Respected readers, authors and reviewers, you can add comments to this page on any questions about the contribution, review, editing and publication of this journal. We will give you an answer as soon as possible. Thank you for your support!
Huang Chuanjiang, Qiao Fangli, Song Yajuan, Li Xinfang. The simulation and forecast of SST in the South China Sea by CMIP5 models[J]. Haiyang Xuebao, 2014, 36(1): 38-47. doi: 10.3969/j.issn.0253-4193.2014.01.005
Citation:
Huang Chuanjiang, Qiao Fangli, Song Yajuan, Li Xinfang. The simulation and forecast of SST in the South China Sea by CMIP5 models[J]. Haiyang Xuebao, 2014, 36(1): 38-47. doi: 10.3969/j.issn.0253-4193.2014.01.005
Huang Chuanjiang, Qiao Fangli, Song Yajuan, Li Xinfang. The simulation and forecast of SST in the South China Sea by CMIP5 models[J]. Haiyang Xuebao, 2014, 36(1): 38-47. doi: 10.3969/j.issn.0253-4193.2014.01.005
Citation:
Huang Chuanjiang, Qiao Fangli, Song Yajuan, Li Xinfang. The simulation and forecast of SST in the South China Sea by CMIP5 models[J]. Haiyang Xuebao, 2014, 36(1): 38-47. doi: 10.3969/j.issn.0253-4193.2014.01.005
First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Key Laboratory of Marine Science and Numerical Modeling, State Oceanic Administration, Qingdao 266061, China
2.
First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
The simulation abilities of 32 CMIP5 (Coupled Model Intercomparison Project Phase 5) climate models to the historical sea surface temperature (SST) in the South China Sea are evaluated by verifying its long-term linear trend and standard deviation. The projections of the SST for the 21st century under different RCP (Representative Concentration Pathway) emission scenarios are analyzed. The results show that most of the models can well reproduce the primary characteristic and change of the historical SST in the South China Sea. However,the simulations of the historical SST are unsatisfactory for 15 climate models. These models are excluded in evaluating the RCP forecasts for minimizing the uncertainty of the forecast results,while their effects to the multi-model ensemble mean are not so significant. Other models show that the SST in the South China Sea will be significant warming in the 21st century,whose linear trends of the multi-model ensemble mean are 0.42,1.50 and 3.30℃/(100 a) under RCP26,RCP45,and RCP85 scenarios,respectively. The changes of these trends are relatively small in space,but not with time. The warming in the early 21st century is significantly stronger than that in the late 21st century under RCP26 and RCP45scenarios,while the opposite under RCP85 scenario.
Taylor K E, Stouffer R J, Meehl G A. An overview of CMIP5 and the experiment design[J]. Bull Amer Meteorol Soc, 2012, 93:485—498, doi: 10.1175/BAMS-D-11-00094.1.
Rayner N A, ParkerD E, Horton E B, et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century[J]. J Geophys Res, 2003, 108(D14), 4407, doi: 10.1029/2002JD002670.
Wu Z, Huang N E, Wallace J M, et al. On the time-varying trend in global-mean surface temperature[J].Clim Dyn, 2011, 37:759—773.
Moss R H, EdmondsJ A, HibbardK A, et al. The next generation of scenarios for climate change research and assessment[J]. Nature, 2010, 463:747—756, doi: 10.1038/nature08823.
Huang Chuanjiang, Qiao Fangli, Song Yajuan, Li Xinfang. The simulation and forecast of SST in the South China Sea by CMIP5 models[J]. Haiyang Xuebao, 2014, 36(1): 38-47. doi: 10.3969/j.issn.0253-4193.2014.01.005
Huang Chuanjiang, Qiao Fangli, Song Yajuan, Li Xinfang. The simulation and forecast of SST in the South China Sea by CMIP5 models[J]. Haiyang Xuebao, 2014, 36(1): 38-47. doi: 10.3969/j.issn.0253-4193.2014.01.005