Modifying the sound‐speed profile to improve the accuracy of the parabolic‐equation technique

1977 ◽  
Vol 62 (3) ◽  
pp. 543-552 ◽  
Author(s):  
H. K. Brock ◽  
R. N. Buchal ◽  
C. W. Spofford
Keyword(s):  
Parabolic Equation ◽  
Sound Speed ◽  
Speed Profile ◽  
Sound Speed Profile

Compensation of INS Errors based on LBL References in a Quadratic Sound-Speed-Profile

2020 ◽  
Author(s):  
Yohannes S.M. Simamora ◽  
Harijono A. Tjokronegoro ◽  
Edi Leksono ◽  
Irsan S. Brodjonegoro
Keyword(s):  
Sound Speed ◽  
Speed Profile ◽  
Sound Speed Profile

Sound speed profile inversion using a horizontal line array in shallow water

2014 ◽  
Vol 58 (1) ◽  
pp. 1-7 ◽  
Author(s):  
ZhengLin Li ◽  
Li He ◽  
RenHe Zhang ◽  
FengHua Li ◽  
YanXin Yu ◽  
...  
Keyword(s):  
Shallow Water ◽  
Sound Speed ◽  
Horizontal Line ◽  
Speed Profile ◽  
Sound Speed Profile ◽  
Line Array ◽  
Profile Inversion

A Computationally Efficient Rayleigh–Ritz Model for Heterogeneous Oceanic Waveguides Using Fourier Series of Sound Speed Profile

2021 ◽  
pp. 2150015
Author(s):  
A. D. Chowdhury ◽  
S. K. Bhattacharyya ◽  
C. P. Vendhan
Keyword(s):  
Fourier Series ◽  
Sound Speed ◽  
Transmission Loss ◽  
Ritz Method ◽  
Computational Cost ◽  
Least Square ◽  
Speed Profile ◽  
Matrix Elements ◽  
Sound Speed Profile ◽  
The Matrix

The normal mode method is widely used in ocean acoustic propagation. Usually, finite difference and finite element methods are used in its solution. Recently, a method has been proposed for heterogeneous layered waveguides where the depth eigenproblem is solved using the classical Rayleigh–Ritz approximation. The method has high accuracy for low to high frequency problems. However, the matrices that appear in the eigenvalue problem for radial wavenumbers require numerical integration of the matrix elements since the sound speed and density profiles are numerically defined. In this paper, a technique is proposed to reduce the computational cost of the Rayleigh–Ritz method by expanding the sound speed profile in a Fourier series using nonlinear least square fit so that the integrals of the matrix elements can be computed in closed form. This technique is tested in a variety of problems and found to be sufficiently accurate in obtaining the radial wavenumbers as well as the transmission loss in a waveguide. The computational savings obtained by this approach is remarkable, the improvements being one or two orders of magnitude.

Improving the Estimation of Temperature and Salinity by Assimilation of Observed Sound Speed Profiles

2021 ◽  
Author(s):  
Jiali Zhang ◽  
Liang Zhang ◽  
Anmin Zhang ◽  
Lianxin Zhang ◽  
Dong Li ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sound Speed ◽  
Field Experiments ◽  
Underwater Acoustics ◽  
Ocean Model ◽  
Speed Profile ◽  
Sound Speed Profile ◽  
Coastal Sea ◽  
Short Time ◽  
Assimilation Scheme

AbstractSound Speed Profile (SSP) affecting underwater acoustics is closely related to the temperature and the salinity fields. It is of great value to obtain the temperature and the salinity information through the high-precision sound speed profiles. In this paper, a data assimilation scheme by introducing sound speed profiles as a new constraint is proposed within the framework of 3DVAR data assimilation (referenced as SSP-constraint 3DVAR (SSPC-3DVAR) ), which aims at improving the analysis accuracy of initial fields of the temperature and salinity in coastal sea areas. In order to validate the performance of the new assimilation scheme, ideal experiments are firstly carried out to show the advantages of the new proposed SSPC-3DVAR. Then the temperature, the salinity, and the SSP observations from field experiments in a coastal area are assimilated into the Princeton Ocean Model to validate the performance of short-time forecasts, adopting the SSPC-3DVAR scheme. Results show that it is efficient to improve the estimate accuracy by as much as 14.6% (11.1%) for the temperature (salinity), compared with the standard 3DVAR. It demonstrates that the proposed SSPC-3DVAR approach works better in practice than the standard 3DVAR and will primarily benefit from variously and widely distributed observations in the future.

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