The relationships between crop productivity and climate variability drivers are often assumed to be stationary over time. However, this may not be true in a warming climate. Here we use a crop model and a machine learning algorithm to demonstrate the changing impacts of climate drivers on wheat productivity in Australia. We find that, from the end of the nineteenth century to the 1980s, wheat productivity was mainly subject to the impacts of the El Nino Southern Oscillation. Since the 1990s, the impacts from the El Nino Southern Oscillation have been decreasing, but those from the Indian Ocean Dipole have been increasing. The warming climate has brought more occurrences of positive Indian Ocean Dipole events, resulting in severe yield reductions in recent decades. Our findings highlight the need to adapt seasonal forecasting to the changing impacts of climate variability to inform the management of climate-induced yield losses.
Simulated annual wheat yields during 1889-2020 show that, since the 1990s, Indian Ocean Dipole has replaced El Nino Southern Oscillation as the dominant climate driver across most of the Australian wheatbelt. The occurrences of more positive Indian Ocean Dipole events in recent decades resulted in severe yield reductions.