Eun-Pa Lim: Ozone – an untapped source of subseasonal to seasonal forecast predictability
Ozone is an important atmospheric constituent that absorbs solar ultraviolet radiation in the stratosphere, thereby warming the stratosphere and protecting the biosphere from harmful ultraviolet exposure. The variability and long-term changes of Antarctic stratospheric ozone are influenced not only by ozone-depleting substances such as chlorofluorocarbons and bromine compounds, but also by the variability and long-term changes of Antarctic stratospheric circulation and temperature. In turn, ozone anomalies can feed back on stratospheric temperature and circulation anomalies, with important implications for stratosphere–troposphere coupling.
Despite this, the role of ozone in driving interannual variability and enhancing predictability of tropospheric circulation and surface climate has generally been regarded as of secondary importance. For instance, many current subseasonal-to-seasonal (S2S) forecast systems do not directly incorporate observed ozone information because of the complexity and computational cost of realistically simulating ozone–radiation–dynamics interactions. However, recent studies have shown that ozone plays an important role in Southern Hemisphere circulation variability and associated rainfall, particularly over Australia, providing additional predictability. In this presentation, we review recent case studies linking Australian surface climate forecast busts to unrealistic ozone configurations in the Bureau of Meteorology’s dynamical S2S forecast system, ACCESS-S2, and use these examples to motivate discussion on how machine-learning approaches might help diagnose and reduce ozone-related forecast biases.