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Variations of Caspian Sea water budget in the epoch of the Last Glacial Maximum (LGM, ~21 thousand years ago) relative to the preindustrial conditions (~1850 CE) are considered using data of climatic modeling under PMIP4-CMIP6 projects. The variations of evaporation from the Caspian Sea surface and the volumes of river flow required to maintain the equilibrium state of the lake under various climate conditions and under various lake levels were also evaluated with the use of a regional configuration of the eddy-resolvingoceanic model INMIO-CICE. The boundary conditions in the oceanic model were derived from experiments with INMCM climate model reproducing LGM climate and the climate of preindustrial period. According to the data of PMIP4 simulation, both Volga runoff and evaporation from the Caspian Sea surface decreased in LGM epoch compared with the control experiment. The difference between the estimates by different models is rather high: from −5 to −50% for the Volga, and from −2 to −20% for the Caspian Sea. Such results are not enough to make unambiguous conclusions about whether the position of the Caspian in the LGM period was regressive or transgressive; however, deep regression of the Caspian is excluded. Even if the Caspian level is estimated with the use of the results of the model that has demonstrated the maximal decrease in the Volga runoff, the volume of river runoff from the territory of the Caspian basin will be enough to prevent the sea level dropping below –45 m above sea level.

The mid-Holocene (6000 years ago) is a standard time period for the evaluation of the simulated response of global climate models using palaeoclimate reconstructions. The latest mid-Holocene simulations are a palaeoclimate entry card for the Palaeoclimate Model Intercomparison Project (PMIP4) component of the current phase of the Coupled Model Intercomparison Project (CMIP6) – hereafter referred to as PMIP4-CMIP6. Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the Northern Hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler than the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe, and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on the hydrological cycle, feedback strength, and potentially climate sensitivity.

Snow cover has a great influence on the energy balance on the surface, in particular ability to reflect solar radiation. As well as radiation, when modeling the climate, it is important to correctly describe the water cycle. During the transitional seasons, when the temperature fluctuates around zero degrees Celsius, some of the melt water can be retained in the snow layer and refreeze. In addition, over time after a snowfall the snow becomes denser. Aged, wet, refrozen snows have different optical properties than new-fallen snow, in particular a lower albedo. Moreover, atmospheric aerosols falling on a snow-covered surface leads to its pollution and, as a consequence, reduces its reflectivity. Aerosols such as mineral dust and black carbon have the greatest effect on the albedo and radiation balance.In the climatу model INMCM, some physical features of snow cover have been implemented. The porous structure of the snow is taken into account and the calculation of the water content of the snow layer is realized. During snowmelt, the ratio of the water is retained in the pores, and does not go immediately to the upper boundary of the soil. The possibility of refreezing of melt water contained in the snow layer has also been implemented. The change in snow density over time is taken into account. At the same time, it is assumed that the snow layer consists of a mixture of usual and refrozen snow, as well as melt water contained in snow pores. The influence of the composition of the snow layer and its density on the reflectivity is taken into account. The effect on the albedo of impurities contained in snow is also taken into account (for example, black carbon). Computational experiments were carried out with the INMCM model to assess the sensitivity to the realized physical processes.This work is supported by the Russian Science Foundation, project No. 20-17-00190.

During the 2019/2020 winter season the extremely high air temperature and precipitation were recorded over northern Eurasia, eastern Asia and eastern North America. Over the UK this winter was stormy and one of the wettest for the entire observational period. Moreover, it was the only winter without stable snow cover in the central East European Plain. The reason of such exceptional weather is the domination of a North Atlantic Oscillation (NAO) positive phase during the whole season.Since the NAO effect on winter weather is strong, prediction of its phase is a challenge for all national meteorological services. Several of them predicted the positive sign of North Atlantic Oscillation phase for 2019/2020 winter season, but underestimated the magnitude and duration. Forecasts obtained from INM RAS climate model (INMCM5) demonstrated consistent results for the considered season.In this work we use the INMCM5 to study the sources of the predictability of both the extremely positive NAO phase and the weather fields anomalies in the 2019/2020 winter season. In particular we consider whether the INM RAS climate model simulates the positive Indian Ocean dipole — positive North Atlantic Oscillation phase teleconnection.The research was carried out during the student educational program "Computational Technologies, Higher Order Data Analysis and Modelling" at the Sirius University and partially supported by the Russian Science Foundation (project 20‑17‑00190).

