Articles liés à Atmospheric Modeling, Data Assimilation and Predictability
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Revue de presse :
'... a frisson of excitement accompanied the rumour that Eugenia Kalnay was writing a new book. Expectations were high, since she is a renowned expert in the field. She has not disappointed us.' Science and Technology
'... quite wonderful, achieving a tremendous balance between comprehensiveness and readability. I am especially pleased with the numerical analysis part, which is crystal clear and shows the benefits of classroom testing. I also like the tiny little touches, like the stepped-on butterfly story and the mention that Poincaré knew about chaos in celestial mechanics. Your book fills an enormous hole in the literature of NWP [numerical weather prediction].' Richard C. J. Somerville, Scripps Institution of Oceanography, San Diego
'Fantastic ... in content, format and practicability.' Kelvin K. Droegemeier, Regents' Professor of Meteorology, and Director, Center for Analysis and Prediction of Storms, University of Oklahoma
'[I] admire the clarity and pedagogic superiority of [this] presentation.' Anders Persson, Swedish Meteorological and Hydrological Institute (SMHI)
'... much better for learning about data assimilation than anything else currently available.' Richard Swinbank, United Kingdom Meteorological Office
'... [the] presentation is impeccable and is very accessible to non-meteorologists like me.' Eric Kostelich, University of Arizona
'... what a great wealth of historical information.' Lawrence Takacs, NASA, Data Assimilation Office
'... a delight to read ... It will be of great assistance to our community and should greatly encourage young scientists who may be thinking of entering the field ... the book will be of considerable value to people who are unable or unwilling to cope with mathematical technicalities. They can gain much by studying the expository sections of the text.' Peter Lynch, Assistant Director, Irish Weather Service
'... [the] method in the [data] assimilation section of starting with 'baby' examples, and then working up through the full analysis, is great for understanding. On the predictability part, the history, and the explanations of how the unstable perturbations grow is the best I've seen.' Alexander E. MacDonald, Director, NOAA Forecast Systems Lab
'... this book ... is extremely useful, informative, and well-written ... there are many instances where items that were only marginally familiar beforehand have now become very clear.' Brian O. Blanton, Senior Scientist/Oceanographer, University of North Carolina, Chapel Hill
Biographie de l'auteur :
'... quite wonderful, achieving a tremendous balance between comprehensiveness and readability. I am especially pleased with the numerical analysis part, which is crystal clear and shows the benefits of classroom testing. I also like the tiny little touches, like the stepped-on butterfly story and the mention that Poincaré knew about chaos in celestial mechanics. Your book fills an enormous hole in the literature of NWP [numerical weather prediction].' Richard C. J. Somerville, Scripps Institution of Oceanography, San Diego
'Fantastic ... in content, format and practicability.' Kelvin K. Droegemeier, Regents' Professor of Meteorology, and Director, Center for Analysis and Prediction of Storms, University of Oklahoma
'[I] admire the clarity and pedagogic superiority of [this] presentation.' Anders Persson, Swedish Meteorological and Hydrological Institute (SMHI)
'... much better for learning about data assimilation than anything else currently available.' Richard Swinbank, United Kingdom Meteorological Office
'... [the] presentation is impeccable and is very accessible to non-meteorologists like me.' Eric Kostelich, University of Arizona
'... what a great wealth of historical information.' Lawrence Takacs, NASA, Data Assimilation Office
'... a delight to read ... It will be of great assistance to our community and should greatly encourage young scientists who may be thinking of entering the field ... the book will be of considerable value to people who are unable or unwilling to cope with mathematical technicalities. They can gain much by studying the expository sections of the text.' Peter Lynch, Assistant Director, Irish Weather Service
'... [the] method in the [data] assimilation section of starting with 'baby' examples, and then working up through the full analysis, is great for understanding. On the predictability part, the history, and the explanations of how the unstable perturbations grow is the best I've seen.' Alexander E. MacDonald, Director, NOAA Forecast Systems Lab
'... this book ... is extremely useful, informative, and well-written ... there are many instances where items that were only marginally familiar beforehand have now become very clear.' Brian O. Blanton, Senior Scientist/Oceanographer, University of North Carolina, Chapel Hill
Eugenia Kalnay was awarded a Ph.D in Meteorology from the Massachusetts Institute of Technology in 1971. Following a position as Associate Professor in the same department, she became Chief of the Global Modeling and Simulation Branch at the NASA Goddard Space Flight Center (1983-1987). From 1987 to 1997 she was Director of the Environmental Modeling Center (US National Weather Service) and in 1998 was awarded the Robert E. Lowry endowed chair at the University of Oklahoma. In 1999 she became the Chair of the Department of Meteorology at the University of Maryland. Professor Kalnay is a member of the US National Academy of Engineering, is the recipient of two gold medals from the US Department of Commerce and the NASA Medal for Exceptional Scientific Achievement, and has received the Jule Charney Award from the American Meteorological Society. The author of more than 100 peer reviewed papers on numerical weather prediction, data assimilation and predictability, Professor Kalnay is a key figure in this field and has pioneered many of the essential techniques.
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- ÉditeurCambridge University Press
- Date d'édition2002
- ISBN 10 0521791790
- ISBN 13 9780521791793
- ReliureRelié
- Nombre de pages364
- Evaluation vendeur
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