Publicado por Lightform Publications, 2004
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Añadir al carritoTaschenbuch. Condición: Neu. Predictability of Tropical Cyclones | "Understanding the limits and uncertainties in Hurricane Prediction" | Jason Sippel (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639175844 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por VDM Verlag Dr. Müller e.K., 2010
ISBN 10: 3639175840 ISBN 13: 9783639175844
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Librería: Mispah books, Redhill, SURRE, Reino Unido
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sippel JasonJason Sippel is currently a postdoctoral fellow at NASA. He received his Ph.D. from Texas A&M University. Fuqing Zhang is a professor at Pennsylvania State University. He received the 2009 American Meteorological Socie.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Through methodology unique for tropical cyclones in peer-reviewed literature and through examination of two tropical cyclone events, this study uses ensemble forecasts, sensitivity analysis, and ensemble data assimilation to explore the dynamics and predictability of tropical cyclone formation with state-of-the-art cloud-resolving mesoscale models. In both of these cases, high convective available potential energy and mid-level moisture were found to benefit genesis. The strong sensitivity to initial condition differences in both cases exemplifies the inherent uncertainties in hurricane intensity prediction where moist convection is the key that limits predictability. The success of using an ensemble Kalman filter in assimilating Doppler radar radial velocity observations of a hurricane demonstrates that, even in cases of extreme uncertainty in a tropical cyclone, advanced data assimilation and subsequent event-dependent probabilistic forecasts can offer significant benefits.