The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to the Coupled Model Intercomparison Project (CMIP6) is the Tier 1 Last Interglacial experiment for 127 000 years ago (lig127k), designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models as for the future and following a common experimental protocol. Here we present a first analysis of a multi-model ensemble of 17 climate models, all of which have completed the CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. The equilibrium climate sensitivity (ECS) of these models varies from 1.8 to 5.6 ∘C. The seasonal character of the insolation anomalies results in strong summer warming over the Northern Hemisphere continents in the lig127k ensemble as compared to the CMIP6 piControl and much-reduced minimum sea ice in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than the CMIP6 midHolocene simulations as expected from the larger insolation anomalies at 127 than 6 ka. New synthesis for surface temperature and precipitation, targeted for 127 ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and for precipitation over the Northern Hemisphere continents. The model–data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions. The CMIP6–Paleoclimate Modeling Intercomparison Project (PMIP4) lig127k simulations, in combination with the proxy record, improve our confidence in future projections of monsoons, surface temperature, and Arctic sea ice, thus providing a key target for model evaluation and optimization.

The amplified warming of the Arctic is one of several factors influencing atmospheric dynamics. In this work, we consider a series of numerical experiments to identify the role of Arctic sea ice reduction in affecting climate trends in the Northern Hemisphere. With this aim in mind, we use two independent mechanisms of ice reduction. The first is traditionally associated with increasing the concentration of carbon dioxide in the atmosphere from the historic level of 360 ppm to 450 ppm and 600 ppm. This growth increases air temperature and decreases the ice volume. The second mechanism is associated with a reduction in the reflectivity of ice and snow. We assume that comparing the results of these two experiments allows us to judge the direct role of ice reduction. The most prominent consequences of ice reduction, as a result, are the weakening of temperature gradient at the tropopause level in mid-latitudes, the slower zonal wind at 50–60∘ N, intensification of wave activity in Europe, Western America, and Chukotka, and its weakening in the south of Siberia and Kazakhstan. We also consider how climate change may alter regimes such as blocking and stationary Rossby waves. The study used the INM-CM48 climate system model.

The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

The article describes the development of the version of the SL-AV global semi-Lagrangian atmospheric model with high spatial resolution in the stratosphere. The new model version uses the vertical grid of 100 levels, grid spacing of 500 m in the layer between 100 and 10 hPa, and the upper lid at 0.04 hPa. The parameterization of the non-orographic gravity wave drag is implemented. Numerous modifications are introduced in the block for the numerical solution of dynamical equations to enhance model stability. The experiment on atmospheric dynamics modeling for 28 years is carried out. It is shown that the SL-AV model reproduces the main features of stratospheric circulation, such as the polar night stratospheric jet formation and sudden stratospheric warming. The quasi-biennial oscillation of equatorial wind is reproduced with realistic period and amplitude.

Seasonal prediction and climate change modeling are carried out on the basis of the programs incorporating the global model of the atmosphere, ocean model, sea ice and land models, etc. Each component of a coupled model has to provide a fairly complete representation of the physical processes in the appropriate medium, while the other components are replaced by reanalysis data. In this paper we present the results of a study aimed at improving the quality of the climate simulation with the SL-AV global atmospheric model where both ocean sur face temperature and ice concentration are prescribed. We also discuss some probtems in tuning the parameterizations of subgrid-scale physical processes and their modifications.

The results of numerical experiments on the sensitivity of the INMCM48 Earth System model (Institute of Numerical Mathematics, Russian Academy of Science (INM RAS)) to the various parameterizations of convection induced by the formation of a new ice are presented and analyzed. It is shown that the response in temperature and salinity is observed not only directly under the ice, but in ocean subpolar regions as well, which is especially pronounced in the North Atlantic. An effective parameterization is proposed which significantly reduces the estimation error of the surface salinity in the AO with no formation of the trends of the near-bottom salinity fields, in contrast with the well-known parameterization (Nguyen, Menemenlis and Kwok, 2009).

