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Narrowing the surface temperature range in CMIP5 simulations over the Arctic

Hao, Mingju, Huang, Jianbin, Luo, Yong, Chen, Xin, Lin, Yanluan, Zhao, Zongci, Xu, Ying
Theoretical and applied climatology 2018 v.132 no.3-4 pp. 1073-1088
General Circulation Models, correlation, data collection, emissions, surface temperature, uncertainty, Arctic region
Much uncertainty exists in reproducing Arctic temperature using different general circulation models (GCMs). Therefore, evaluating the performance of GCMs in reproducing Arctic temperature is critically important. In our study, 32 GCMs in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) during the period 1900–2005 are used, and several metrics, i.e., bias, correlation coefficient (R), and root mean square error (RMSE), are applied. The Cowtan data set is adopted as the reference data. The results suggest that the GCMs used can reasonably reproduce the Arctic warming trend during the period 1900–2005, as observed in the observational data, whereas a large variation of inter-model differences exists in modeling the Arctic warming magnitude. With respect to the reference data, most GCMs have large cold biases, whereas others have weak warm biases. Additionally, based on statistical thresholds, the models MIROC-ESM, CSIRO-Mk3-6-0, HadGEM2-AO, and MIROC-ESM-CHEM (bias ≤ ±0.10 °C, R ≥ 0.50, and RMSE ≤ 0.60 °C) are identified as well-performing GCMs. The ensemble of the four best-performing GCMs (ES4), with bias, R, and RMSE values of −0.03 °C, 0.72, and 0.39 °C, respectively, performs better than the ensemble with all 32 members, with bias, R, and RMSE values of −0.04 °C, 0.64, and 0.43 °C, respectively. Finally, ES4 is used to produce projections for the next century under the scenarios of RCP2.6, RCP4.5, and RCP8.0. The uncertainty in the projected temperature is greater in the higher emissions scenarios. Additionally, the projected temperature in the cold half year has larger variations than that in the warm half year.