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Proceedings Paper

The use of remotely sensed data and innovative modeling to improve hurricane prediction
Author(s): Robert Atlas; O. Reale; B.-W. Shen; S.-J. Lin
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Paper Abstract

The assimilation of remotely sensed data from aircraft and satellites has contributed substantially to the current accuracy of operational hurricane forecasting. In the 1960's, satellite imagery revolutionized hurricane detection and forecasting. Since that time, quantitative remotely sensed data (eg. atmospheric motion winds, passive infrared and microwave radiances or retrievals of temperature, moisture, surface wind and rain rate, active microwave measurements of surface wind and rain rate) and significant advances in modeling and data assimilation have increased the accuracy of hurricane track forecasts very significantly. The development of advanced next-generation models in combination new types of remotely sensed observations (eg. space-based lidar winds) should yield significant further improvements in the timing and location of landfall and in the predicted intensification of hurricanes.

Paper Details

Date Published: 4 May 2006
PDF: 8 pages
Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62330U (4 May 2006); doi: 10.1117/12.673221
Show Author Affiliations
Robert Atlas, NOAA Atlantic Oceanographic and Meteorological Lab. (United States)
O. Reale, Univ. of Maryland, Baltimore (United States)
B.-W. Shen, Science Applications International Corp., NASA GSFC (United States)
S.-J. Lin, NOAA Geophysical Fluid Dynamics Lab. (United States)

Published in SPIE Proceedings Vol. 6233:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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