The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to CMIP6 is the Tier 1 lig127k experiment, designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models and following a common experimental protocol. We present a multi-model ensemble of 17 climate models, all of which (except for two) have also completed the CMIP6 DECK experiments. The Equilibrium Climate Sensitivity (ECS) of these models varies from 2.1 to 5.6 °C. The seasonal character of the insolation anomalies results in strong warming over the Northern Hemisphere (NH) continents in the lig127k ensemble as compared to the piControl in June–July–August and a much-reduced minimum (August–September) summer sea ice extent in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation and areal extent in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than midHolocene simulations as expected from the larger insolation anomalies at 127 ka than 6 ka. New syntheses for surface temperature and precipitation, targeted for 127 ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and precipitation over the Northern Hemisphere continents. The model-data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the specified boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions. The CMIP6-PMIP4 lig127k simulations, in combination with the proxy record, have potential implications for confidence in future projections of monsoons, surface temperature, Arctic sea ice, and the stability of the Greenland ice sheet.

The Last interglacial (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models’ representation of climate reconstructions is one of the objectives set up by the Paleoclimate Mod-elling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 12 climate models in terms of Arctic sea ice. The mean pre-industrial to LIG reduction in minimum sea ice area (SIA) reaches 59 % (multi-model mean LIG area is 2.21 mill. km2, compared to 5.85 mill. km2 for the PI), and the range of model results for LIG minimum sea ice area (from 0.02 to 5.65 mill. km2) is larger than for PI (from 4.10 to 8.30 mill. km2). On the other hand there is little change for the maximum sea ice area (which is 12 mill. km2 for both the PI and the LIG, with a standard deviation of 1.04 mill. km2 for PI and 1.21 mill. km2 for LIG). To evaluate the model results we synthesize LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. South of 78° N in the Atlantic and Nordic seas the LIG was seasonally ice-free. North of 78° N there are some discrepancies between sea-ice re-constructions based on dinocysts/foraminifers/ostracods and IP25: some sites have both seasonal and perennial interpretations based on the same core, but different indicators. Because of the conflicting interpretations it is not possible for any one model to match every data point in our data synthesis, or say whether the Arctic was seasonally ice-free. Drivers for the inter-model differences are: different phasing of the up and down short-wave anomalies over the Arctic ocean, associated with differences in model albedo; possible cloud property differences, in terms of optical depth; LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally we note that inter-comparisons between the LIG simulations, and simulations with moderate CO2 increase (during the transition to high CO2 levels), may yield insight into likely 21C Arctic sea ice changes using these LIG simulations.

The Last Glacial Maximum (LGM, ~ 21,000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models have been used to generate LGM simulations as part of the Palaeoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3-CMIP5). We show that the PMIP4-CMIP6 are globally less cold and less dry than the PMIP3-CMIP5 simulations, most probably because of the use of a more realistic specification of the northern hemisphere ice sheets in the latest simulations although changes in model configuration may also contribute to this. There are important differences in both atmospheric and ocean circulation between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large so, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land-sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the palaeoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. The spatial patterns of increased precipitation associated with changes in the jet streams are also poorly captured. However, changes in the tropics are more realistic, particularly the changes in tropical temperatures over the oceans. Although these results are preliminary in nature, because of the limited number of LGM simulations currently available, they nevertheless point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.

El Niño–Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.

Sea ice formation is accompanied by the rejection of salt which in nature tends to be mixed vertically by the formation of convective plumes. Here we analyze the influence of a salt plume parameterization in an atmosphere‐sea ice‐ocean model. Two 330‐yearlong simulations have been conducted with the AWI Climate Model. In the reference simulation, the rejected salt in the Arctic Ocean is added to the uppermost ocean layer. This approach is commonly used in climate modeling. In another experiment, employing salt plume parameterization, the rejected salt is vertically redistributed within the mixed layer based on a power law profile that mimics the penetration of salt plumes. We discuss the effects of this redistribution on the simulated mean state and on atmosphere–ocean linkages associated with the intensity of deepwater formation. We find that the salt plume parameterization leads to simultaneous increase of sea ice (volume and concentration) and decrease of sea surface salinity in the Arctic. The salt plume parameterization considerably alters the interplay between the atmosphere and the ocean in the Nordic Seas. The parameterization modifies the ocean ventilation; however, resulting changes in temperature and salinity largely compensate each other in terms of density so that the overturning circulation is not significantly affected.

