E. M. Volodin

Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations

The INMCM3.0 climate model has formed the basis for the development of a new climate-model version: the INMCM4.0. It differs from the previous version in that there is an increase in its spatial resolution and some changes in the formulation of coupled atmosphere-ocean general circulation models. A numerical experiment was conducted on the basis of this new version to simulate the present-day climate. The model data were compared with observational data and the INMCM3.0 model data. It is shown that the new model adequately reproduces the most significant features of the observed atmospheric and oceanic climate. This new model is ready to participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5), the results of which are to be used in preparing the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC).

Causes and implications of persistent atmospheric carbon dioxide biases in Earth System Models

The strength of feedbacks between a changing climate and future CO2 concentrations is uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations—in which atmospheric CO2levels were computed prognostically—for historical (1850–2005) and future periods (Representative Concentration Pathway (RCP) 8.5 for 2006–2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO2. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO2 biases and future CO2levels for the multimodel ensemble. We used this relationship to create a contemporary CO2 tuned model (CCTM) estimate of the atmospheric CO2 trajectory for the 21st century. The CCTM yielded CO2estimates of 600±14 ppm at 2060 and 947±35 ppm at 2100, which were 21 ppm and 32 ppm below the multimodel mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO2, CO2-induced radiative forcing, and CO2-induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO2 during the 21st century was tied to biases that existed during the observational era and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO2from Mauna Loa, our analysis suggests that uncertainties in future climate projections can be reduced.

Comparison of the Seasonal Change in Cloud-Radiative Forcing from Atmospheric General Circulation Models and Satellite Observations

We compare seasonal changes in cloud-radiative forcing (CRF) at the top of the atmosphere from 18 atmospheric general circulation models, and observations from the Earth Radiation Budget Experiment (ERBE). To enhance the CRF signal and suppress interannual variability, we consider only zonal mean quantities for which the extreme months (January and July), as well as the northern and southern hemispheres, have been differenced. Since seasonal variations of the shortwave component of CRF are caused by seasonal changes in both cloudiness and solar irradiance, the latter was removed. In the ERBE data, seasonal changes in CRF are driven primarily by changes in cloud amount. The same conclusion applies to the models. The shortwave component of seasonal CRF is a measure of changes in cloud amount at all altitudes, while the longwave component is more a measure of upper level clouds. Thus important insights into seasonal cloud amount variations of the models have been obtained by comparing both components, as generated by the models, with the satellite data. For example, in 10 of the 18 models the seasonal oscillations of zonal cloud patterns extend too far poleward by one latitudinal grid. •Institute for Terrestrial and Planetary Atmospheres, Marine Sciences Research Center, State University of New York at Stony Brook. 2program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, California. 3Department of Numerical Mathematics, Russian Academy of Sciences, Moscow. 4Canadian Climate Centre, Downsview, Ontario. SLaboratoire de Mdtdorologie Dynamique, Paris. 6Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia. 7Department of Atmospheric Science, Colorado State University, Fort Collins. 8NASA Goddard Institute for Space Studies, New York. 9Maltrio-France, Centre National de Recherches Mdtdorologiques, Toulouse, France. •oDivision of Atmospheric Research, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria, Australia. •Max Planck Institute for Meteorology, Hamburg, Germany. •2National Center for Atmospheric Research, Boulder, Colorado. •3Hadley Centre for Climate Prediction and Research, U. K. Meteorological Office, Bracknell, England. •4Atmospheric Sciences Research Center, State University of New York at Albany. •SVoeikov Main Geophysical Obseratory, St. Petersburg, Russia. •6European Centre for Medium-Range Weather Forecasts, Reading, England. •7Department ofAtmospheric Sciences, University of Illinois, Urbana. 18Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton University, Princeton, New Jersey. Copyright 1997 by the American Geophysical Union. Paper number 97JD00927. 01480227/97/97JD-00927509.00

Interpretation of Winter Warming on Northern Hemisphere Continents in 1977–94

Abstract Northern Hemisphere December–March near-surface temperature and pressure anomalies during 1977–94 relative to those during 1946–76 are considered. To a first approximation these anomalies can be decomposed into two components. The first one reaches its maximum during 1977–88. The main features of the anomalies of 1977–88 can be obtained as the atmospheric general circulation model (AGCM) response to sea surface temperature anomalies observed during that period. The second component reaches its maximum in 1989–94. The main features of anomalies of 1989–94 relative to 1977–88 can be obtained as the AGCM response to lower-stratosphere ozone depletion observed in 1989–94.

