人工智能预测2023年印度的夏季季风雨将在2023年达到正常水平
Udit Narang1, Kushal Juneja1, Pankaj Upadhyaya2
1Department of Computer Science and Engineering, Indraprastha Institute of Information Technology Delhi, Delhi, India.
Scientific reports
|January 17, 2024
概括
机器学习模型准确预测全印度夏季季风雨 (AISMR). 这些数据驱动的方法优于传统方法,预测2023年典型的季风.
科学领域:
- 气候科学 气候科学
- 气象学 天气学
- 数据科学数据科学数据科学
背景情况:
- 准确的全印度夏季季风降雨 (AISMR) 预测对印度的经济和人口至关重要.
- 提高AISMR预测准确性是一个重大的科学挑战.
研究的目的:
- 为了提高全印度夏季季风降雨 (AISMR) 预报的准确性.
- 探索机器学习技术在季风预测中的有效性.
主要方法:
- 使用历史AISMR数据开发数据驱动模型.
- 将纳入Niño3.4指数和印度洋双极 (IOD) 分类值纳入模型.
- 将机器学习模型的性能与传统物理模型进行比较.
主要成果:
- 与传统的物理模型相比,数据驱动模型显示出更高的性能.
- 性能最好的机器学习模型预测2023年AISMR大约为790毫米.
- 预测的降雨量表明一个典型的季风年.
结论:
- 机器学习技术为改善AISMR预测提供了一个有希望的进步.
- 数据驱动的方法可以更准确地预测季风降雨模式.
- 准确的季风预报可以减轻印度的社会经济影响.
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