In this paper we consider the influence of various parametrizations of aerosol-cloud-interaction on the total solar radiation and cloud transmission at the earth's surface according to the INMCM5 model. Several 10-year numerical experiments were carried out with/without three parametrizations of this interaction. In addition, numerical experiments with different emissions of aerosol precursor gases for 1980 and 2005 were performed. We show that the account for aerosol particles in aerosol-cloud interaction leads to an increase in the cloudiness by an average of 0.1 and a decrease in the total radiation by 25 W/m2. As a result, there is a decrease in the air temperature by an average of 2 degrees for all months of the year. This result confirms the theoretical assumptions about the increase of the cloud albedo effect with a decrease in the effective radius of the particles. However, numerical experiments with different emissions of aerosol precursor gases for 2005 and for 1980 revealed that at lower emissions there is a decrease in cloud transmission and an increase in the cloudiness. The probable causes of the observed effect are discussed.

The paper analyzes the results ofthe numerical experiment aiming at the reconstruction of climate ofthe penultimate (Eemian) interglacial (last interglacial, LIG) obtained using the Earth system model developed in the Institute of Numerical Mathematics of RAS. Orbital parameters were set with the periodicity of one thousand years and were further interpolated with the time step of 100 years. Assuming that during the LIG the concentrations of greenhouse gases were not very much different from the preindustrial values, this potential forcing was neglected. The climatic block of the ESM was called every 100 model years to foltow changes in orbital forcmg. The sub–models of ice sheets were asynchronously coupled to the sub–models of the atmosphere and the ocean with the ratio of model years as 100 to 1. Obtained anomaly (Eemian versus preindustrial) fields of surface air temperature generally correspond to the results of the earlier studies. Changes in the structure of the global atmospheric circulation resulted in the transformation ofthe precipitation field in some world regions. In particular, precipitation growth in North Africa was the reason for the radical change of landscapes.

In the framework of the study of the Eemian interglacial we consider the role of the Greenland ice sheet in the rise of the mean level of the World Ocean. Its contribution estimated as 2 m confirms the newest estimates based on the model results and on the proxy data analysis. In the beginning of the Eemian interglacial (earlier than 126 thousand years ago) mass lost occurs through the marine margin of the sheet. During the next five millennia, the negative surface mass balance plays the leading role. Taking into account the contribution of Greenland ice sheet, ocean thermal expansion, and the melting of mountain glaciers and ice caps, it is very probable that the West Antarctic ice sheet was the main source of the global sea level growth equal to 6–9 m the compared to the present.

Currently, the Earth system models are widely used for studying present-day climate dynamics and for palaeoreconstructions. A full Earth system model should include dynamical ice sheet models of Greenland and Antarctica as subsystems. To couple the latters with the atmospheric and with the oceanic blocks, it is necessary to introduce a special procedure to sustain mutual data exchange between subsystems with different temporal and spatial scales. In this paper, we give a brief description of the blocks of the Earth system model developed in the Institute of Numerical Mathematics of RAS (INMCM). On the basis of the previous studies aimed at examination of sensitivity of the cryospheric block of the model to variations in the key model parameters, we carried out numerical experiments to prove stability of the model climate and to establish equilibration time of the Greenland ice sheet to the conventional pre-industrial climate. It was confirmed that our Earth System Model with the interactively and asynchronously coupled Greenland ice sheet model simulates stationary climate. Equilibration time of the Greenland ice sheet is nearly 20 thousand model years. It was demonstrated that the values of calculated surface mass balance and its components correspond to similar model results described in the literature.

The results of joint analysis of temperature variations near mesopause from long-term measurements at the Zvenigorod Scientific Station of the Obukhov Institute of Atmospheric Physics RAS in 1960–2015 and variations of surface air temperature characterizing global climate change. Together with variations of temperature at the mesopause T ms from measurements of the hydroxyl emissions we analyzed the temperature variations near mesopause T m reduced to the same level of solar activity. The observed strong decrease in temperature near mesopause during last decades, particularly in winter, with its tendency to slow down since the 1980’s is was detected against the background of general increase in the surface air temperature of the Northern Hemisphere T NHs and the Earth as a whole. It was revealed a sharp drop in winter temperature near mesopause in 1970s. and its synchronicity with the shift in climatic features at the surface associated with changes in formation of El Nino events and their impact on the global climate. The general significant negative correlation of temperature variations near mesopause and T NHs detected from 56-year observational data was not accompanied by any significant coherence between the most long-period temperature variations from the cross-wavelet analysis. To assess the possible manifestation of this coherence the results of numerical simulations with a global climate model were used. According to model simulations for the 20–21 centuries taking into account anthropogenic forcings for significant coherence between long-term variations T m and T NHs the prolonged observations are required for temperature near mesopause–about a century or more.

