Food scarcity under a growing world population is a pressing problem, especially amplified by increased yield variability due to climate change and stagnation of yield increase. Spatiotemporal variability on a small sub-country scale is rarely addressed in the literature so far, as well as the influences of climatic compound events (multiple extreme events occurring together) which are therefore the subject matter of this study.
To identify spatial differences in variability and stagnation, the time series of grain maize and winter wheat in the 96 counties of Bavaria since 1983 were decomposed into their trend and noise. The trend shows when the yields stagnate, while the noise reveals their variability. To spatially grasp the variability of yields, additionally, the trend-free Sharpe ratio was calculated which increases with lower yield variability.
The trend-free Sharpe ratio of grain maize raises towards the south of Bavaria showing that the yields are more stable there. Also, the variability of the decomposed time series is lower in southern counties. Winter wheat has more stable yields with a mean trend-free Sharpe ratio of 12.1 compared to 10.0 for grain maize and shows no north-south gradient. The frequency of climatic compound events (drought plus heatwaves) increased since 1983, falling together with years of yield collapse. They also occur rather in the dry north of Bavaria, potentially explaining the higher yield variability of maize there.
The results of this study can be used by farmers to choose the most fitting crops in their counties to adapt to the impacts of climatic compound events, especially focusing more on yield stability instead of high mean yields.