预测10天前印度的最高气温,使用机器学习模型
J V Ratnam1, Swadhin K Behera2, Masami Nonaka2
1Application Laboratory, VAIG, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-Ku, Yokohama, Kanagawa, 236-0001, Japan. jvratnam@jamstec.go.jp.
Scientific reports
|October 11, 2023
概括
机器学习模型有效地预测了印度4月和5月的每日最大温度异常,超过了持久性和复杂气候模型的匹配. 这些人工智能工具为热浪预测提供了有希望的进步.
科学领域:
- 气象学 天气学
- 气候科学 气候科学
- 人工智能的人工智能
背景情况:
- 由于白天高温 (Tmax),印度在3月至6月期间面临严重的热浪风险.
- 准确预测Tmax异常对于减轻热浪影响至关重要.
研究的目的:
- 评估机器学习模型,预测印度的每日Tmax异常提前10天.
- 为此预测任务确定最佳的机器学习模型.
主要方法:
- 评估了10种不同的机器学习模型.
- 确定了AdaBoost回归器与多层感知器作为最佳模型.
- 基准预测与持久性和气候预测系统 (CFS) 的预测对比.
主要成果:
- 最优的机器学习模型显示出更高的技能而不是坚持性,并且与4月和5月的CFS预测可比.
- 模型的性能在3月和6月受到限制,表现类似于持久性.
结论:
- 机器学习模型对预测印度4月和5月的地表空气最大温度异常充满希望.
- 这些模型可以补充复杂的数值天气模型的预测,提高热浪准备.
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