+44 1803 865913
By: John A Colosi(Author)
424 pages, 26 colour & 98 b/w illustrations, 17 tables
The ocean is opaque to electromagnetic radiation and transparent to low frequency sound, so acoustical methodologies are an important tool for sensing the undersea world. Stochastic sound-speed fluctuations in the ocean, such as those caused by internal waves, result in a progressive randomisation of acoustic signals as they traverse the ocean environment. This signal randomisation imposes a limit to the effectiveness of ocean acoustic remote sensing, navigation and communication. Sound Propagation Through the Stochastic Ocean provides a comprehensive treatment of developments in the field of statistical ocean acoustics over the last 35 years. This will be of fundamental interest to oceanographers, marine biologists, geophysicists, engineers, applied mathematicians, and physicists. Key discoveries in topics such as internal waves, ray chaos, Feynman path integrals, and mode transport theory are addressed with illustrations from ocean observations. The topics are presented at an approachable level for advanced students and seasoned researchers alike.
Part I. Introduction and Prerequisites:
1. Sound propagation through the stochastic ocean
2. Acoustical prerequisites
3. Stochastic ocean internal waves
4. Introduction to acoustic fluctuations
Part II. Wave Propagation Theories:
5. Ray theory
6. Weak fluctuation theory
7. Path integral theory
8. Mode transport theory
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John A. Colosi is a Professor of Oceanography at the Naval Postgraduate School in Monterey, California. He is a Fellow of the Acoustical Society of America (ASA), and was the recipient of the 2011 ASA Medwin Prize in Acoustical Oceanography and the 2001 UK Institute of Acoustics A. B. Wood Medal. He has twice been a Cecil H. and Ida M. Green Scholar at the Scripps Institution of Oceanography, University of California, San Diego.
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I don't know how you got a book printed 26 years ago in the conditions that I received it (like new) but you do it! ABSOLUTELY AWESOME!
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