Factor Separation in the Atmosphere Applications and Future Prospects
Modeling atmospheric processes in order to forecast the weather or future climate change is an extremely complex and computationally intensive undertaking. One of the main difficulties is that there are a huge number of factors that need to be taken into account, some of which are still poorly under...
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2011
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| 245 | 0 | 0 | |a Factor Separation in the Atmosphere |b Applications and Future Prospects |c edited by Pinhas Alpert and Tatiana Sholokhman, Tel Aviv University, Israel |
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| 520 | |a Modeling atmospheric processes in order to forecast the weather or future climate change is an extremely complex and computationally intensive undertaking. One of the main difficulties is that there are a huge number of factors that need to be taken into account, some of which are still poorly understood. The Factor Separation (FS) method is a computational procedure that helps deal with these nonlinear factors. In recent years many scientists have applied FS methodology to a range of modeling problems, including paleoclimatology, limnology, regional climate change, rainfall analysis, cloud modeling, pollution, crop growth, and other forecasting applications. This book is the first to describe the fundamentals of the method, and to bring together its many applications in the atmospheric sciences. The main audience is researchers and graduate students using the FS method, but it is also of interest to advanced students, researchers, and professionals across the atmospheric sciences. | ||
| 700 | 1 | |a Alpert, Pinhas | |
| 700 | 1 | |a Sholokhman, Tatiana | |
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| spelling | Factor Separation in the Atmosphere Applications and Future Prospects edited by Pinhas Alpert and Tatiana Sholokhman, Tel Aviv University, Israel Cambridge Cambridge University Press 2011 1 Online-Ressource (xviii, 274 Seiten) txt c cr Modeling atmospheric processes in order to forecast the weather or future climate change is an extremely complex and computationally intensive undertaking. One of the main difficulties is that there are a huge number of factors that need to be taken into account, some of which are still poorly understood. The Factor Separation (FS) method is a computational procedure that helps deal with these nonlinear factors. In recent years many scientists have applied FS methodology to a range of modeling problems, including paleoclimatology, limnology, regional climate change, rainfall analysis, cloud modeling, pollution, crop growth, and other forecasting applications. This book is the first to describe the fundamentals of the method, and to bring together its many applications in the atmospheric sciences. The main audience is researchers and graduate students using the FS method, but it is also of interest to advanced students, researchers, and professionals across the atmospheric sciences. Alpert, Pinhas Sholokhman, Tatiana Erscheint auch als Druck-Ausgabe 9780521191739 TUM01 ZDB-20-CTM TUM_PDA_CTM https://doi.org/10.1017/CBO9780511921414 Volltext |
| spellingShingle | Factor Separation in the Atmosphere Applications and Future Prospects |
| title | Factor Separation in the Atmosphere Applications and Future Prospects |
| title_auth | Factor Separation in the Atmosphere Applications and Future Prospects |
| title_exact_search | Factor Separation in the Atmosphere Applications and Future Prospects |
| title_full | Factor Separation in the Atmosphere Applications and Future Prospects edited by Pinhas Alpert and Tatiana Sholokhman, Tel Aviv University, Israel |
| title_fullStr | Factor Separation in the Atmosphere Applications and Future Prospects edited by Pinhas Alpert and Tatiana Sholokhman, Tel Aviv University, Israel |
| title_full_unstemmed | Factor Separation in the Atmosphere Applications and Future Prospects edited by Pinhas Alpert and Tatiana Sholokhman, Tel Aviv University, Israel |
| title_short | Factor Separation in the Atmosphere |
| title_sort | factor separation in the atmosphere applications and future prospects |
| title_sub | Applications and Future Prospects |
| url | https://doi.org/10.1017/CBO9780511921414 |
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