Seismic activity and deep conductivity structure of the Eastern Carpathians

We present results of a study of the seismicity and the geoelectric structure of the Eastern Carpathians. After the evaluation of the seismicity, new methods of processing and analyzing seismic data are developed, which allow constructing an averaged horizontal-layered velocity model of the crust in the Carpathian region of Ukraine, tracing the seismic active faults and localizing the seismic events both in horizontal and in vertical direction with a better precision. For the study of the conductivity structure beneath the Eastern Carpathians, the collected magnetovariation and magnetotelluric data are used. The depth of electrical conductivity anomalies are estimated and the resulting quasi-3D model of the conductivity structure beneath the Carpathians is compared with the seismicity in the depth range of 10 ± 2.5 km. The comparison suggests possible geological mechanisms: the seismic events occur mainly in resistive solid rock domains which surround aseismic high-conductivity zones, consisting of at least partially melted material. Aqueous fluids, or a joint effect of several mechanisms, may also play an active role in this distribution.     

Fractal variations of the Transcarpathians,West Ukraine,seismicity and their potential relation to changing phases of local seismic cycles

The evolution of spatial arrangement of the Transcarpathian earthquakes is studied by means of fractal analysis. Spatial correlation dimension is evaluated for a subset of fixed number of catalogue events consecutively shifted in time by one event forward. Distinctive patterns that may be related to different phases of local seismic cycle/cycles have been identified, corresponding to extreme values of the dimension. Their potential relation to evolution of the seismogenic stress field is discussed. The time it takes for the capacity dimension to reach the so-called percolation threshold is estimated for a subset consecutively extended by adding next catalogue events. Temporal and spatial frames of percolation analysis are discussed in relation to parameters of the future earthquake.     

Analysis of change in relative uncertainty in GHG emissions from stationary sources for the EU 15

Total uncertainty in greenhouse gas (GHG) emissions changes over time due to “learning” and structural changes in GHG emissions. Understanding the uncertainty in GHG emissions over time is very important to better communicate uncertainty and to improve the setting of emission targets in the future. This is a diagnostic study divided into two parts. The first part analyses the historical change in the total uncertainty of CO₂ emissions from stationary sources that the member states estimate annually in their national inventory reports. The second part presents examples of changes in total uncertainty due to structural changes in GHG emissions considering the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) emissions scenarios that are consistent with the EU’s “20-20-20” targets. The estimates of total uncertainty for the year 2020 are made under assumptions that relative uncertainties of GHG emissions by sector do not change in time, and with possible future uncertainty reductions for non-CO₂ emissions, which are characterized by high relative uncertainty. This diagnostic exercise shows that a driving factor of change in total uncertainty is increased knowledge of inventory processes in the past and prospective future. However, for individual countries and longer periods, structural changes in emissions could significantly influence the total uncertainty in relative terms.     

Dynamic downscaling of global climate projections for Eastern Europe with a horizontal resolution of 7 km

Climate change is one of the key factors influencing the quantity and quality of water resources in hydrologically sensitive regions. In order to downscale global climate simulations from horizontal resolutions of about 125–200 km to about 7 km, a double nesting strategy was chosen. The modelling approach was implemented with the Regional Climate Model CCLM (COSMO-Climate Local Model) with a first nesting covering a central part of Europe and with a second nesting covering parts of Poland, Belarus, and the Ukraine. A control run—driven by global reanalysis data—was evaluated by comparing the model results with corresponding reference data. Long-term yearly and monthly mean differences of temperature and precipitation were statistically assessed. As reference data for the first nesting, the gridded CRU data set with a horizontal resolution of about 55 km was used. Station data of the NOAA and ECA databases were interpolated to provide an appropriate reference data set for the second nesting. Both nestings overestimated long-term yearly precipitation means. Seasonal evaluation of the first nesting showed positive precipitation biases for spring and winter months and negative biases in summer. Furthermore, differences in the spatial precipitation patterns occured, especially in the high mountain area of the Carpathians. The second nesting overestimated precipitation in spring and summer with smaller biases than in the first nesting. Long-term area means of temperature were properly reproduced. The first nesting showed an overestimation for all months with maximal deviations in summer and spring. In contrast, the second nesting was slightly too warm for summer and autumn and too cold for winter and spring.