Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.
Andrej Ceglar1, Andrea Toreti2, Chloe Prodhomme3
1European Commission, Joint Research Centre, via Enrico Fermi 2749, 21027, Ispra, Italy. andrej.ceglar@ec.europa.eu.
Scientific Reports
|January 24, 2018
Summary
Predicting European maize yield is improved using a combined stress index (CSI) that accounts for drought and heat. Land-surface initialized seasonal climate forecasts enhance prediction accuracy for this vital crop.
Area of Science:
- Agricultural Science
- Climate Science
- Environmental Science
Background:
- Seasonal crop yield forecasting is crucial for market stability, mitigating socio-economic impacts of crop losses, and ensuring food security.
- Climate variability and extreme weather significantly influence agricultural production, necessitating early prediction for adaptation.
- Current seasonal climate forecasts have limited utility in Europe for agricultural decisions due to poor surface variable prediction skill.
Purpose of the Study:
- To develop and validate a combined stress index (CSI) for predicting European maize yield.
- To assess the utility of land-surface initialized seasonal climate forecasts for maize yield prediction in Europe.
Main Methods:
- Developed a combined stress index (CSI) integrating drought and heat stress during summer.
- Utilized observed climate data to evaluate the CSI's ability to explain inter-annual maize yield variability.
- Employed land-surface initialized seasonal climate forecasts and compared their skill against climatological initializations for predicting the CSI.
Main Results:
- The CSI explained approximately 53% of the inter-annual maize yield variability under observed climate conditions.
- The CSI effectively highlighted the impact of concurrent heat and drought events on recent maize yield anomalies.
- Land-surface initialized seasonal climate forecasts demonstrated improved, marginally useful skill in predicting the CSI over climatological initialization in several European regions.
Conclusions:
- A combined stress index (CSI) offers a valuable tool for predicting European maize yield by integrating drought and heat stress.
- Land-surface initialization significantly enhances the skill of seasonal climate forecasts for predicting maize yield in key European agricultural areas.
- Improved seasonal climate forecasting holds potential for better agricultural decision-making and adaptation strategies in Europe.
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