The INMCM5.0 numerical model of the Earth’s climate system is presented, which is an evolution from the previous version, INMCM4.0. A higher vertical resolution for the stratosphere is applied in the atmospheric block. Also, we raised the upper boundary of the calculating area, added the aerosol block, modified parameterization of clouds and condensation, and increased the horizontal resolution in the ocean block. The program implementation of the model was also updated. We consider the simulation of the current climate using the new version of the model. Attention is focused on reducing systematic errors as compared to the previous version, reproducing phenomena that could not be simulated correctly in the previous version, and modeling the problems that remain unresolved.

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979–2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

Some hemispheric variation features of the near surface air and sea-surface temperatures are considered. A specially designed technique of the wavelet-based cross-correlations is used for this purpose. In-phase synchronizations of the hemispheric temperatures as whole as well as such synchronizations between land and sea temperatures are found within the timescales of one, two, and six-seven decades. In contrast, no synchronization is found within the timescales between the above indicated ones. Consideration of the afore-mentioned temperatures in a long integration of the climatic model of the Marchuk Institute of Numerical Mathematics of RAS (the “Pi-Control” experiment when external forces were accepted equal to their mean values during the preindustrial period) shows lack of any synchronization. However, results of the “Historical” experiment when effects of external forces, and, in particular, small variations of the total solar irradiation (TSI), were taken into consideration, reveal similar in-phase synchronizations in the same timescales in which the in-phase synchronizations exist in reality, but during the second half of the XXth century only. Perhaps, it is so because the TSI effects were taken into consideration incorrectly for the first half of the XXth century. All (in reality and in the model runs as well) synchronized temperature variations lag respective TSI variations. From this one can suppose that the namely TSI-variations, despite their amplitudes are very small, synchronize the hemispheric temperature variations.

In this paper we present first results on the use of Polar WRF model for regionalization of the atmospheric circulation in the Arctic region produced by the global climate model INM-CM48 developed in INM RAS. We demonstrate that Polar WRF does not show run off effects in the first year of integration, gives reasonable results with respect to the global model with more details in the regions of complex topography and coast line.

The aerosol module is included into the INM RAS climate model. The module computes the evolution of main aerosols: sea salt, mineral dust, sulfate aerosol, and black and organic carbon. Aerosol surface fluxes, advection, gravitational sedimentation, surface absorption, and scavenging by precipitation are taken into account to compute aerosol concentration variations. Model aerosol distribution is used to compute radiation fluxes. The ten-year run of the climate model is performed. The climatology of model aerosol is considered. The aerosol mass, integral source values, optical thickness, and radiative forcing are presented. The results are compared with the data of other models and observations.

The results of simulations of the World Ocean sea surface hight (SSH) in by various versions of the Climate Model of the Institute of Numerical Mathematics, Russian Academy of Sciences, are compared with the CNES-CLS09 fields of the mean dynamic topography (deviation of the ocean level from the geoid). Three models with different ocean blocks are considered which slightly differ in numerical schemes and have various horizontal spatial resolution, i.e., the INMCM4 model, which participated in the Climate Model Intercomparison Project (CMIP Phase 5, resolution of 1° × 1/2°); the INMCM5 model, which participates in the next project, CMIP6 (resolution of 1/2° × 1/4°); and the advanced INMCM-ER eddy-resolving model (resolution of 1/6° × 1/8°). It is shown that an increase in the spatial resolution improves the reproduction of ocean currents (with Agulhas and Kuroshio currents as examples) and their variability. A probable cause of relatively high errors in the reproduction of the SSH of Southern and Indian oceans is discussed.

