Climate of Russia in the 21st century. Part 3. Future climate changes calculated with an ensemble of coupled atmosphere-ocean general circulation CMIP3 models

Probable climate changes in Russia in the 21st century are considered based on the results of global climate simulations with an ensemble of coupled atmosphere-ocean CMIP3 models. The future changes in the surface air temperature, atmospheric pressure, cloud amount, atmospheric precipitation, snow cover, soil water content, and annual runoff in Russia and some of its regions in the early, middle, and late 21st century are analyzed using the A2 scenario of the greenhouse gas and aerosol emission. Future changes in the yearly highest and lowest surface air temperatures and in summer precipitation of high intensity are estimated for Russia. Possible oscillations of the Caspian Sea level associated with the expected global climate warming are estimated. In addition to the estimates of the ensemble mean changes in climatic characteristics, the information about standard deviations and statistical significance of the corresponding climate changes is given.     

Projected climate change impacts on the operation of power engineering facilities in Russia

The aspects ofthe impact ofcurrent and future (in the middle of the 21st century) climate change on the operational safety and efficiency of traditional energy sources (thermal, nuclear, and hydroelectric power stations) in seven regions of Russia are considered. The climate change projections are provided by the ensemble of the MGO regional climate model with the resolution of 25 km under the IPCC RCP8.5 scenario. The regions with the highest weather- and climate-related risk for the energy production are identified, and some recommendations on the risk reduction are provided.     

How much the warming in Russia agrees with the output of coupled atmosphere-ocean general circulation models?

Climate variability parameters and air temperature trends in Russia, derived from observational data, are compared with those derived from climate modeling in the second half of the 20th-early 21st century, using the atmosphere-ocean general circulation model ensemble. The computation results from these models were used in the preparation of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. It is demonstrated that the ensemble averaging allowed us to efficiently filter the internal climate variability and get relatively stable estimates of trends. As a whole, for Russia, these estimates are in good agreement with the observational data, both for a year on average, and in individual seasons. The comparison of model and observed air temperature trends on a regional scale turns out to be irrelevant in a number of cases because of a high inadequacy of trend estimates derived from the observational data.     

Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model

The results are analyzed of the ensemble forecast of temperature and precipitation extremes on the territory of Siberia by the middle of the 21st century based on the regional climate model of the Main Geophysical Observatory (MGO) with the resolution of 25 km. The results of computation of oceanic components of CMIP3 coupled models are used as the boundary conditions on the sea surface. It is demonstrated that the high resolution of the regional model enables to simulate the observed climate variability in a more realistic way as compared to the low-resolution models. The analysis of the signal-to-noise ratio for future climate changes made it possible to determine to which degree its internal variability for various time scales (from interannual to interdecennial one) bounds the potential of the ensemble to compute the statistically significant anthropogenic changes of extremes. A comparative analysis of variations of extreme and average seasonal characteristics of the Siberian climate is carried out.     

Climate of Russia in the 21st century. Part 1. New evidence of anthropogenic climate change and the state of the art of its simulation

This is the first of three papers devoted to the study of climate change in Russia in the 20th and 21st centuries using ensembles of CMIP3 Atmosphere-Ocean General Circulation Models. Current studies of observed global and regional climate changes are briefly reviewed based on the analysis of the Intergovernmental Panel on Climate Change (IPCC). The anthropogenic nature of climate change is emphasized. It is also noted that the observed warming in Russia is significantly larger than global warming. Alternative hypotheses on causes of global climate changes discussed in some Russian publications are reviewed and their groundlessness is shown. The paper discusses some characteristics of ensembles of CMIP3 models that participated in the preparation of the IPCC Fourth Assessment Report. A model quality index is introduced. The dependence of simulated climate change in Russia on the choice of model ensembles and emission scenarios is considered. It is shown that the climate change in Russia does not depend significantly on the emission scenario choice until the middle of the 21st century.     

