This handy reference introduces the subject of forecastverification and provides a review of the basic concepts,discussing different types of data that may be forecast. Each chapter covers a different type of predicted quantity(predictand), then looks at some of the relationships betweeneconomic value and skill scores, before moving on to review the keyconcepts and summarise aspects of forecast verification thatreceive the most attention in other disciplines. The book concludes with a discussion on the most importanttopics in the field that are the subject of current research orthat would benefit from future research. An easy to read guide of current techniques with real life casestudies An up-to-date and practical introduction to the differenttechniques and an examination of their strengths andweaknesses Practical advice given by some of the world?s leadingforecasting experts Case studies and illustrations of actual verification and itsinterpretation Comprehensive glossary and consistent statistical andmathematical definition of commonly used terms

Forecast Verification: A Practioner's Guide in Atmospheric Science, 2nd Edition provides an indispensible guide to this area of active research by combining depth of information with a range of topics to appeal both to professional practitioners and researchers and postgraduates. The editors have succeeded in presenting chapters by a variety of the leading experts in the field while still retaining a cohesive and highly accessible style. The book balances explanations of concepts with clear and useful discussion of the main application areas. Reviews of first edition: "This book will provide a good reference, and I recommend it especially for developers and evaluators of statistical forecast systems." (Bulletin of the American Meteorological Society; April 2004) "...a good mixture of theory and practical applications...well organized and clearly written..." (Royal Statistical Society, Vol.168, No.1, January 2005) NEW to the second edition: Completely updated chapter on the Verification of Spatial Forecasts taking account of the wealth of new research in the area New separate chapters on Probability Forecasts and Ensemble Forecasts Includes new chapter on Forecasts of Extreme Events and Warnings Includes new chapter on Seasonal and Climate Forecasts Includes new Appendix on Verification Software Cover image credit: The triangle of barplots shows a novel use of colour for visualizing probability forecasts of ternary categories – see Fig 6b of Jupp et al. 2011, On the visualisation, verification and recalibration of ternary probabilistic forecasts, Phil. Trans. Roy. Soc. (in press).

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

This volume is the outcome of contributions from 51 scientists who were invited to expose their latest findings on precipitation research and in particular, on the measurement, estimation and prediction of precipitation. The reader is presented with a blend of theoretical, mathematical and technical treatise of precipitation science but also with authentic applications, ranging from local field experiments and country-scale campaigns to multinational space endeavors.

This book offers a complete primer, covering the end-to-end process of forecast production, and bringing together a description of all the relevant aspects together in a single volume; with plenty of explanation of some of the more complex issues and examples of current, state-of-the-art practices. Operational Weather Forecasting covers the whole process of forecast production, from understanding the nature of the forecasting problem, gathering the observational data with which to initialise and verify forecasts, designing and building a model (or models) to advance those initial conditions forwards in time and then interpreting the model output and putting it into a form which is relevant to customers of weather forecasts. Included is the generation of forecasts on the monthly-to-seasonal timescales, often excluded in text-books despite this type of forecasting having been undertaken for several years. This is a rapidly developing field, with a lot of variations in practices between different forecasting centres. Thus the authors have tried to be as generic as possible when describing aspects of numerical model design and formulation. Despite the reliance on NWP, the human forecaster still has a big part to play in producing weather forecasts and this is described, along with the issue of forecast verification – how forecast centres measure their own performance and improve upon it. Advanced undergraduates and postgraduate students will use this book to understand how the theory comes together in the day-to-day applications of weather forecast production. In addition, professional weather forecasting practitioners, professional users of weather forecasts and trainers will all find this new member of the RMetS Advancing Weather and Climate series a valuable tool. Provides an end-to-end description of the weather forecasting process Clearly structured and pitched at an accessible level, the book discusses the practical choices that operational forecasting centres have to make in terms of what numerical models they use and when they are run. Takes a very practical approach, using real life case-studies to contextualize information Discusses the latest advances in the area, including ensemble methods, monthly to seasonal range prediction and use of ‘nowcasting’ tools such as radar and satellite imagery Full colour throughout Written by a highly respected team of authors with experience in both academia and practice. Part of the RMetS book series ‘Advancing Weather and Climate’

The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplines involved in the science, modeling, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modeling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions. The book consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field. - Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications - Provides a one-stop shop for graduate students, academic and applied researchers, and practitioners in an emerging and interdisciplinary field - Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making - Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages

Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture. - Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place - Provides real-world examples of methods used to formulate forecasts - Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner

Weather and climate extremes can significantly impact the economics of a region. This book examines how weather and climate forecasts can be used to mitigate the impact of the weather on the economy. Interdisciplinary in scope, it explores the meteorological, economic, psychological, and statistical aspects to weather prediction. The contributors encompass forecasts over a wide range of temporal scales, from weather over the next few hours to the climate months or seasons ahead, and address the impact of these forecasts on human behaviour. Economic Value of Weather and Climate Forecasts seeks to determine the economic benefits of existing weather forecasting systems and the incremental benefits of improving these systems, and will be an interesting and essential reference for economists, statisticians, and meteorologists.