Characteristics of the internal and external sources of the Mediterranean synoptic cyclones for the period 1956–2013

This paper investigates the main sources and features of the Mediterranean synoptic cyclones affecting the basin, using the cyclone tracks. The cyclones’ tracks are identified using sea level pressure (SLP) from the NCEP/NCAR reanalysis data for the period 1956–2013. The identified cyclones are classified into two categories: basin affected and basin non-affected. Most of the basin-affected (non-affected) cyclones are internal (external), i.e., generated inside (outside) the Mediterranean basin. This study reveals four (five) main sources of internal (external) cyclones. These four (five) main sources generated about 63.76% (57.25%) of the internal (external) cyclones. Seasonal analysis shows that most of the basin-affected internal (external) cyclones were generated in the winter (spring) season. The lowest number of cyclones were found in the summer. Moreover, the synoptic study of the atmospheric systems accompanied the highest- and lowest-generated years demonstrates that the deepening of the north Europe cyclones and the relative positions of Azores- and Siberian-high systems represent the important factors that influence the number of internal cyclones. Essential factors influencing the external cyclones are the strength of the maximum upper wind, Azores high, Siberian high, and orientations of their ridges.     

Examination of multi-perturbation methods for ensemble prediction of the MJO during boreal summer

The impact of initialization and perturbation methods on the ensemble prediction of the boreal summer intraseasonal oscillation was investigated using 20-year hindcast predictions of a coupled general circulation model. The three perturbation methods used in the present study are the lagged-averaged forecast (LAF) method, the breeding method, and the empirical singular vector (ESV) method. Hindcast experiments were performed with a prediction interval of 10 days for extended boreal summer (May–October) seasons over a 20 year period. The empirical orthogonal function (EOF) eigenvectors of the initial perturbations depend on the individual perturbation method used. The leading EOF eigenvectors of the LAF perturbations exhibit large variances in the extratropics. Bred vectors with a breeding interval of 3 days represent the local unstable mode moving northward and eastward over the Indian and western Pacific region, and the leading EOF modes of the ESV perturbations represent planetary-scale eastward moving perturbations over the tropics. By combining the three perturbation methods, a multi-perturbation (MP) ensemble prediction system for the intraseasonal time scale was constructed, and the effectiveness of the MP prediction system for the Madden and Julian oscillation (MJO) prediction was examined in the present study. The MJO prediction skills of the individual perturbation methods are all similar; however, the MP‐based prediction has a higher level of correlation skill for predicting the real-time multivariate MJO indices compared to those of the other individual perturbation methods. The predictability of the intraseasonal oscillation is sensitive to the MJO amplitude and to the location of the dominant convective anomaly in the initial state. The improvement in the skill of the MP prediction system is more effective during periods of weak MJO activity.     

Physico-Chemical and Shrinkage Properties of Highly Organic Soil Treated with Non-traditional Additives

The changes in the shrinkage and physicochemical properties of untreated and treated organic soil using several chemical additives were investigated. In order to evaluate the effect of each chemical solution on the peaty soil environment different experiments namely; shrinkage limit, unconfined compressive strength (UCS), pH test, and water content were undertaken. The results of the laboratory experiments are further proved and interpreted using the X-ray diffraction, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy tests. The result unveils the structure of the treated soil significantly changed depending upon the used additive type and concentrations. The rate of shrinkage largely decreased when sodium silicate additives are used. In addition, it was observed that UCS value increased up to 500% and water content reduced up to 50% in comparison with untreated samples, depend on the amount of used non-traditional additives. The SEM micrographs of the sample before and after treatment validate the results obtained and analyzed from experiments.     

Inversion of magnetic anomalies due to isolated thin dike-like sources using artificial neural networks

A new approach is proposed to interpret magnetic anomalies caused by isolated thin dike-like causative targets. The approach is essentially based on utilizing artificial neural network (ANN) inversion for estimating the problem parameters. Particularly, the modular neural network (MNN) is used for the inversion process in order to quantitatively interpret the magnetic anomalies. The MNN inversion has been first tested on a synthetic data with and without random white Gaussian noise. The effect of random noise has been clearly investigated where it showed that the approach provided satisfactory results. Furthermore, three field examples have been inverted in order to investigate the applicability of the proposed approach. The results showed good agreement with the techniques that have been stated in the literatures.