Effects of climate change and extreme events on forest communities in the European North

The European north is increasingly affected by changes in climate and climate variability. These changes and their causes are global in scope but specific impacts vary considerably between different regions. Recent incidents and events show that forest-resource based regions have difficulties in alleviating adverse effects of these changes. Also, the future socio-economic impact is to date unexplored. Norrbotten in Sweden, Lappi in Finland and Arkhangelsk oblast in Russia are regions that differ significantly in terms of their socio-economic characteristics and capacities. A modified employment multiplier model is used to predict future changes. Scenarios of changing forest resources provide quantitative estimations of the sensitivity of regional employment. These estimates are used to assess and discuss the adaptive capacities of the regions. Results show that Arkhangelsk oblast is more vulnerable to climate variability than Norrbotten and Lappi. This is due to the continued dependency on natural resources in combination with different capacities to counteract negative effects or to take advantage of the opportunities offered by climate change in this region.     

A correspondence between the model ensemble simulations and observations of temperature changes on the territory of Russia

The results are presented of the statistical analysis of correspondence between the model simulations and observations of temperature changes on the territory of Russia. Three model ensembles are considered, differing in the level of taking account of the impact of external forcings on the climate system of the Earth. For each of them, the statistical correspondence is estimated between the observed surface air temperature variations in the second half of the 20th century and at the beginning of the 21st century and model simulations taking account of the natural variability typical of the climate system. The analysis demonstrated that, in spite of the uncertainties associated with the differences in the representation of anthropogenic and natural external forcings on the climate in model simulations as well as with the imperfection of climate models and with internal variability of the climate system, the model experiments enable to obtain the relevant information both on the temporal evolution of temperature changes on the territory of Russia and on their spatial peculiarities.     

Evaporation from Irrigated Lands in Arid Regions as Inferred from the Regional Climate Model and Atmospheric Boundary Layer Model Simulations

The applicability is analyzed of the modeling system consisting of the MGO regional climate model and multilevel atmospheric boundary layer model for the mesoscale climate change evaluation in the regions with irrigated land use. Based on these models, the Aral Sea evolution impact on the spatial distribution of temperature and humidity in the vicinity of irrigated land is assessed. Numerical experiments cover climate evolution during 1979–2011. It is shown that in the middle of the 20th century the Aral Sea impact was manifested in the temperature and humidity distributions up to the altitude of 200–300 m at the distance of about 40 km off the seashore. The effect of advection on the calculated values of evapotranspiration in irrigated areas located at different distances from the sea is also investigated. Different methods for the determination of evapotranspiration over the irrigated cotton fields are intercompared. The influence of different resolution of surface temperature distribution on total evapotranspiration estimates is analyzed.     

Scientific basis of agrometeorological and agroclimatic support to the agrarian sector of the Russian economy

Results are reviewed of the studies aimed at the development of current techniques for estimation of bioclimatic potential of Russia to provide agrometeorological support to the agrarian sector of economy under the present-day conditions. Problems are considered of estimating and accounting the effects of the climate changes on productivity and long-term stability of agriculture. Results are presented of using the satellite information for operative monitoring of condition and productivity of agriculture. It is shown that the studies carried out at All-Russian Research Institute of Agricultural Meteorology (VNIISKhM) allow creating a complex system for operative agrometeorological monitoring on the basis of the modern models of the agro-ecosystem productivity. The system will allow regular estimating of conditions, expected harvest and total yield in the times specified by Roshydromet and presenting a set of their probability estimates as dependent on the predicted weather. As a result, all levels of the agriculture, from the farmers to the Ministry of Agriculture, will be provided with agrometeorological and agroclimatic information.     

Climate of Russia in the 21st Century. Part 2. Verification of atmosphere-ocean general circulation models CMIP3 for projections of future climate changes

Results of simulation of radiation, cloud cover, surface air temperature, sea-level pressure, and hydrological regime components for Russia with the help of an ensemble of CMIP3 global climate models is analyzed. Despite a large spread among the models, the CMIP3 AOGCM ensemble simulations of the key characteristics of the observed surface climate agree well with observations, anyway in averaging over areas of vast regions, from watersheds of large rivers to the whole of Russia. These means (ensemble-and area-averaged values) often fall into the range of estimates derived from observations. This suggests the existence of uncertainty in the estimates obtained from simulations as well as from observational data. Comparison of different-generation models demonstrates a gradual improvement of the AOGCM simulation of surface climate characteristics. In general, the averaging over the CMIP3 AOGCM ensemble allows us to state that the ensemble is suitable for estimates of future climate changes.     

