The impact of weather patterns on inter-annual crop yield variability

Inter-annual variations in crop production have significant implications for global food security, economic stability, and environmental sustainability. Existing crop yield prediction models primarily using meteorological variables may not adequately encapsulate the full breadth of weather influence...

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Veröffentlicht in:The Science of the total environment 2024-12, Vol.955, p.177181, Article 177181
Hauptverfasser: Knight, Chris, Khouakhi, Abdou, Waine, Toby W.
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description Inter-annual variations in crop production have significant implications for global food security, economic stability, and environmental sustainability. Existing crop yield prediction models primarily using meteorological variables may not adequately encapsulate the full breadth of weather influences on crop development processes, such as compound or extreme events. Incorporating weather patterns into crop models could provide a more comprehensive understanding of the environmental conditions affecting growth, enabling more accurate and earlier yield predictions. Our study examines 30 distinct UK Met Office weather patterns (MO30) based on mean sea level pressure. We investigate their association with weather conditions that limit winter wheat yield in the UK (1990–2020). Blocked, negative North Atlantic Oscillation (NAO) patterns create the highest risk of temperatures that are below optimal for crop yield. However, the connection between weather patterns and yield is complex, with differing effects at a regional scale and even at which point in the growth cycle they appear. It was found that anticyclonic weather patterns during sowing, emergence, vernalisation, anthesis, and grain filling exhibit a relationship with good crop yields with a Spearman correlation coefficient of up to 0.55 for a single weather pattern (WP3 during vernalisation in South East England), whilst cyclonic patterns can help during the terminal spikelet phenological phase. The strongest positive correlations were during sowing, emergence, and vernalisation, whilst the largest negatives were observed in anthesis and grain filling. The potential of combining weather patterns with existing crop simulation models to produce earlier and more accurate yield predictions is shown. This would enable effective crop management and climate mitigation strategies, critical to strengthening food security. Projected changes in weather pattern occurrences in the late 21st century will likely reduce crop yields. This is due to increased cyclonic weather patterns, which bring warmer, wetter conditions during the wheat's vernalisation stage, followed by warmer, drier conditions during the anthesis and grain-filling phases. [Display omitted] •Weather patterns exhibit a complex relationship with interannual variations in UK Winter Wheat yields.•Northern UK shows differing relationship between weather patterns and yield compared to East and Southeast England.•Future predicted weather pattern changes sugge
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It was found that anticyclonic weather patterns during sowing, emergence, vernalisation, anthesis, and grain filling exhibit a relationship with good crop yields with a Spearman correlation coefficient of up to 0.55 for a single weather pattern (WP3 during vernalisation in South East England), whilst cyclonic patterns can help during the terminal spikelet phenological phase. The strongest positive correlations were during sowing, emergence, and vernalisation, whilst the largest negatives were observed in anthesis and grain filling. The potential of combining weather patterns with existing crop simulation models to produce earlier and more accurate yield predictions is shown. This would enable effective crop management and climate mitigation strategies, critical to strengthening food security. Projected changes in weather pattern occurrences in the late 21st century will likely reduce crop yields. 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It was found that anticyclonic weather patterns during sowing, emergence, vernalisation, anthesis, and grain filling exhibit a relationship with good crop yields with a Spearman correlation coefficient of up to 0.55 for a single weather pattern (WP3 during vernalisation in South East England), whilst cyclonic patterns can help during the terminal spikelet phenological phase. The strongest positive correlations were during sowing, emergence, and vernalisation, whilst the largest negatives were observed in anthesis and grain filling. The potential of combining weather patterns with existing crop simulation models to produce earlier and more accurate yield predictions is shown. This would enable effective crop management and climate mitigation strategies, critical to strengthening food security. Projected changes in weather pattern occurrences in the late 21st century will likely reduce crop yields. 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subjects Climate Change
Climate change resilience
Crop Production - methods
Crops, Agricultural - growth & development
Prediction
Seasons
Sustainability
Triticum - growth & development
United Kingdom
Weather
Weather patterns
Wheat
Yield
title The impact of weather patterns on inter-annual crop yield variability
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