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Climate Dynamics

, Volume 52, Issue 5–6, pp 2597–2612 | Cite as

Simulating evaluation and projection of the climate zones over China by CMIP5 models

  • Wen-ping HeEmail author
  • Shan-shan Zhao
  • Qiong Wu
  • Yun-di Jiang
  • Shiquan Wan
Article
  • 101 Downloads

Abstract

On the basis of climate zones classified by the number of days of the daily average temperature ≥ 10 °C (DT10) over China, the performance of the 9 CMIP5 climate models is evaluated in this paper. The results indicate that the CMCC-CMS and MPI-ESM-MR show higher skill than the other 7 models in simulating spatial pattern and its decadal change of climate zones over China. The simulation results for FGOALS-g2 and INM-CM4 both show relatively lower skill than the other 7 models. Meanwhile, the performance of multi-model ensemble in simulating climate zones over China is obviously better than the simulated result of any single model. So, it is a good way to simulate climate zones by multi-model ensemble to reduce some uncertainty of climate models. However, it is crucial to select appropriate ensemble members. Compared with 1960–2005, the climatic zones in China have an obvious trend of northward shift in 2021–2100. The range of southern sub-tropical belt expands to the most areas in the south of Yangtze River under RCP4.5 emission scenarios, and further extends to the north areas of Yangtze River with a maximum of 2–6° of latitude under RCP8.5 emission scenarios. Middle sub-tropical belt shifts gradually to the areas between Yellow River and north areas of the middle and lower reaches of the Yangtze River. Northern sub-tropical belt shifts northward to southeastern North China. Warm extra-tropical belt extends to the most of Northeast China, most of central Inner Mongolia, and northern Xinjiang under RCP8.5 emission scenarios.

Keywords

Climate zone CMIP5 Evaluation of climate model Projection DT10 

Notes

Acknowledgements

The authors would like to thank the anonymous reviewers and editors for the beneficial and helpful suggestions for this manuscript, and Wen Zhang for beneficial discussion. This research was jointly supported by National Natural Science Foundation of China (Grant Nos. 41775092, 41605069, 41475073, 41530531, and 41475064).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.National Climate CenterChina Meteorological AdministrationBeijingChina
  2. 2.Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Sciences and TechnologyNanjingChina
  3. 3.LAGEO, Institute of Atmosphere PhysicsChinese Academy of ScienceBeijingChina
  4. 4.Yangzhou Meteorological Bureau of Jiangsu ProvinceYangzhouChina

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