Climate variability in the Southern Hemisphere (SH) extratropical regions is dominated by the SH annular mode (SAM). Future changes in the SAM could have a large influence on the climate over broad regions. In this paper, the authors utilized model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to examine projected future changes in the SAM during the austral summer [December-February (DJF)]. To start off, first, the ability of the models in reproducing the recently observed spatial and temporal variability was assessed. The 12 CMIP5 models examined were found to reproduce the SAM's spatial pattern reasonably well in terms of both the symmetrical and the asymmetric component. The CMIP5 models show an improvement over phase 3 of CMIP (CMIP3) in simulating the seesaw structure of the SAM and also give improvements in the recently observed positive SAM trend. However, only half the models appeared to be able to capture two major recent decadal SAM phases. Then, the future SAM trends and its sensitivity to greenhouse gas (GHG) concentrations using simulations based on the representative concentration pathways 4.5 (RCP4.5) and 8.5 (RCP8.5) were explored. With RCP4.5, a very weak negative trend for this century is found. Conversely, with RCP8.5, a significant positive trend was projected, with a magnitude similar to the recently observed trend. Finally, model uncertainty in the future SAM projections was quantified by comparing projections from the individual CMIP5 models. The results imply the response of SH polar region stratospheric temperature to GHGs could be a significant controlling factor on the future evolution of the SAM.

No abstract

ENSO is the strongest interannual signal in the global climate system with worldwide climatic, ecological and societal impacts. Over the past decades, the research about ENSO prediction and predictability has attracted broad attention. With the development of coupled models, the improvement in initialization schemes and the progress in theoretical studies, ENSO has become the most predictable climate mode at the time scales from months to seasons. This paper reviews in detail the progress in ENSO predictions and predictability studies achieved in recent years. An emphasis is placed on two fundamental issues: the improvement in practical prediction skills and progress in the theoretical study of the intrinsic predictability limit. The former includes progress in the couple models, data assimilations, ensemble predictions and so on, and the latter focuses on efforts in the study of the optimal error growth and in the estimate of the intrinsic predictability limit.