Influence of the Load Wavelength on the Permeability of a Viscosity Interface in the Mantle

Assuming a radially stratified Newtonian mantle in a steady-state approximation, we demonstrate that the permeability of a viscosity interface at 660-km depth strongly depends on the wavelength of buoyancy forces driving the flow. The flow induced by long-wavelength loads penetrates through the boundary freely even if the viscosity increases by two orders. In contrast, the boundary is practically impermeable for short-wavelength loads located in the upper mantle. Thus, a stepwise increase of viscosity is a significant obstacle for small descending features in the upper mantle, but huge upper mantle downwellings, or upwellings formed in the-lower mantle can overcome it easily. This indicates that certain care is necessary in interpreting the seismic structure of the mantle by means of flow models. The global tomographic image includes only the first few degrees of the harmonic series and, consequently, its interpretation in terms of a present-day flow field results in a predominantly whole-mantle circulation even for extreme viscosity contrasts.     

Remote sensing detection of atmospheric pollutants by differential absorption LIDAR 510M/SODAR PA2 mobile system

Summary Air pollution problem in the Czech Republic is very complex due to large number of factors as turbulent dispersion and chemical reactions concurring in the status of the PBL. For this 3D distribution of pollutants is a key information that cannot be given by conventional monitoring stations. Combined use of DIAL lidar and sodar can give access to such information. Case studies of air pollutants transport are presented using 3D concentration fields of NO₂ and ozone measured by lidar and meteorological conditions monitored by Doppler Sodar.     

Mesozooplankton spatial distribution and community structure in the South Adriatic Sea during two winters (2015, 2016)

Whereas the data on mesozooplankton in the epipelagic offshore Mediterranean Sea are extensive, less information is available about plankton in the deeper layers. The present study aims to describe the vertical and horizontal structure and distribution of mesozooplankton species and their associations down to 1,200 m in the water of the Southern Adriatic Sea. Zooplankton were sampled using a Nansen net of 200‐μm mesh size during two cruises in the winters of 2015 and 2016, extending from the coast to the open sea. In total, 203 zooplankton taxa were identified. The community was dominated by copepods, representing between 67% and 91% of the total abundance. The highest total densities were recorded in the upper layers where a high proportion (up to 36%) of appendicularians was also observed in the first sampled year. Five groups of samples were determined based on their community structure. In 2015 communities were distinct between the 0 and 50 m layer and the underlying one (50–100 m), whereas in 2016 epipelagic waters were inhabited by a more uniform mesozooplankton community. The mesopelagic and deep‐water fauna, especially copepods, showed a relatively stable composition in both sampling years Overall, our study confirms the oligotrophic character of the Southern Adriatic, with occasional density outbreaks of appendicularians under favourable conditions.     

Salinity Distribution at Canal Istanbul and Its Possible Impacts on the Northern Marmara Sea

China Ocean Engineering - Turkey has announced its plan to construct a new waterway, Canal Istanbul, parallel to the Bosphorus. In this study, the influence of Canal Istanbul on salinity...     

The Late Cretaceous Klepa basalts in Macedonia (FYROM)—Constraints on the final stage of Tethys closure in the Balkans

The waning stage(s) of the Tethyan ocean(s) in the Balkans are not well understood. Controversy centres on the origin and life‐span of the Cretaceous Sava Zone, which is allegedly a remnant of the last oceanic domain in the Balkan Peninsula, defining the youngest suture between Eurasia‐ and Adria‐derived plates. In order to investigate to what extent Late‐Cretaceous volcanism within the Sava Zone is consistent with this model we present new age data together with trace‐element and Sr–Nd–Pb isotope data for the Klepa basaltic lavas from the central Balkan Peninsula. Our new geochemical data show marked differences between the Cretaceous Klepa basalts (Sava Zone) and the rocks of other volcanic sequences from the Jurassic ophiolites of the Balkans. The Klepa basalts mostly have Sr–Nd–Pb isotopic and trace‐element signatures that resemble enriched within‐plate basalts substantially different from Jurassic ophiolite basalts with MORB, BAB and IAV affinities. Trace‐element modelling of the Klepa rocks indicates 2%–20% polybaric melting of a relatively homogeneously metasomatised mantle source that ranges in composition from garnet lherzolite to ilmenite+apatite bearing spinel–amphibole lherzolite. Thus, the residual mineralogy is characteristic of a continental rather than oceanic lithospheric mantle source, suggesting an intracontinental within‐plate origin for the Klepa basalts. Two alternative geodynamic models are internally consistent with our new findings: (1) if the Sava Zone represents remnants of the youngest Neotethyan Ocean, magmatism along this zone would be situated within the forearc region and triggered by ridge subduction; (2) if the Sava Zone delimits a diffuse tectonic boundary between Adria and Europe which had already collided in the Late Jurassic, the Klepa basalts together with a number of other magmatic centres represent volcanism related to transtensional tectonics.     

Modeling Urban Land Use Changes Using Support Vector Machines

Support Vector Machines (SVM) is a machine learning (ML) algorithm commonly applied to the classification of remotely sensing data and more recently for modeling land use changes. However, in most geospatial applications the current literature does not elaborate on specifications of the SVM method with respect to data sampling, attribute selection and optimal parameters choices. Therefore the main objective of this study is to present and investigate the SVM technique for modeling urban land use change. The SVM model building procedure is presented together with the detailed evaluation of the output results with respect to the choice of datasets, attributes and the change of SVM parameters. Geospatial datasets containing nine land use classes and spatial attributes for the Municipality of Zemun, Republic of Serbia were used for years 2001, 2003, 2007 and 2011. The Correlation‐based Feature Subset method, kappa coefficient, Area Under Receiver Operating Characteristic Curve (AUC) and kappa simulation were used to perform the model evaluation and compare the model outputs with the real land use datasets. The obtained results indicate that the SVM‐based models perform better when implementing balanced data sampling, reduced data sets to informative subsets of attributes and properly identify the optimal learning parameters.