Abstract
Assessing the performance of climate models in surface air temperature (SAT) simulation and projection have received increasing attention during the recent decades. This paper assesses the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulating intra-annual, annual and decadal temperature over Northern Eurasia from 1901 to 2005. We evaluate the skill of different multi-model ensemble techniques and use the best technique to project the future SAT changes under different emission scenarios. The results show that most of the general circulation models (GCMs) overestimate the annual mean SAT in Northern Eurasia and the difference between the observation and the simulations primarily comes from the winter season. Most of the GCMs can approximately capture the decadal SAT trend; however, the accuracy of annual SAT simulation is relatively low. The correlation coefficient R between each GCM simulation and the annual observation is in the range of 0.20 to 0.56. The Taylor diagram shows that the ensemble results generated by the simple model averaging (SMA), reliability ensemble averaging (REA) and Bayesian model averaging (BMA) methods are superior to any single GCM output; and the decadal SAT change generated by SMA, REA and BMA are almost identical during 1901–2005. Heuristically, the uncertainty of BMA simulation is the smallest among the three multi-model ensemble simulations. The future SAT projection generated by the BMA shows that the SAT in Northern Eurasia will increase in the 21st century by around 1.03 °C/100 yr, 3.11 °C/100 yr and 7.14 °C/100 yr under the RCP 2.6, RCP 4.5 and RCP 8.5 scenarios, respectively; and the warming accelerates with the increasing latitude. In addition, the spring season contributes most to the decadal warming occurring under the RCP 2.6 and RCP 4.5 scenarios, while the winter season contributes most to the decadal warming occurring under the RCP 8.5 scenario. Generally, the uncertainty of the SAT projections increases with time in the 21st century.
Highlights
The future surface air temperature (SAT) projection generated by the Bayesian model averaging (BMA) shows that the SAT in Northern Eurasia will increase in the 21st century by around 1.03 °C/100 yr, 3.11 °C/100 yr and 7.14 °C/100 yr under the representative concentration pathways (RCPs) 2.6, RCP 4.5 and RCP 8.5 scenarios, respectively; and the warming accelerates with the increasing latitude
There is an interesting phenomenon in Northern Eurasia found by Bulygina et al (2011) that most areas of Northern Eurasia have experienced an increase in both winter average and maximum snow depths in recent decades, which is against the background of global temperature rise and sea ice reduction in the northern hemisphere
This study evaluates and compares the SAT change over Northern Eurasia using the outputs from the general circulation models (GCMs), simple model averaging (SMA), reliability ensemble averaging (REA) and BMA, and projects the future SAT trend for different emission scenarios
Summary
There is an interesting phenomenon in Northern Eurasia found by Bulygina et al (2011) that most areas of Northern Eurasia have experienced an increase in both winter average and maximum snow depths in recent decades, which is against the background of global temperature rise and sea ice reduction in the northern hemisphere. Climate projections and their associated applications have become an important topic during recent decades. By using GCMs, we can simulate the present-day and project future climatic changes under different scenarios and separate natural climate variability from anthropogenic effects
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