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

IF 8.2 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Science of the Total Environment Pub Date : 2024-12-10 Epub Date: 2024-10-22 DOI:10.1016/j.scitotenv.2024.177181
Chris Knight, Abdou Khouakhi, Toby W Waine
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Abstract

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.

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天气模式对作物年际产量变化的影响。
作物产量的年际变化对全球粮食安全、经济稳定和环境可持续性具有重大影响。现有的作物产量预测模型主要使用气象变量,可能无法充分概括天气对作物生长过程的全面影响,如复合或极端事件。将天气模式纳入作物模型可以更全面地了解影响作物生长的环境条件,从而更准确、更早地预测产量。我们的研究以平均海平面气压为基础,研究了英国气象局的 30 种不同天气模式(MO30)。我们调查了它们与限制英国冬小麦产量的天气条件的关联(1990-2020 年)。受阻的负北大西洋涛动(NAO)模式导致气温低于作物最佳产量的风险最高。然而,天气模式与产量之间的联系十分复杂,在区域范围内,甚至在生长周期的哪个阶段,都会产生不同的影响。研究发现,播种、出苗、春化、开花和籽粒灌浆期间的反气旋天气模式与作物丰产有一定关系,单一天气模式(英格兰东南部春化期间的 WP3)的斯皮尔曼相关系数高达 0.55,而气旋模式则有助于小穗末期的物候期。播种、出苗和春化期的正相关性最强,而开花期和籽粒灌浆期的负相关性最大。这表明,将天气模式与现有作物模拟模型相结合,可以更早、更准确地预测产量。这将有助于制定有效的作物管理和气候减缓战略,对加强粮食安全至关重要。预计 21 世纪晚期天气模式的变化可能会降低作物产量。这是由于气旋天气模式增多,在小麦春化阶段带来更温暖、更潮湿的条件,随后在开花和籽粒饱满阶段带来更温暖、更干燥的条件。
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来源期刊
Science of the Total Environment
Science of the Total Environment 环境科学-环境科学
CiteScore
17.60
自引率
10.20%
发文量
8726
审稿时长
2.4 months
期刊介绍: The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere. The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.
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