General circulation model results on migrating and nonmigrating tides in the mesosphere and lower thermosphere. Part I: comparison with observations

Abstract The general circulation model of the Department of Numerical Mathematics of the Russian Academy of Science ( Volodin and Schmitz, 2001 , Tellus 53A (2001) 300) from the surface to mesospheric and lower thermospheric heights has been used to analyse the diurnal and semi-diurnal tides. The GCM includes tropospheric and stratospheric tidal forcings due to absorption of the radiation and latent heat release and uses the gravity wave breaking parameterization of Hines (J. Atmos. Sol. Terr. Phys. 59 (1997a) 371; J. Atmos. Sol. Terr. Phys. 59 (1997b) 387). The model tides describe the observed tidal amplitudes and phases of eastward wind components at different northern hemispheric medium frequency radar sites (Andenes, Juliusruh, Saskatoon, Yamagawa and Hawaii) for January and July conditions. The separation of model tides into migrating and nonmigrating components shows that the nonmigrating part forms the total tide to a large extent, especially for the diurnal tide at low latitudes. The variability of diurnal and semi-diurnal tides is mostly determined by the variability of the nonmigrating part; the variability due to migrating tidal oscillations contributes only a small amount to the total variability. The nonmigrating diurnal model tide is strongly dependent on the longitude, with maxima in the western hemisphere at middle southern latitudes in January. In July, these tidal amplitudes are much weaker with maxima in the subtropics of the eastern hemisphere.

Simulation and prediction of climate changes in the 19th to 21st centuries with the Institute of Numerical Mathematics, Russian Academy of Sciences, model of the Earth’s climate system

This paper presents results from a simulation of climate changes in the 19th–21st centuries with the Institute of Numerical Mathematics Climate Model Version 4 (INMCM4) in the framework of the Coupled Model Intercomparison Project, phase 5 (CMIP5). Like the previous INMCM3 version, this model has a low sensitivity of 4.0 K to a quadrupling of CO2 concentration. Global warming in the model by the end of the 21st century is 1.9 K for the RCP4.5 scenario and 3.4 K for RCP8.5. The spatial distribution of temperature and precipitation changes driven by the enhanced greenhouse effect is similar to that derived from the INMCM3 model data. In the INMCM4 model, however, the heat flux to the ocean and sea-level rise caused by thermal expansion are roughly 1.5 times as large as those in the INMCM3 model under the same scenario. A decrease in sea-ice extent and a change in heat fluxes and meridional circulation in the ocean under global warming, as well as some aspects of natural climate variability in the model, are considered.

Combined chemistry-climate model of the atmosphere

A combined three-dimensional global model of the chemistry and dynamics of the lower and middle atmosphere (up to 90 km from the Earth’s surface) is described. With the use of this model within the AMIP2 (1979–1995) program, numerical calculations were performed with consideration for the interactive coupling between the ozone content, radiation heating, and atmospheric circulation. Comparisons were made between calculated and observed data on the ozone content and temperature. Heterogeneous processes on the surface of polar stratospheric clouds were shown to be important for a correct simulation of the spatial and temporal distribution of atmospheric ozone.

Variation of the global electric circuit and Ionospheric potential in a general circulation model

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).

A troposphere–stratosphere–mesosphere general circulation model with parameterization of gravity waves: climatology and sensitivity studies

The climatology of the troposphere–stratosphere–mesosphere model of the Institute forNumerical Mathematics (INM) with the uppermost level at 0.003 hPa is presented. This modelis vertically extended from the upper level of 10 hPa for the earlier version, and a drag parameterizationdue to internal gravity waves (GW) is included. The model describes the mainfeatures of the mesospheric circulation: decreasing and reversion of westerly and easterly winds, equatorward shift of the westerly wind maximum with height and reversal of the meridionaltemperature gradient in the upper mesosphere. The model underestimates to some extent theamplitude of wave number 1 for stationary waves in the winter hemisphere. The same holdsfor the internal low-frequency variability in the winter stratosphere. The sensitivity of the modelclimate is studied with respect to the inclusion of orographic gravity wave drag and the variationof the source height of internal gravity waves.

Relation between temperature sensitivity to doubled carbon dioxide and the distribution of clouds in current climate models

The paper considers a relation between equilibrium global warming at doubled carbon dioxide (climate sensitivity) and the distribution of clouds and relative humidity in 18 state-of-the-art climate models. There is a strong correlation among three indices: (1) model climate sensitivity, (2) mean cloud amount change due to global warming, and (3) the difference in cloud amount between the tropics and midlatitudes. In the simulation of the present-day current, models with high sensitivity produce smaller clouds amounts in the tropics and larger cloud amounts over midlatitude oceans than models with low sensitivity. The relative humidity in the tropics is smaller in models with high sensitivity than in models with low sensitivity. There is a similarity between vertical profiles of cloud amount and relative humidity under global warming and vertical profiles of the difference in these quantities averaged over the tropics and midlatitudes. Based on the correlations obtained and observations of cloud amount and relative humidity, an estimate is made of the sensitivity of a real climate system.