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 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:

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.

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:

To analyze heat fluxes, observational data for 1979-2018 were used for the North Atlantic. The spatiotemporal variability of the total heat flux was modeled by a stochastic diffusion process. The coefficients of the stochastic differential equation were estimated by using nonparametric statistics. Previously, the existence and uniqueness of a solution in the strong sense of the stochastic differential equation generated by the constructed diffusion process was proven when Kolmogorov's conditions were met. In this work, the coefficients of the equation were approximated in time by trigonometric polynomials, the amplitudes and phases of which depended on the flow values. Using a given series of 40 years in length from 1979 to 2018, spatial maps and time curves were constructed. The results are shown for 1999 and 2018, and their comparative analysis is also carried out. Numerical calculations were realized on the Lomonosov-2 supercomputer of the Lomonosov Moscow State University.

Abstract:

Observational data from the North Atlantic over 40 years of the NAAD project were analyzed. The total heat flux from the ocean to the atmosphere (and from the atmosphere to the ocean) was considered as the sum of latent and sensible heat. The coefficients of the stochastic differential equation representing the stochastic process were statistically determined from the original data set. Previously, the existence and uniqueness of a solution in the strong sense of the stochastic differential equation generated by the constructed diffusion process was proven when Kolmogorov's conditions were met. Numerical calculations on the Lomonosov-2 supercomputer at Moscow State University. M.V. Lomonosov.