天气模式对年间作物产量变化的影响
Chris Knight1, Abdou Khouakhi1, Toby W Waine1
1Cranfield Environment Centre, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK.
The Science of the total environment
|October 24, 2024
概括
了解英国气象局的天气模式 (MO30) 是预测冬季小麦产量的关键. 特定的反旋风模式促进作物生长,而旋风模式带来风险,影响粮食安全.
科学领域:
- 农业科学 农业科学
- 气象学 天气学
- 气候科学 气候科学
背景情况:
- 年间作物产量的变化会影响粮食安全和经济稳定.
- 使用气象变量的现有作物产量模型可能无法完全捕捉极端天气影响.
- 整合天气模式可以更全面地了解环境对作物发展的影响.
研究的目的:
- 调查30个英国气象局天气模式 (MO30) 与英国冬季小麦产量限制 (1990-2020) 之间的关联.
- 评估天气模式对作物产量的复杂,区域和现象阶段特定影响.
- 探索将天气模式与作物模型相结合的潜力,以提高产量预测.
主要方法:
- 基于平均海平面压力的30个不同的英国气象局天气模式 (MO30) 的分析.
- 相关性分析 (斯皮尔曼) 确定特定天气模式与不同生长阶段和地区的冬季小麦产量之间的关系.
- 检查历史天气数据 (1990-2020年) 和作物产量数据.
主要成果:
- 阻塞的,负的北大西洋振荡 (NAO) 模式与作物产量低于最佳温度相关.
- 在播种,涌现, vernalisation, anthesis 和谷物填充期间的抗气旋天气模式显示出与良好的产量 (高达0.55) 有正相关性.
- 旋风模式在终端尖端阶段是有益的,而负相关性在结合和谷物填充期间是最强的.
结论:
- 天气模式显著影响冬季小麦产量,在各个生长阶段和地区都有明显的影响.
- 将天气模式分析与作物模拟模型相结合,可以提高产量预测的准确性和时间.
- 预计向更为旋风型的模式的转变可能会由于不利的温度和湿度条件而降低未来的小麦产量.
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