Probabilistic analysis of the seasonal variation of fields based on observational data on heat fluxes in the North Atlantic

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 longterm 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.