The work is devoted to the study of the climatic effects of black carbon (BC) transferred from forest fires to the Arctic zone. The HYSPLIT (The Hybrid Single-Particle Lagrangian Integrated Trajectory model) trajectory model was used to initially assess the potential for particle transport from fires. The results of the trajectory analysis of the 2019 fires showed that the probability of the transfer of particles to the Arctic ranges from 1% to 10%, and in some cases increases to 20%. Detailed studies of the possible influence of BC ejected as a result of fires became possible by using the climate model of the INMCM5 (Institute of Numerical Mathematics Climate Model). The results of the numerical experiments have shown that the maximum concentration of BC in the Arctic atmosphere is observed in July and August and is associated with emissions from fires. The deposition of BC in the Arctic increases by about 1.5–2 times in the same months, in comparison with simulation without forest fire emissions. This caused an average decrease in solar radiation forcing of 0.3–0.4 Wt/m² and an increase in atmospheric radiation heating of up to 5–6 Wt/m². To assess the radiation forcing from BC contaminated snow, we used the dependences of the change in the snow albedo on the snow depth, and the albedo of the underlying surface for a given amount of BC fallen on the snow. These dependences were constructed on the basis of the SNICAR (Snow, Ice, and Aerosol Radiative) model. According to our calculations, the direct radiative forcing from BC in the atmosphere with a clear sky is a maximum of 4–5 W/m² in July and August.

Simulations of Institute of Numerical Mathematics (INM) coupled climate model 5th version for the period from 2015 to 2100 under moderate (SSP2-4.5) and severe (SSP5-8.5) scenarios of greenhouse gases growth are analyzed to investigate changes of Arctic polar stratospheric vortex, planetary wave propagation, Sudden Stratospheric Warming frequency, Final Warming dates, and meridional circulation. Strengthening of wave activity propagation and a stationary planetary wave number 1 in the middle and upper stratosphere, acceleration of meridional circulation, an increase of winter mean polar stratospheric volume (Vpsc) and strengthening of Arctic stratosphere interannual variability after the middle of 21st century, especially under a severe scenario, were revealed. March monthly values of Vpsc in some winters could be about two times more than observed ones in the Arctic stratosphere in the spring of 2011 and 2020, which in turn could lead to large ozone layer destruction. Composite analysis shows that “warm” winters with the least winter mean Vpsc values are characterized by strengthening of wave activity propagation from the troposphere into the stratosphere in December but weaker propagation in January–February in comparison with winters having the largest Vpsc values.

Five 50-year simulations for the 5th version of the climate model of the Marchuk Institute of Numerical Mathematics, Russian Academy of Science (INM RAS), are used to analyze the interannual variability of Arctic stratospheric polar vortex and dates of spring breakup events (springtime transition) in comparison with reanalysis data. Early spring breakup events are accompanied by stronger wave activity in comparison with late ones. Winter seasons with the maximal air volume in the polar stratosphere and conditions sufficient for the formation of polar stratospheric clouds are characterized by relatively early spring breakup events.

This paper describes the modification of a simple land snow cover module of the INM RAS climate model. The possible liquid water and refreezing of meltwater in the snow layer are taken into account by the proposed parameterization. This is particularly important for modelling the transition season, as this phenomenon is mainly observed during the formation and melting of the snow cover when the surface temperature fluctuates around $0 °$C. The snow density evolution simulation is also added. This parameterization is implemented in the INM-CM snow module and verified on observation data using the ESM-SnowMIP-like protocol. As a result, the INM-CM mean climate snow melt periods are refined, particularly in middle and high latitudes. The snow-covered area according to the model is also improved. In the future, a modified version of the land snow module can be used, coupled with a snow albedo model that takes into account snow metamorphism. This module can also be applied to sea ice snow.

Using a balance model of the snow layer, we estimate the concentration of black carbon (BC) in the snow; then, with the help of radiative transfer model SNICAR, we calculate the snow albedo and radiative forcing (RF) from snow darkening with BC. Data from an ensemble simulation with INMCM5, the 5th version of the climate model of Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences for the period 1998–2002 are used as input, which include snow both on land and on sea ice. The regionally averaged results are compared with other model data and field measurements.

The problem of wind-driven circulation in a thin layer of homogeneous viscous rotating fluid is considered. In the limit of small Froude and Burger numbers it is described by two parameters—the...