Statistical postprocessing of ensemble forecasts
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 applicatio...
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| Sprache: | English |
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Amsterdam, Netherlands
Elsevier
[2018]
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| 245 | 1 | 0 | |a Statistical postprocessing of ensemble forecasts |c edited by Stéphane Vannitsem, Daniel S. Wilks, Jakob W. Messner |
| 264 | 1 | |a Amsterdam, Netherlands |b Elsevier |c [2018] | |
| 264 | 4 | |c © 2018 | |
| 300 | |a 1 online resource |b illustrations | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
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| 500 | |a Includes bibliographical references and index | ||
| 520 | |a 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 MïÅưller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). | ||
| 520 | |a 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. | ||
| 520 | |a 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 | ||
| 650 | 7 | |a SCIENCE / Earth Sciences / Geography |2 bisacsh | |
| 650 | 7 | |a SCIENCE / Earth Sciences / Geology |2 bisacsh | |
| 650 | 7 | |a Weather forecasting |2 fast | |
| 650 | 4 | |a Weather forecasting | |
| 700 | 1 | |a Vannitsem, Stéphane |4 edt | |
| 700 | 1 | |a Wilks, Daniel S. |4 edt | |
| 700 | 1 | |a Messner, Jakob |4 edt | |
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| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 0128123729 |
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Datensatz im Suchindex
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|---|---|
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| author2 | Vannitsem, Stéphane Wilks, Daniel S. Messner, Jakob |
| author2_role | edt edt edt |
| author2_variant | s v sv d s w ds dsw j m jm |
| author_facet | Vannitsem, Stéphane Wilks, Daniel S. Messner, Jakob |
| building | Verbundindex |
| bvnumber | BV045383119 |
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| ctrlnum | (ZDB-33-ESD)on1036985964 (ZDB-33-EBS)on1036985964 (OCoLC)1036985964 (DE-599)BVBBV045383119 |
| dewey-full | 551.63 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 551 - Geology, hydrology, meteorology |
| dewey-raw | 551.63 |
| dewey-search | 551.63 |
| dewey-sort | 3551.63 |
| dewey-tens | 550 - Earth sciences |
| discipline | Geologie / Paläontologie |
| format | Electronic eBook |
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| id | DE-604.BV045383119 |
| illustrated | Illustrated |
| indexdate | 2024-12-24T06:59:54Z |
| institution | BVB |
| isbn | 9780128122488 012812248X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030769452 |
| oclc_num | 1036985964 |
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| owner_facet | DE-1046 |
| physical | 1 online resource illustrations |
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| publishDate | 2018 |
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| publisher | Elsevier |
| record_format | marc |
| spelling | Statistical postprocessing of ensemble forecasts edited by Stéphane Vannitsem, Daniel S. Wilks, Jakob W. Messner Amsterdam, Netherlands Elsevier [2018] © 2018 1 online resource illustrations txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index 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 MïÅưller (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 SCIENCE / Earth Sciences / Geography bisacsh SCIENCE / Earth Sciences / Geology bisacsh Weather forecasting fast Weather forecasting Vannitsem, Stéphane edt Wilks, Daniel S. edt Messner, Jakob edt Erscheint auch als Druck-Ausgabe 9780128123720 Erscheint auch als Druck-Ausgabe 0128123729 https://www.sciencedirect.com/science/book/9780128123720 Verlag URL des Erstveröffentlichers Volltext http://library.smu.ca:2048/login?url=https://www.sciencedirect.com/science/book/9780128123720 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Statistical postprocessing of ensemble forecasts SCIENCE / Earth Sciences / Geography bisacsh SCIENCE / Earth Sciences / Geology bisacsh Weather forecasting fast Weather forecasting |
| title | Statistical postprocessing of ensemble forecasts |
| title_auth | Statistical postprocessing of ensemble forecasts |
| title_exact_search | Statistical postprocessing of ensemble forecasts |
| title_full | Statistical postprocessing of ensemble forecasts edited by Stéphane Vannitsem, Daniel S. Wilks, Jakob W. Messner |
| title_fullStr | Statistical postprocessing of ensemble forecasts edited by Stéphane Vannitsem, Daniel S. Wilks, Jakob W. Messner |
| title_full_unstemmed | Statistical postprocessing of ensemble forecasts edited by Stéphane Vannitsem, Daniel S. Wilks, Jakob W. Messner |
| title_short | Statistical postprocessing of ensemble forecasts |
| title_sort | statistical postprocessing of ensemble forecasts |
| topic | SCIENCE / Earth Sciences / Geography bisacsh SCIENCE / Earth Sciences / Geology bisacsh Weather forecasting fast Weather forecasting |
| topic_facet | SCIENCE / Earth Sciences / Geography SCIENCE / Earth Sciences / Geology Weather forecasting |
| url | https://www.sciencedirect.com/science/book/9780128123720 http://library.smu.ca:2048/login?url=https://www.sciencedirect.com/science/book/9780128123720 |
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