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Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 522
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Book Description
Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 522
Get Book Here
Book Description
Author: Royal Meteorological Society (Great Britain)
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 404
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Book Description
Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 526
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Book Description
Author: Anonymous
Publisher: BoD – Books on Demand
ISBN: 3385358426
Category : Fiction
Languages : en
Pages : 298
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Book Description
Reprint of the original, first published in 1883.
Author: Meteorological Society (Great Britain)
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 376
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Book Description
Vols. 1-9 include Meteorology of England by James Glaisher as seperately paged section at end.
Author: Literary and Philosophical Society of Liverpool
Publisher:
ISBN:
Category : Humanities
Languages : en
Pages : 414
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Book Description
Author: Royal Meteorological Society (Great Britain)
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 132
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Book Description
Vols. 10-11 include Meteorology of England by James Glaisher as seperately paged section at end.
Author: Peter Ray
Publisher: Springer
ISBN: 1935704206
Category : Science
Languages : en
Pages : 803
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Book Description
This book is a collection of selected lectures presented at the ‘Intensive Course on Mesoscale Meteorology and Forecasting’ in Boulder, USA, in 1984. It includes mesoscale classifications, observing techniques and systems, internally generated circulations, mesoscale convective systems, externally forced circulations, modeling and short-range forecasting techniques. This is a highly illustrated book and comprehensive work, including extensive bibliographic references. It is aimed at graduates in meteorology and for professionals working in the field.
Author: Stéphane Vannitsem
Publisher: Elsevier
ISBN: 012812248X
Category : Science
Languages : en
Pages : 364
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Book Description
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
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309380979
Category : Science
Languages : en
Pages : 187
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Book Description
As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.
