Operational prediction of acoustic properties in the ocean using multi-model statistics

Super-ensemble (SE) multi-model forecasts optimize local combination of individual models which is superior to individual models because they allow for local correction and bias removal. Multi-model statistics are applied to optimize the forecast skills from ocean models with different resolution or configuration, run operationally during the MREA04 field experiment off the West coast of Portugal. The method, based on a training/forecast cycle uses linear regression optimization. The performance and the limitations of the different super-ensemble combinations and the individual models are discussed. The SE method is shown to reduce errors in sound velocity significantly for 24 h forecasts.     

印度洋偶极子预报技巧在多模式中的对比研究

本文采用北美多模式集合产品数据,分析了印度洋偶极子指数在不同模式中实际预报技巧和潜在可预报性的差异,并进一步探究其可能的原因。结果表明,印度洋偶极子的有效预报时效在不同模式中差别较大,从2个月到4个月不等。其中东极子海温异常在不同模式中预报技巧的差别较西极子海表面温度异常更明显,表明模式误差和初始误差对东极子海表面温度异常演变的影响更为显著。另外,印度洋偶极子的实际预报技巧和潜在预报技巧存在明显的线性关系,潜在预报技巧高的模式,其实际预报技巧也高。最后,本文诊断、分析了厄尔尼诺对印度洋偶极子预报技巧的影响,发现在厄尔尼诺和印度洋偶极子相关性较高的气候模式中,印度洋偶极子实际预报技巧也较高。     

A climate shift in seasonal values of meteorological and hydrological parameters for Northeastern Asia

The well-known climate shift that occurred around 1976/1977 in the marine ecosystem of North Pacific Ocean was preceded by changes in the early 1970s over Northeastern Asia. In this paper long-term variability of Siberian High and Aleutian Low parameters, seasonal discharge of Siberian rivers and air temperature and precipitation regime in their watersheds are examined in data sets covering 1945–1995. It was found that the change in seasonal values of Siberian river discharges is a consequence of an atmospheric climatic shift that occurred in the early 1970s over North Asia. This shift was induced by a change in atmospheric circulation pattern in the Eurasian sector and Pacific sector of the Northern Hemisphere after 1970. It resulted in changes in position and intensity of the Siberian High and Aleutian Low before and after the 1970s, which induced a different pattern of precipitation in West and East Siberia. There was an increase in winter precipitation over West Siberia but a decrease over East Siberia. The period after 1970s is characterized by higher amplitude of all parameters and increases in the year-to-year variability.     

A hybrid simplex genetic algorithm for estimating geoacousticparameters using matched-field inversion

Matched-fieId inversion (MFI) undertakes to estimate the geometric and geoacoustic parameters in an ocean acoustic scenario by matching acoustic field data recorded at hydrophone array with numerical calculations of the field. The model which provides the best fit to the data is the estimate of the actual experimental scenario. MFI provides a comparatively inexpensive method for estimating ocean bottom parameters over an extensive area. The basic components of the inversion process are a sound propagation model and matching (minimization) algorithm. Since a typical MFI problem requires a large number of computationally intensive sound propagation calculations, both of these components have to be efficient. In this study, a hybrid inversion algorithm which uses a parabolic equation propagation model and combines the downhill simplex algorithm with genetic algorithms is introduced. The algorithm is demonstrated on synthetic range-dependent shallow-water data generated using the parabolic equation propagation model. The performance for estimating the model parameters is compared for realistic signal-to-noise ratios in the synthetic data     

A reliable simulation for hydrodynamic performance prediction of surface-piercing propellers using URANS method

Surface Piercing Propellers (SPPs) are a particular kind of propellers which are partially submerged operating at the interface of air and water. They are more efficient than submerged propellers for the propulsion system of high-speed crafts because of larger propeller diameter, replacing cavitation with ventilation, decreasing the torque and higher efficiency. This study presents a reliable numerical simulation to predict SPP performance using Unsteady Reynolds-Averaged Navier–Stokes (URANS) method. A numerical study on 841-B SPP is performed in open water condition. The free surface is modeled by Volume of Fluid (VOF) approach and the sliding mesh technique is implemented to model the propeller rotational motion. The sliding mesh allows capturing the process of water entry and water exit of blades. The propeller hydrodynamic characteristics, the ventilation pattern and the time history of blade loads are validated through the comparison with available experimental data. For the studied case, it was found that the common grid independence study approach is not sufficient. The grid should be elaborately generated fine enough based on the flow pattern and turbulence modeling parameters in regions near the blade's tip, trailing and leading edges and over the suction side. Details of URANS simulations including optimal time-step size based on propeller revolution rate and the required number of propeller revolutions for periodical results are presented and discussed.     

A model for numerical simulation of nonstationary sonar reverberation using linear spectral prediction

An innovative approach to the numerical generation of nonstationery reverberation time series is presented and demonstrated. The computer simulated reverberation time series are of high quality, in that they are accurate representations of those which would result from an actual sonar system (transmit/receive and horizontal/ vertical beampatterns; pulse type, shape, length, and power; frequency and sampling rate), platform (speed and depth), and environment (wind speed and direction, backscattering strengths, and propagation loss). Volume, surface, and/or bottom reverberation as seen by a multiple beam sonar on a moving platform is generated. The approach utilizes recent developments in linear spectral prediction research in which the spectra of stochastic processes are modeled as rational functions and algorithms are used to efficiently compute optimal estimates of coefficients which specify the spectra. A two-fold sequence is formulated; first, the expected reverberation spectra for all beams are predicted and, second, the stochastic time series are generated from the expected spectra. The expected spectra are predicted using a numerical implementation, referred to as the REVSPEC (reverberation spectrum) model, of a general formulation of Faure, Ol'shevskii, and Middleton. Given the spectra, the Levinson-Durbin method is used to solve the Yule-Walker equations of the autoregressive formulation of linear spectral prediction. The numerical implementation of the approach, referred to as the REVSIM (reverberation simulation) model, produces nonstationary coherent multiple-beam reverberation time series. The formulation of the REVSIM model is presented and typical results given. A comparison is made between the simulation outputs of the REVSIM model and those of the REVGEN (reverberation generator) model, a standard well-accepted time series simulation model, to demonstrate the validity of the new approach.