Drivers of Southern Hemisphere climate change

• Main Author: Arblaster, Julie Michelle
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: 2013
• Subjects: climate variability; ozone hole; climate change; global climate models; extreme events; Austral; Southern Ocean
• Online Access: http://hdl.handle.net/11343/38243

© 2013 Dr. Julie Michelle Arblaster The climate of the Southern Hemisphere (SH) has undergone significant changes over recent decades, with additional warming expected under future emission scenarios. However, while temperature increases are robust across models there is more uncertainty around changes in rainfall, atmospheric circulation and extremes, all of which have a large impact on human society and ecosystems. The objective of this thesis was to increase our confidence in future projections by considering the relative importance of various drivers of past and future climate change, with a focus on the Southern Hemisphere. These drivers include sea surface temperatures (SSTs; which may or may not be anthropogenically forced), greenhouse gases and stratospheric ozone. To achieve this objective a hierarchy of model experiments were utilised, from idealised experiments to multimodel datasets. Insights were gained by exploring both the consistencies and the spread across the model results. The main results were: 1) The internal variability of the climate system, such as the El Niño-Southern Oscillation (ENSO), impacts the emerging signals of anthropogenic climate change and characterisations of this noise were explored. Opposite phases of ENSO were found to drive marked contrasts in maximum temperature extremes, with ENSO fidelity crucial in simulating the observed relationships. These patterns are unlikely to change substantially under future climate change. Over the Australian continent, future warming leads to increases in warm temperature extremes and a propensity for longer dry spells interspersed with heavy rainfall events. In general, the magnitude of changes in both temperature and precipitation extremes indices scaled with the strength of emissions. 2) Coupled model simulations were able to reproduce the large-scale features of SH climate trends since 1950, if observed changes in anthropogenic forcings were included. However, atmospheric models driven by observed SSTs and anthropogenic forcings were unable to capture wintertime trends, suggesting either deficiencies in the modelling framework, SSTs or models themselves or that internal variability has been largely responsible for these trends. The improvement of the simulated trends in experiments with partial coupling suggests the modelling framework plays some role in this deficiency. 3) Future changes in the SH atmospheric circulation will be driven by the competing effects of greenhouse gases and stratospheric ozone recovery. Climate sensitivity was found to largely explain the difference in Southern Annular Mode (SAM) projections between two coupled climate models under identical greenhouse gas and stratospheric ozone forcing. This result extended to multimodel simulations under transient carbon dioxide (CO2) conditions in all seasons, with the stronger the warming the larger the trend in the SAM. Tropical upper tropospheric warming was found to be more relevant than polar stratospheric cooling to the model spread in SAM responses to CO2. 4) Idealised SST experiments in two models showed a consistent poleward shift of the SH wintertime westerly jet under Southern Ocean cooling. However, the austral winter response to increased tropical SSTs was found to be model dependent, with opposite latitudinal shifts in the SH westerly jet in the two models. This finding was linked to different tropical rainfall and convective atmospheric heating responses in the models to identical SST increases. These results highlight the reliability of current climate model simulations as well as some of their limitations. Potential deficiencies in forcing datasets, modelling frameworks and the simulation of internal variability were identified. Understanding and improving these deficiencies is crucial for interpreting recent observed change and understanding future projections, particularly at the regional scale.