmospheric sciences 4th edition: Oxford Handbook of Public Health Practice Charles Guest, Walter Ricciardi, Ichiro Kawachi, Iain Lang, 2013-02-28 Fully revised and updated for the third edition, the Oxford Handbook of Public Health Practice remains the first resort for all those working in this broad field. Structured to assist with practical tasks, translating evidence into policy, and providing concise summaries and real-world issues from across the globe, this literally provides a world of experience at your fingertips. Easy-to-use, concise and practical, it is structured into seven parts that focus on the vital areas of assessment, data and information, direct action, policy, health-care systems, personal effectiveness and organisational development. Reflecting recent advances, the most promising developments in practical public health are presented, as well as maintaining essential summaries of core disciplines. This handbook is designed to assist students and practitioners around the world, for improved management of disasters, epidemics, health behaviour, acute and chronic disease prevention, community and government action, environmental health, vulnerable populations, and more. |
STATISTICAL Definition & Meaning - Merriam-Webster
The meaning of STATISTICAL is of, relating to, based on, or employing the principles of statistics. How to use statistical in a sentence.
STATISTICAL | English meaning - Cambridge Dictionary
There is very little statistical evidence. It was designed to facilitate the combination of qualitative methods with statistical analysis. The generalizations are advanced on the basis of statistical …
Statistics - Wikipedia
Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of quantitative data, or a label, as …
STATISTICAL Definition & Meaning | Dictionary.com
of, pertaining to, consisting of, or based on statistics. statistics. Examples have not been reviewed. In doing so, the judges said she could not point to “background circumstances” or …
What is Statistical Analysis? - GeeksforGeeks
Apr 15, 2025 · Statistical Analysis means gathering, understanding, and showing data to find patterns and connections that can help us make decisions. It includes lots of different ways to …
Statistics | Definition, Types, & Importance | Britannica
May 20, 2025 · statistics, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic …
Statistical - definition of statistical by The Free Dictionary
Define statistical. statistical synonyms, statistical pronunciation, statistical translation, English dictionary definition of statistical. adj. Of, relating to, or employing statistics or the principles of …
STATISTICAL definition and meaning | Collins English Dictionary
Statistical means relating to the use of statistics. The report contains a great deal of statistical information. Of or relating to statistics.... Click for English pronunciations, examples sentences, …
Introduction to Research Statistical Analysis: An Overview of the ...
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power.
Statistics - Definition, Examples, Mathematical Statistics
Statistics is defined as the process of collection of data, classifying data, representing the data for easy interpretation, and further analysis of data. Statistics also is referred to as arriving at …
STATISTICAL Definition & Meaning - Merriam-Webster
The meaning of STATISTICAL is of, relating to, based on, or employing the principles of statistics. How to use statistical in a sentence.
STATISTICAL | English meaning - Cambridge Dictionary
There is very little statistical evidence. It was designed to facilitate the combination of qualitative methods with statistical analysis. The generalizations are advanced on the basis of statistical …
Statistics - Wikipedia
Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of quantitative data, or a label, as …
STATISTICAL Definition & Meaning | Dictionary.com
of, pertaining to, consisting of, or based on statistics. statistics. Examples have not been reviewed. In doing so, the judges said she could not point to “background circumstances” or …
What is Statistical Analysis? - GeeksforGeeks
Apr 15, 2025 · Statistical Analysis means gathering, understanding, and showing data to find patterns and connections that can help us make decisions. It includes lots of different ways to …
Statistics | Definition, Types, & Importance | Britannica
May 20, 2025 · statistics, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic …
Statistical - definition of statistical by The Free Dictionary
Define statistical. statistical synonyms, statistical pronunciation, statistical translation, English dictionary definition of statistical. adj. Of, relating to, or employing statistics or the principles of …
STATISTICAL definition and meaning | Collins English Dictionary
Statistical means relating to the use of statistics. The report contains a great deal of statistical information. Of or relating to statistics.... Click for English pronunciations, examples sentences, …
Introduction to Research Statistical Analysis: An Overview of the ...
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power.
Statistics - Definition, Examples, Mathematical Statistics
Statistics is defined as the process of collection of data, classifying data, representing the data for easy interpretation, and further analysis of data. Statistics also is referred to as arriving at …