CLIMATE CHANGE PROJECTIONS AND IMPACTS IN RUSSIAN FEDERATION AND CENTRAL ASIA STATES
Lead Author: Vladimir Kattsov
Contributing Authors: Veronika Govorkova, Valentin Meleshko, Tatyana Pavlova, Igor ShkolnikContents
2. Constructing climate change scenarios for RF and CAS
2.1 Regions under consideration and specific features of their climates
2.2 State-of-the-art climate models
2.3 Climatological baseline and time slices for the 21st century
2.4 Sources of projection uncertaintiesf
3. RF/CAS climate change projections for the 21st century
3.1 Surface air temperaturef
3.4 Sea level pressure and wind
4. Concluding remarks
Increased levels of atmospheric greenhouse gases (GHG) will have a larger effect on climate in Northern Eurasia, particularly in its arctic and subarctic regions, than in most of other regions of the Earth. To estimate a possible future climate change over the territories of Russian Federation (RF) and five Central Asian States (CAS: Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) ensembles of up to 16 comprehensive global (coupled atmosphere-ocean) climate models are used in this Assessment. Additional estimates are obtained using a regional climate model customized to two major domains in the Northern Eurasia. Future concentrations of GHG and aerosol emissions can be estimated assuming demographic, socio-economic and technological changes through the 21st century. Within IPCC, a set of emission scenarios has been prepared; in this Assessment so called A2, A1B, and B1 scenarios are considered. These are, correspondingly in the upper, middle and lower parts of the range of scenarios provided by the IPCC.
Projections with the global models provide a physically consistent quantitative picture of climate change through the 21st century. The projected changes in RF and CAS in many cases continue the tendencies already observed, while increase of their rates as well as inter-scenario differences are accelerating by the end of the 21st century. Relative to the base line climate (1980-1999), the area averaged annual mean warming for the RF and CAS by 2011-2030 is 1.0-1.2ºC. By the end of the 21st century, the increase of the area averaged annual mean temperature varies from 3.0±1.0ºC (B1) to 5.5±1.2ºC (A2) for RF, and from 2.6±0.7ºC (B1) to 4.7±0.9ºC (A2) for CAS. Area averaged winter warming is stronger in RF (from 3.8±1.3ºC (B1) to 7.2±1.5ºC (A2)), than in CAS (from 2.7±1.0ºC (B1) to 4.6±1.0ºC (A2)). In summer, on the contrary, CAS territory warms stronger (from 2.8±0.6ºC (B1) to 5.0±1.0ºC (A2)), than RF (2.3±0.9ºC (B1) to 4.2±1.3ºC (A2)).
The warming is accompanied by decreases in yearly number of frost days (with surface air temperature below 0ºC), in duration of extremely low winter temperatures, and in annual ranges of extreme temperatures. E.g., by mid-21st century in Central and East Siberia the decrease of the number of the frost days is 10-15 days, in European RF, Kazakhstan, Turkmenistan and Uzbekistan – 15-30 days, in Kyrgyzstan and Tajikistan, as well as Baltic region, – 30-35 days. An increase is projected in duration of summer temperature high extremes. The most severe heat waves are projected to occur in West Siberia and CAS.
Over the territories of both RF and CAS, the increase of winter precipitation is a robust feature of projections for all scenarios. In summer, however, the increase is projected only in the northern and eastern parts of RF, while South-West of RF and CAS demonstrate a decrease in precipitation and thus an increase in drought risk. By the end of the 21st century, over the territory of RF, the increase of the area averaged annual mean precipitation varies from 11.3±3.1% (B1) to 17.7±3.7% (A2). For CAS, projected annual mean changes usually do not exceed the intermodel standard deviation, with a few exclusions for the territory of Kazakhstan. In many regions along with decreasing mean precipitation an increase in very intensive precipitation is projected. However, credibility of precipitation projections is estimated to be lower than that of the temperature.
Runoff is projected to increase over the catchments of Siberian rivers, while over the southern watersheds runoff will decrease both due to precipitation decrease and evaporation increase in the warm season. Over the European RF the terrestrial snow cover is projected to decrease, while in Siberia, where the solid precipitation dominates, the snow mass accumulated during the cold season will be increasing. As a result, winter runoff is expected to increase in European RF. In Asian Russia, the combination of the increase of the snow mass accumulated during the winter and acceleration of its melting in spring results in increasing risks of flooding.
Degradation of permafrost in the warming climate will manifest itself in increasing seasonally thawing depths, and shifting northward the boundary between seasonal thawing and seasonal freezing of the grounds. Arctic sea ice is projected to be shrinking through the 21st century, with a faster disappearing old, multi-year ice. In A2 scenario, in late 21st century, some models project entire disappearance of sea ice in the Northern hemisphere by the end of summer.
RF/CAS territory is characterized by complex and still insufficiently understood climate processes and feedbacks, contributing to the challenge, which the region poses from the viewpoint of climate modelling. Local and regional climate features, such as enhanced precipitation or winds close to steep mountains, are not well represented in global climate models due to their limited horizontal resolution. Physically based methods for local and regional climate simulation rely on high resolution models run over limited time slices. Such methods can be used to interpret global simulations on finer scales and capture areas with intensified precipitation, extreme wind events etc. Unfortunately, only very limited high-resolution regional model results for the RF/CAS territory have been available for this Assessment.
Natural variability in the region under consideration is large and could mask or amplify a change due to human activities. This effect could be larger or smaller depending on the region, the climate parameter (temperature, precipitation, snow cover, etc.) and the time and space scales. To assess the relative importance of natural variability versus a prescribed climate forcing massive ensembles of differently formulated climate models run from an ensemble of initial conditions should be used. This technique requires substantial computing resources. Massive ensembles containing on the order of hundred simulations would give a better estimate of climate change probability distributions, including changes in the frequency of winter storms, temperature extremes, etc.