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Agriculture is particularly vulnerable to extreme climatic events, yet knowledge is lacking regarding the precise extent of losses caused by disasters in the sector. This analysis aims to provide the most extensive estimation of disaster losses (including non-hydrometeorological disasters) in the agricultural sector worldwide by including data from 197 countries and 186 commodities from 1991 to 2021, accounting for 12 000 time series and about 9 000 disaster events. The disaster events data is drawn from the Emergency Events Database (EM-DAT) and the records of yields, productions, cultivated areas, and prices for all commodities over the period from FAOSTAT.
This practical handbook provides a clearly structured, concise and comprehensive account of the huge variety of atmospheric and related measurements relevant to meteorologists and for the purpose of weather forecasting and climate research, but also to the practitioner in the wider field of environmental physics and ecology. The Springer Handbook of Atmospheric Measurements is divided into six parts: The first part offers instructive descriptions of the basics of atmospheric measurements and the multitude of their influencing factors, fundamentals of quality control and standardization, as well as equations and tables of atmospheric, water, and soil quantities. The subsequent parts present classical in-situ measurements as well as remote sensing techniques from both ground-based as well as airborn or satellite-based methods. The next part focusses on complex measurements and methods that integrate different techniques to establish more holistic data. Brief discussions of measurements in soils and water, at plants, in urban and rural environments and for renewable energies demonstrate the potential of such applications. The final part provides an overview of atmospheric and ecological networks. Written by distinguished experts from academia and industry, each of the 64 chapters provides in-depth discussions of the available devices with their specifications, aspects of quality control, maintenance as well as their potential for the future. A large number of thoroughly compiled tables of physical quantities, sensors and system characteristics make this handbook a unique, universal and useful reference for the practitioner and absolutely essential for researchers, students, and technicians.
Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: "(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers." Aslib Book Guide Vol 63, No. 9, 1998 "(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching." EOS Transactions, D.A. Jay, 1999 "(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations." Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 "(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries." E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999
Trends and Changes in Hydroclimatic Variables: Links to Climate Variability and Change discusses the change detection and trend analysis methods used to assess hydroclimatic variables in a changing climate. Changes and trends in hydroclimatic variables are assessed using state-of-the-art methods, such as non-linear trend estimation (including spline smoothing and local regression) and handling persistence (or serial auto-correlation in data) for assessing trends in different hydroclimatic variables (e.g. pre-whitening methods). This book offers a variety of real-life case studies and problem-solving techniques for a field that is rapidly evolving. Users will find methods to evaluate points where time series characteristics change and non-homogeneity in time series. In addition, it covers the subject of climate variability and change in an immense level of detail, including changes on precipitation, streamflow and sea levels. - Examines statistical methods for trend analysis, providing an excellent reference book for scholars, scientists, students and professionals - Offers an exhaustive treatment of several hydroclimatic variables in one book, providing readers with a comprehensive understanding of changes in hydroclimatic variables over time and space - Presents case studies dealing with changes in hydroclimatic variables in different geographical regions of the world - Focuses on climate variability and change, including an extensive assessment of trends and their associated links to climate variability and change
There is a dearth of relevant books dealing with both theory and application of time series analysis techniques, particularly in the field of water resources engineering. Therefore, many hydrologists and hydrogeologists face difficulties in adopting time series analysis as one of the tools for their research. This book fills this gap by providing a proper blend of theoretical and practical aspects of time sereies analysis. It deals with a comprehensive overview of time series characteristics in hydrology/water resources engineering, various tools and techniques for analyzing time series data, theoretical details of 31 available statistical tests along with detailed procedures for applying them to real-world time series data, theory and methodology of stochastic modelling, and current status of time series analysis in hydrological sciences. In adition, it demonstrates the application of most time series tests through a case study as well as presents a comparative performance evaluation of various time series tests, together with four invited case studies from India and abroad. This book will not only serve as a textbook for the students and teachers in water resources engineering but will also serve as the most comprehensive reference to educate researchers/scientists about the theory and practice of time series analysis in hydrological sciences. This book will be very useful to the students, researchers, teachers and professionals involved in water resources, hydrology, ecology, climate change, earth science, and environmental studies.
This book contains selected contributions from the geoENV98 - the Second European Conference on Geostatistics for Environmental Sciences, held in Valencia, Spain in November 1998. This second book of the geoENV series illustrates the developments on geostatistics as applied to the environmental sciences which have occurred during the past two years. It also presents practical applications which will be of interest to both researchers and practitioners. The book starts with three keynote papers on ecology, climatology and soil science, followed by forty-three contributions. The contents of the book are eminently practical. The objective of the editors was to compile a set of papers in which the reader could perceive how geostatistics is applied within the environmental sciences. A few selected theoretical contributions are also included. The papers are organized in the following seven main areas Air pollution Climatology Ecology Hydrogeology Soil Science Theory Other applications presenting applications varying from particle matter analysis, noise exposure sampling, space-time modeling of ozone levels, downscaling of precipitation, kriging with categorical external drift, analysis of fish abundance, combining variograms and radio-telemetry in ecology, kriging radionuclide deposition, mapping of soil contamination, network design for soil monitoring, inverse modeling in hydrogeology, groundwater transport modeling, coastal evolution mapping to spatial modeling of cancer ratios. Audience: This publication will be of great interest and practical value to geostatisticians working both in academia and in industry.
Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.
MOP 28 serves as a basic reference, providing a thorough, up-to-date guide for hydrologists.
While most books on missing data focus on applying sophisticated statistical techniques to deal with the problem after it has occurred, this volume provides a methodology for the control and prevention of missing data. In clear, nontechnical language, the authors help the reader understand the different types of missing data and their implications for the reliability, validity, and generalizability of a study’s conclusions. They provide practical recommendations for designing studies that decrease the likelihood of missing data, and for addressing this important issue when reporting study results. When statistical remedies are needed--such as deletion procedures, augmentation methods, and single imputation and multiple imputation procedures--the book also explains how to make sound decisions about their use. Patrick E. McKnight's website offers a periodically updated annotated bibliography on missing data and links to other Web resources that address missing data.