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Empirical Methods in Short-Term Climate Prediction

Autor Huug van den Dool
en Limba Engleză Hardback – 7 dec 2006
This clear and accessible text describes the methods underlying short-term climate prediction at time scales of 2 weeks to a year. Although a difficult range to forecast accurately, there have been several important advances in the last ten years, most notably in understanding ocean-atmosphere interaction (El Nino for example), the release of global coverage data sets, and in prediction methods themselves. With an emphasis on the empirical approach, the text covers in detail empirical wave propagation, teleconnections, empirical orthogonal functions, and constructed analogue. It also provides a detailed description of nearly all methods used operationally in long-lead seasonal forecasts, with new examples and illustrations. The challenges of making a real time forecast are discussed, including protocol, format, and perceptions about users. Based where possible on global data sets, illustrations are not limited to the Northern Hemisphere, but include several examples from the Southern Hemisphere. Includes foreword by Professor Edward Lorenz (Massachusetts Institute of Technology).
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Specificații

ISBN-13: 9780199202782
ISBN-10: 0199202788
Pagini: 240
Ilustrații: 12 plates, numerous tables and line drawings
Dimensiuni: 160 x 240 x 17 mm
Greutate: 0.52 kg
Editura: OUP OXFORD
Colecția OUP Oxford
Locul publicării:Oxford, United Kingdom

Recenzii

Thoughtful, original, and worthy of serious consideration
This is a great book ... every student and practitioner of climate prediction should have a copy on their desk

Notă biografică

Huug van den Dool gained his PhD in Dynamical Meteorology from the University of Utrecht in 1975. He has since worked as a researcher at KNMI (Royal Netherlands Meteorological Institute), Scripps Institution of Oceanography, the University of Maryland, and as Chief of Prediction at the CPC (Climate Prediction Center). He is currently a principal scientist at CPC and an adjunct professor at the University of Maryland.