Assessment of CMIP5 climate models and projected temperature changes over Northern Eurasia

By Chiyuan Miao, Qingyun Duan, Qiaohong Sun, Yong Huang, Dongxian Kong, Tiantian Yang, Aizhong Ye, Zhenhua Di, Wei Gong. 2014

215 citations recorded by the source corpus.

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.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a526215439d95cd5c949b7577487b22b65bdf947

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Qingyun Duan
2. Renate A. I. Wilcke

In Global and Planetary Change

1. Qiaohong Sun
2. Qingyun Duan
3. Renate A. I. Wilcke
4. Martin Schroeder
5. Chiyuan Miao

Citations in the corpus

• A nonstationary bias‐correction technique to remove bias in GCM simulations (2016, background): “In CMIP5, the internal variability is roughly constant through time and the other uncertainties increase with time, but at different rates [Intergovernmental Panel on Climate Change, 2013; Miao et al., 2014].”
• Ips typographus and Dendroctonus ponderosae Models Project Thermal Suitability for Intra- and Inter-Continental Establishment in a Changing Climate (2019, background): “We acknowledge that climate projections are uncertain, and that GCMs may overestimate mean annual temperature (Miao et al., 2014).”