The Greenland ice sheet is a very important potential source of fresh water inflow to the World Ocean under warming climate conditions. Apparently, it was the same during the Last Interglacial 130-115 thousand years ago. In order to quantify input of the Greenland ice sheet to the rise of the global mean sea level in the past or in the future, we include a surface mass balance model block into the Earth System Model. The computational algorithm is based on the calculation of energy balance on the ice sheet surface. The key tuning parameter of the model is the daily amplitude of air surface temperature. It defines the area and the rate of snow or ice melting. The range of possible values of this parameter is determined during a series of numerical experiments. High sensitivity of meltwater runoff volume to surface air temperature amplitude is revealed.

The reproduction of dynamic processes in the stratosphere at extratropical latitudes is considered in calculations of the atmospheric module of the global climate model of the Institute of Numerical Mathematics, Russian Academy of Sciences, with an upper boundary of 0.2 hPa (~60 km) for the period from 1979 to 2008 in comparison with the data observational. Changes in temperature, zonal wind, activity of planetary waves, heat fluxes in the lower stratosphere, and sudden stratospheric warmings with the displacement and splitting of the polar vortex, as well as the distribution of associated circulation anomalies in the troposphere, are analyzed.

In this paper, we present the first results of the ionospheric potential (IP) calculations with the chemistry-climate model (CCM) SOCOL (Solar Climate Ozone Links). For the study, we exploit a parameterization of the difference in electric potential between Earth's surface and lower boundary of the ionosphere as a function of thunderstorm and electrified cloud properties. The model shows a good enough agreement with the IP obtained by balloon soundings. The simulated UT variation of IP exhibits a maximum at 20 Universal time (UT) and minimum at about 2 UT which agree with the UT cycle of the lightning activity. The obtained results allow understanding of IP variability pattern at diurnal, seasonal and annual timescales. We also compare our results with the IP simulated with the climate model INMCM4 using similar IP parameterization. The comparison shows a good agreement of UT cycles especially before 12 UT. Simulated IP annual cycle reaches its maximum in late spring in both models. However, the comparison also reveals some differences in amplitudes of IP variability on different time scales. The large deviations occur after 12 UT for all seasons except summer where the maximum of both results happens before 12 UT. The UT cycle of IP simulated with CCM SOCOL is in a better agreement with observations after 12 UT in terms of phase with similar timing of maximum values. The calculation of IP using climate models can help to fill up the gaps when the observed IP is not available. The interactive calculation of IP is also a step forward in coupling atmospheric and ionospheric processes.

Detailed monitoring of soil temperature provides a unique experimental material for studying the complex processes of heat transfer from the surface layer of the atmosphere to the soil. According to air temperature monitoring data, within each of the key areas there are no significant differences between the data of the observation sites. According to annual (2011-2018) observations of soil temperature, it has been found that the microclimatic properties of bog ecosystems clearly manifest themselves in the characteristics of daily and annual variations of soil temperature. The thickness of the seasonally frozen layer at all sites is 20-60 cm, and maximum freezing of the peat layer is reached in February-March. There is evidence of degradation of the seasonally frozen layer that occurs both from above and from below. It has been found that similar bog ecosystems in different bog massifs may have significantly different temperature regimes. The peat stratum of northern bogs may be both warmer (in winter) and colder (in summer), in comparison with some bogs located 520 km to the south and 860 km to the west.

Climate changes observed in 1850–2014 are modeled and studied on the basis of seven historical runs with the climate model INM-CM5 under the scenario proposed for the Coupled Model Intercomparison Project Phase 6 (CMIP6). In all runs global mean surface temperature rises by 0.8 K at the end of the experiment (2014) in agreement with the observations. Periods of fast warming in 1920–1940 and 1980–2000 as well as its slowdown in 1950–1975 and 2000–2014 are correctly reproduced by the ensemble mean. The notable change here with respect to the CMIP5 results is the correct reproduction of the slowdown in global warming in 2000–2014 that we attribute to a change in ocean heat uptake and a more accurate description of the total solar irradiance in the CMIP6 protocol. The model is able to reproduce the correct behavior of global mean temperature in 1980–2014 despite incorrect phases of the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation indices in the majority of experiments. The Arctic sea ice loss in recent decades is reasonably close to the observations in just one model run; the model underestimates Arctic sea ice loss by a factor of 2.5. The spatial pattern of the model mean surface temperature trend during the last 30 years looks close to the one for the ERA-Interim reanalysis. The model correctly estimates the magnitude of stratospheric cooling.

