Abstract:

The results of studies of atmospheric pressure in the Arctic region of Russia in the period from 1948 to 2008 are presented. The analysis of the climatic seasonal variation of the atmospheric pressure fields is carried out. As the main research method, the probabilistic and statistical analysis of the time series of the pressure field 60 years long at fixed points in the region of the Arctic zone of Russia was used. In total, about 90,000 daily (in six-hour increments) pressure values were examined. On the basis of these data, a climatic seasonal variation was constructed as an averaging of the values of a given time series at each point in space and for a fixed date. The characteristics of the seasonal course, its amplitude and phase have been studied. These characteristics were analyzed and their geophysical interpretation was carried out. In particular, the minimum and maximum values ​​of the series were determined for the entire region and the time series of these characteristics were constructed. It is shown that the deviation is asymmetric, this is an unobvious research result. For the maximum and minimum, the best approximations were constructed, and these approximations were tested by known methods of statistical analysis, including maximum likelihood, least squares and goodness of fit methods (tests), in particular, the χ²-criterion. The conducted research has applications both purely physical (allows to explain the nature, genesis and distribution of large-scale atmospheric formations in a climatic year) and prognostic (allows understanding and tracking trends in climate, as well as quantitatively assessing the scale and variability of large-scale atmospheric processes). Numerical calculations were performed on the Lomonosov-2 supercomputer of the Lomonosov Moscow State University.

Abstract: The stability problem is considered in terms of the classical Lyapunov definition. For this, a set of initial conditions is set, consisting of their preliminary calculations, and the spread of the trajectories obtained as a result of numerical simulation is analyzed. This procedure is implemented as a series of ensemble experiments with a joint MPI-ESM model of the Institute of Meteorology M. Planck (Germany). For numerical modeling, a series of different initial values of the characteristic fields was specified and the model was integrated, starting from each of these fields for different time periods. Extreme ocean level characteristics over a period of 30 years were studied. The statistical distribution was built, the parameters of this distribution were estimated, and the statistical forecast for 5 years in advance was studied. It is shown that the statistical forecast of the level corresponds to the calculated forecast obtained by the model. The localization of extreme level values was studied and an analysis of these results was carried out. Numerical calculations were performed on the Lomonosov-2 supercomputer of Lomonosov Moscow State University.

Abstract: Modern astronomy experiences a rapid increase of data being acquired in obser-vations or in numerical simulations. Efficient storage and management of these data is a problem as important as the scientific analysis itself. In the article we analyze the reasons behind such an "information explosion" and outline the problems the Virtual Observatory faces due to it – primarily, the development of standards and technologies for accessing the data remotely and in an automated way. We also review the main requirements for modern scientific information such as repeatability of results, versioning, data provenance etc. Obvious solution for long-term storage of such a data is Database Management Systems (DBMS). We discuss how well different kinds of astronomical information – catalogues, spectra, images, time series, simulation results – are compatible to relational model of most popular DBMSs and formulate requirements for specia-lized systems which are optimal for storage and analysis of scientific data.

Abstract:

The paper analyzes the statistical and temporal seasonal and decadal variability of the atmospheric pressure field in the Arctic region of Russia. Schemes for the frequency analysis of probability transitions for characteristics of stochastic-diffusion processes were used as the main research method. On the basis of the given series of 60 years long from 1948 to 2008, such parameters of diffusion processes as the mean (drift process) and variance (diffusion process) were calculated and their maps and time curves were constructed. The seasonal and long-term variability of calculated fields was studied as well as their dependencies on a discretization of the frequency intervals. These characteristics were analyzed and their geophysical interpretation was carried out. In particular, the known cycles of solar activity in 11 and 22 years were revealed. Numerical calculations were performed on the Lomonosov-2 supercomputer of the Lomonosov Moscow State University.

Abstract: International Virtual Observatory (IVO) is a collection of integrated astronomical data archives and software tools that utilize computer networks to create an environment in which research can be conducted. Several countries have initiated national virtual observatory programs that will combine existing databases from ground-based and orbiting observatories and make them easily accessible to researchers. As a result, data from all the world's major observatories will be available to all users and to the public. This is significant not only because of the immense volume of astronomical data but also because the data on stars and galaxies have been compiled from observations in a variety of wavelengths: optical, radio, infrared, gamma ray, X-ray and more. Each wavelength can provide different information about a celestial event or object, but also requires a special expertise to interpret. In a virtual observatory environment, all of this data is integrated so that it can be synthesized and used in a given study. The International Virtual Observatory Alliance (IVOA) represents 17 international projects working in coordination to realize the essential technologies and interoperability standards necessary to create a new research infrastructure. Russian Virtual Observatory is one of the founders and important members of the IVOA. The International Virtual Observatory project was launched about ten years ago, and major IVO achievements in science and technology in recent years are discussed in this presentation. Standards for accessing large astronomical data sets were developed. Such data sets can accommodate the full range of wavelengths and observational techniques for all types of astronomical data: catalogues, images, spectra and time series. The described standards include standards for metadata, data formats, query language, etc. Services for the federation of massive, distributed data sets, regardless of the wavelength, resolution and type of data were developed. Effective mechanisms for publishing huge data sets and data products, as well as data analysis toolkits and services are provided. The services include source extraction, parameter measurements and classification from data bases, data mining from image, spectra and catalogue domains, multivariate statistical tools and multidimensional visualization techniques. Development of prototype VO services and capabilities implemented within the existing data centers, surveys and observatories are also discussed. We show that the VO has evolved beyond the demonstration level to become a real research tool. Scientific results based on end-to-end use of VO tools are discussed in the presentation.

Abstract:

The observational data for 1979-2018 in the North Atlantic region are analyzed. These data were obtained as a result of the implementation of the project of the Russian Academy of Sciences for the study of the atmosphere in the North Atlantic (RAS-NAAD). The dataset provides many surface and free atmosphere parameters based on the sigma model and meets the many requirements of meteorologists, climatologists and oceanographers working in both research and operational fields. The paper analyzes the seasonal and long-term variability of the field of heat fluxes and water surface temperature in the North Atlantic. Schemes for analyzing diffusion processes were used as the main research method. Based on the given series of 40 years in length from 1979 to 2018, such parameters of diffusion processes as the mean (process drift) and variance (process diffusion) were calculated and their maps and time curves were constructed. Numerical calculations realized on the Lomonosov-2 supercomputer of the Lomonosov Moscow State University.