Seasonal and Geographic Constraints for Acoustic Surface Scatter
Abstract
The long-term goal of this research is to develop an improved prediction capability for acoustic surface scatter in open ocean and littoral regions. Special emphasis is given to the identification of easily observable environmental factors that are intrinsically related to surface wave and bubble cloud scattering, which can be used as inputs to next-generation scattering models. Although significant advancements have been made in understanding the physical mechanisms of low frequency (<1000 Hz) surface scatter, a lingering mystery is the explanation for large scattering-level differences (approx. 15 dB) between observation sets obtained under apparently similar wind forcing conditions (Nicholas et al., 1998, McDaniel, 1993). It is hypothesized here that site-to-site differences in surface scattering strength (SSS) are dependent upon the environmental forcing conditions that influence surface wave and bubble cloud evolution at each site. Hence, the primary objective is to demonstrate that significant SSS prediction improvements can be made when site-specific environmental forcing conditions, in addition to local winds, are used in a predictive model. Surface scattering strengths were consistently measured in six contrasting open-ocean environments during the multi-year Critical Sea Test (CST) program (Ogden and Erskine, 1994A and 1994B). The observations at each site cover a wide variety of atmospheric forcing conditions, and a detailed suite of environmental measurements accompanied each acoustic observation. The CST data were used by Nicholas et al. (1998) to construct a best-fit multiparameter empirical model for SSS. The resulting Nicholas-Ogden-Erskine (ONE SSS) algorithm employs wind speed measured at 10-m height (U10) as the sole environmental input to predict SSS over a range of acoustic frequencies and grazing angles. In this study, ONE-model prediction errors were calculated.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1998
- Accession Number
- ADA552548
Entities
People
- Jeffrey L. Hanson
Organizations
- Johns Hopkins University