Instability indices for the Cyprus area

Summary In this paper, forecasts of thunderstorms for the Cyprus area, are examined, by using various instability indices. In addition, some combinations of the indices are proposed since they proved more successful in thunderstorms forecasting. A statistical method pointed out that the Pickup index (PI) and the suggested combination of the humidity index (HI) with cyclonic curved flow at 500 hPa are more successful than the other ones examined in this study.With 1 Figure     

Matched-field processing for broad-band source localization

In the Hudson Canyon experiment, a sound source moved at a constant depth in 73 m of water while transmitting four tonals. The signal was received on a vertical array of hydrophones that spanned the water column. The data set from this experiment has become a standard test case for studying source tracking using matched field processing. As part of that process it was important to first determine a suitable environment model and demonstrate the feasibility of matched-field processing. In this paper, we provide the background on the original data processing that was done to accomplish this. Several interesting results emerged from that study. Frequency averaging was demonstrated to be extremely beneficial when used with the Bartlett processor. However, the popular Minimum Variance processor performed poorly. Finally we discuss a very simple approach to combining the energy coherently that provided significantly improved results.     

Application of neural and statistical classifiers to the problem ofseafloor characterization

In this paper neural and statistical classifiers are applied to the problem of seafloor classification. The feature vectors used consist of acoustic backscatter as a function of angle of incidence. Simulated seafloor backscatter is obtained by employing the Helmholtz-Kirchhoff approximation and the statistical properties of bottom reverberation. These synthetic data are used initially to train multilayer perceptrons and then to test them for their ability to discriminate among signal returns produced by seafloors with different roughness parameters. The same data are also processed with optimum Bayesian classifiers. A comparison of the results indicates a suboptimum performance for the perceptrons. The same procedures are applied to real data collected by the Sea Beam bathymetric system over two Central North Pacific seamounts. In this case, the perceptron performance is similar to that of the statistical classifier, which is no longer optimum, since no prior knowledge of the probability distribution parameters is available. In addition, Self Organizing Maps are applied to both synthetic and real data and are shown to result in a successful separation of the output space into distinct regions corresponding to different seafloor classes     

Evaporation over the Aegean sea using large-scale parameters

Summary The accuracy of evaporation estimates based on meteorological observations from selected coastal stations and various methods are tested in the area of the Aegean sea. The higher values of evaporation are predicted through Smith's approach and bulk aerodynamic formula withC _E=1.85×10³. Priestley-Taylor parameter and annual variation of evaporation in the are are presented analytically.With 5 Figures