An Introduction to Global Spectral Modeling: 35 (Atmospheric and Oceanographic Sciences Library) - Hardcover

Über die Autorin bzw. den Autor

T.N. Krishnamurti is professor of meteorology at Florida State University. He obtained his PhD in 1959 at the University of Chicago. His research interests are in the following areas: high resolution hurricane forecast (tracks, landfall, and intensity), monsoon forecasts on short, medium range, and monthly time scale and studies of interseasonal and interannual variability of the tropical atmosphere. As a participant in the meteorology team in tropical field projects, he has been responsible for the acquisition and analysis of meteorological data, which extends over most of the tropical atmosphere over several years and is now being assembled and analyzed. These data are unique; it is unlikely that a meteorological data record will be available for decades. Phenomenological interests include hurricanes, monsoons, jet streams, and the meteorology of arid zones.

H.S. Bedi is affiliated with Florida State University.

V.M. Hardiker is a research associate at Florida State University.

L. Ramaswamy is a graduate research assistant in the Department of Meteorology at Florida State University.

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Numerical weather prediction is receiving increased attention as weather forecasters aim to improve the numerical models used to forecast the weather. This is a textbook on global spectral modeling, which is an important component for global weather forecasts at numerous operational centers. This book covers all areas of model development including numerical analysis, treatment of clouds, mountains, radiation, precipitation processes, and the surface layers over land and the ocean. The objectives of this book are to provide a systematic and sequential background for students, researchers, and operational weather forecasters in order to develop comprehensive weather forecast models. This is designed for a one semester introductory graduate level course on weather prediction methodologies. As a prerequisite it requires a basic background in meteorology, applied mathematics, and numerical analysis.