Uncertainties of the global-to-regional temperature and precipitation simulations in CMIP5 models for past and future 100 years
- 310 Downloads
Global-to-regional surface temperature and precipitation trends are examined based on the CMIP5 model 100 years of historical simulations and another future 100 years following the Representative Concentration Pathway (RCP) emission scenario projection. Different from the ensemble mean approach in the previous studies, the probabilistic multimodal ensemble prediction with Gaussian fitting is used to generate probabilistic simulations. The results show that the averaged precipitation increases slightly with global warming, but the response is not globally uniform. Both historical model simulations and the RCP emission scenario projections suffer from large uncertainties in the selected models and the geographic distribution. The spatial distribution of spreads among the multimodal scenario projections is similar to that in the historical simulations, except the magnitude of spread sharply increases and the region expands equatorward and poleward in surface temperature and precipitation, respectively.
KeywordsEmission Scenario CMIP5 Model Representative Concentration Pathway Precipitation Trend Historical Simulation
The surface temperature data for HadCRUT4 is created by the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia and the new GISS analysis dataset is developed by the National Aeronautics and Space Administration’s (NASA) Goddard Institute for Space Studies (GISS). The Program for Climate Model Diagnosis and Intercomparison (PCMDI) collected and archived the model data. In addition, the first author was partially supported by a key program of the National Natural Science Foundation of China (Grant 41230528, 41305039) and the priority Academic program development (PAPD) of Jiangsu Higher Education. The authors would like to thank these agencies for providing the data and funding support.
This work was supported by the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), Center for Satellite Applications and Research (STAR). The views, opinions, and findings contained in this publication are those of the authors and should not be considered an official NOAA or US Government position, policy, or decision.
- Christensen, J. H., et al. 2007: Regional climate projections. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, pp, 847–940Google Scholar
- Intergovernmental Panel on Climate Change (2013) Climate Change 2013: the physical science basis, summary for policy makers. WG1 contribution to IPCC AR5, 27 September 2013, 36 ppGoogle Scholar
- Jones P. D., D.H. Lister, T.J. Osborn, C. Harpham, M. Salmon, and C.P. Morice, 2012.“Hemispheric and large-scale land-surface air temperature variations: An extensive revision and an update to 2010′′, Journal of Geophysical Research, vol. 117. doi: 10.1029/2011JD017139
- Santer BD, Painter J, Mears C, Doutriaux C, Caldwell P, Arblaster JM, Cameron-Smith P, Gillett NP, Gleckler PJ, Lanzante JR, Perlwitz J, Solomon S, Stott PA, Taylor KE, Terray L, Thorne PW, Wehner MF, Wentz FJ, Wigley TML, Wilcox L, Zoun C-Z (2013) Identifying human influences on atmospheric temperature. Proc Natl Acad Sci U S A 110:26–33. doi: 10.1073/pnas.1210514109 CrossRefGoogle Scholar