Dynamics of severe atmospheric droughts in European Russia

Severe atmospheric droughts of different intensity over the southern Russian Plain are studied using the observations and model data during the period of 1936–2100. Spatial distribution, frequency, and duration of droughts are considered. Dynamics of extreme droughts in the 20th century is derived from the meteorological station data. The tendency of drought occurrence in 1991–2000, 2041–2050, and 2091–2100 is obtained from the MGO (Main Geophysical Observatory) regional climate model (RCM). A catalog of severe atmospheric droughts of different intensity is made based on the observations for 1936–2000 and modeling results for 1991–2000. The comparison of the observational and model data has shown that the MGO RCM simulates well the frequency of severe atmospheric droughts.     

Temperature extremes and wildfires in Siberia in the 21st century: the MGO regional climate model simulation

Possible changes in temperature extremes and wildfires in the 21st century in the regions of Russia are analyzed using a regional climate model (RCM) with high space-time resolution. The IPCC A2 scenario of greenhouse gas and aerosol concentration increase in the atmosphere is used. It is shown that changes in extreme wildfires appear to be in the 21st century most pronounced relative to changes in moderate and high wildfires. In some areas, along with decreased moderate and high wildfires, a significant increase in extreme wildfires is expected. Further studies should be associated both with RCM development, aimed at improving simulation of the wildfire atmospheric condition, and with enlarging the parameter set for wildfire analysis. Not only seasonal mean, but also monthly mean wildfire conditions should be studied, along with the use of statistical methods of model data interpretation to analyze intraseasonal and interannual variability of wildfire characteristics.     

Climate change estimates for the regions of Russia in the 20th century and in the beginning of the 21st century based on the observational data

Compared are the estimates or regional changes in temperature and precipitation on the territory of Russia for two methods of the spatial averaging of meteorological station data, one of which is adapted to the sparse observational network and takes account of the station weights proportional to the area of their influence. Considered are several variants of the zoning with the separation of the different number of regions. Formulated is a criterion of the zoning adequacy to the problem of the revelation and analysis of regional climate changes. Estimated is the representativeness of the network of observations of temperature and precipitation for separate regions. Presented are the estimates of regional trends of air temperature and precipitation for the century interval and for the recent decades obtained on the basis of the full archive of available data for the zoning attached to the administrative division of the Russian Federation into the federal districts.     

Assessment of Climate Change Impacts on the Economic Development of the Russian Arctic in the 21st Century

The problem of increasing the informativeness of climate projections in the Russian Arctic in order to meet the current economy needs is considered. The detailed estimates are presented of changes for the most important specialized indicators of the thermal and moisture regimes which characterize climatic impacts on the economic development of the Russian Arctic in the 21st century. The calculations are based on the data of numerical experiments with the regional climate model which were conducted for the Arctic region in the framework of the international CORDEX project. The high resolution of the model (50 km) and the consideration of mesoscale factors helped to detect significant spatial differences in the estimates of changes in the analyzed parameters which should be taken into account when adapting to climate change at the regional level.     

The taiga tick Ixodes persulcatus: Propagation under climate change conditions in the 21st century

The contemporary climatic habitat of the taiga tick, the dangerous carrier of tick-borne encephalitis and Lyme disease, is computed using the model. The expected climate changes will cause the reduction of the climatic habitat of Ixodes persulcatus in its western part and the expansion in the northern and eastern directions. By the late 21st century, this species can inhabit almost the whole north of the European part of Russia and the most part of Siberia up to 70° N. At the same time, I. persulcatus will disappear from Baltic countries, Belarus, the northern part of Ukraine, and the western areas of Russia. The RCP4.5 and RCP8.5 scenarios till 2040 suggest climate changes that will affect the location of climatic habitat approximately at the same scale. The differences will start being manifested in 2041–2060 and will become the most pronounced in the last 20 years of the 21st century. Expected climate changes will favor the significant expansion of the climatic habitat of the taiga tick in the 21st century and the potential formation of the zones of tick-borne encephalitis and Lyme disease in the regions, where these diseases are not currently observed.     

Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed.     

South African crop farming and climate change: An economic assessment of impacts

This paper assesses the economic impact of the expected adverse changes in the climate on crop farming in South Africa using a revised Ricardian model and data from farm household surveys, long-term climate data, major soils and runoffs. Mean annual estimates indicate that a 1% increase in temperature will lead to about US$ 80.00 increase in net crop revenue while a 1 mm/month fall in precipitation leads to US$ 2.00 fall, but with significant seasonal differences in impacts. There are also significant spatial differences and across the different farming systems. Using selected climate scenarios, the study predicts that crop net revenues are expected to fall by as much as 90% by 2100 with small-scale farmers been most affected. Policies therefore need to be fine-tuned and more focused to take advantage of the relative benefits across seasons, farming systems and spatially, and by so doing climate change may be beneficial rather than harmful.     

Model estimates of moistening conditions on the Russian plains by the middle of the 21st century

The spatiotemporal variations of long-term values of annual precipitation, annual radiation balance, and radiation index of dryness by the middle of the 21st century as compared with the last two decades of the 20th century were investigated using the results of numerical simulations based on the atmosphere-ocean general circulation models (AOGCMs). According to the model scenarios, the variations of moistening conditions follow the arid and arid-humid combined types. All models predict the significant moistening reduction in the south of European Russia by the middle of the 21st century. Studied is the reaction of boundaries of moistening zones in subboreal flat landscapes of Russia to the climate change. It is demonstrated that in spite of different directions of the spatial shift of moistening zone boundaries predicted by the climate models, these changes remain within the interannual selective variability.     

The MGO climate model for Siberia

Validation results of the MGO regional climate model (RCM) with 50-km resolution for Siberia are discussed. For the specification of side boundary conditions, the reanalysis data are used. It is shown that the model satisfactorily simulates the sea-level pressure and temperature fields for all seasons and the year as a whole. The lowest computational errors in the simulation of regional surface temperature arise in the fall and winter; in spring and summer, the temperature errors are slightly higher. The model slightly underestimates the variability of daily mean temperature in winter relative to the reanalysis data. In summer, on the contrary, the RCM-simulated variability exceeds the variability in reanalysis. In winter, the space distribution of model precipitation is in qualitative agreement with the data of observational analysis; in summer, the space variability of model precipitation is significantly higher than that of precipitation in the reanalysis, especially in the mountains. Agreement between time changes in precipitation and temperature anomalies in RCM and in the reanalysis is better in the areas with a relatively large number of weather stations. The model can be used for estimation of future climate changes in the above-mentioned region.     

Reducing Uncertainties in Climate Projections with Emergent Constraints:Concepts,Examples and Prospects

Models disagree on a significant number of responses to climate change,such as climate feedback,regional changes,or the strength of equilibrium climate sensitivity.Emergent constraints aim to reduce these uncertainties by finding links between the inter-model spread in an observable predictor and climate projections.In this paper,the concepts underlying this framework are recalled with an emphasis on the statistical inference used for narrowing uncertainties,and a review of emergent constraints found in the last two decades.Potential links between highlighted predictors are explored,especially those targeting uncertainty reductions in climate sensitivity,cloud feedback,and changes of the hydrological cycle.Yet the disagreement across emergent constraints suggests that the spread in climate sensitivity can not be significantly narrowed.This calls for weighting the realism of emergent constraints by quantifying the level of physical understanding explaining the relationship.This would also permit more efficient model evaluation and better targeted model development.In the context of the upcoming CMIP6 model intercomparison a growing number of new predictors and uncertainty reductions is expected,which call for robust statistical inferences that allow cross-validation of more likely estimates.