The accuracy of computer simulations in reproducing crop failure events that have occurred across the globe suggests that seasonal forecasts can be useful for monitoring global food production, reports a paper published in Nature Climate Change this week.
Toshichika Iizumi and colleagues linked ensemble seasonal climate forecasts with statistical crop models to assess how well the models reproduce crop failures for the major global crops: wheat, soybean, maize and rice. They found that yield loss over a substantial proportion (26-33%) of the harvested area was predictable if climatic forecasts were sufficiently accurate. However, the reliability of yield estimates varied significantly by crop, with rice and wheat yields being the most predictable.
Although the proportion of harvest area that was reliably predicted may not seem high, there is sufficient predictability of crop failure to aid in the monitoring of global food production and provide insight into potential price volatility. Such information can also support the adaptation of food systems to climatic extremes.