Elaboration of a modern Earth system model (ESM) requires incorporation of ice sheet dynamics. Coupling of an ice sheet model (ICM) to an AOGCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmospheric and oceanic components. To overcome this difficulty, we apply two different approaches for the incorporation of ice sheets into an ESM. Coupling of the Antarctic ice sheet model (AISM) to the AOGCM is accomplished via using procedures of resampling, interpolation and assigning to the AISM grid points annually averaged meanings of air surface temperature and precipitation fields generated by the AOGCM. Surface melting, which takes place mainly on the margins of the Antarctic peninsula and on ice shelves fringing the continent, is currently ignored. AISM returns anomalies of surface topography back to the AOGCM. To couple the Greenland ice sheet model (GrISM) to the AOGCM, we use a simple buffer energy- and water-balance model (EWBM-G) to account for orographically-driven precipitation and other sub-grid AOGCM-generated quantities. The output of the EWBM-G consists of surface mass balance and air surface temperature to force the GrISM, and freshwater run-off to force thermohaline circulation in the oceanic block of the AOGCM. Because of a rather complex coupling procedure of GrIS compared to AIS, the paper mostly focuses on Greenland.

Numerical experiments with the INMCM4 climate model have shown that the observed 10% difference in the lower tropospheric methane concentration between the Arctic and the Southern Hemisphere can be reproduced in a climate model in which only the present-day spatial distribution of anthropogenic methane emissions and calculated emissions from wet ecosystems are considered. In model runs with an additional 50- or 100-Mt/year methane emission in the Arctic, the difference in atmospheric methane concentrations between the Arctic and the Southern Hemisphere is higher than the observed one. An additional methane emission of 4000 Mt/year in the Arctic is shown to result in an increase of 1.5° in global mean surface air temperature. The spatial distribution of warming is similar to that induced by an increase in the carbon dioxide concentration, depends on the global mean methane concentration, and does not depend at all on where the additional methane source lies.

A general circulation model of the atmosphere and ocean INMCM4.0 (Institute of Numerical Mathematics Coupled Model) is used for modeling the global electric circuit short-time variability and long-term evolution. The ionospheric potential parameterization is proposed which takes into account quasi-stationary currents of electrified clouds (including thunderstorms) as principal contributors into the DC global circuit. The diurnal, seasonal, and interannual variations of the ionospheric potential (IP) are modeled and compared with available data. Numerical simulations suggest that the IP decreases in the mean with the global warming due to increasing greenhouse gas emission (by about 10% during the 21st century if the Representative Concentration Pathway 8.5 Wm−2 scenario is assumed). At the same time the lightning flash rate increases with global warming by about 5 fl/s per degree. Interannual IP variability is low and does not exceed 1% of the mean value, being tightly correlated with the mean sea surface temperature in the Pacific Ocean (El Nino area).

The Last Glacial Maximum (LGM, 21,000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalise on the relative abundance of palaeoenvironmental observations and quantitative climate reconstructions already available for the LGM.

The Last Glacial Maximum (LGM, 21 000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM.

The sensitivities of two climate-model versions—INMCM4 which participated in the Coupled Model Intercomparison Project, Phase 5 (CMIP5), and a new INMCM5 version with increased vertical and horizontal resolutions in its atmospheric block—to the quadrupled concentration of CO2 are studied. When the CO2 concentration is quadrupled, the equilibrium increase in surface temperature amounts to about 4.2 K for INMCM4, which is lower than that for other models that participated in the CMIP5. When the CO2 concentration increases, the cloud radiative forcing in the model decreases; in this case, one portion of this decrease occurs during the first year after the concentration of CO2 is quadrupled and the other portion almost linearly depends on the value of global warming. The results of additional numerical experiments with the model show that a rapid decrease in cloud-radiative forcing results from variations in stratification in the atmospheric surface boundary layer and associated increased cloudiness. The portion of a linear decrease in cloud-radiative forcing with increased temperature is associated with an increase in the water content of model clouds at higher temperatures. The elimination of these two mechanisms allows one to increase the model sensitivity to the quadrupled concentration of CO2 up to 5.2 K.