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基于时代网的热带顶点湿延迟的短期预测
Xuan Zhao1, Shouzhou Gu1,2, Jinzhong Mi1
1Chinese Academy of Surveying and Mapping, Beijing 100036, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
这项研究介绍了TimesNet用于预测热层顶点湿延迟 (ZWD),这对于大气水蒸气逆转和降雨预测至关重要. 与现有模型相比,TimesNet显著提高了各种条件的预测准确性和适应性.
科学领域:
- 地质测量和大气科学
- 气象预报 气象预报
- 机器学习在地质科学中的应用
背景情况:
- 热带球顶湿延迟 (ZWD) 对大气水蒸气逆转和短期降雨预测至关重要.
- 传统的ZWD预测模型在处理非静态性和局部特征提取方面存在局限性.
- 准确的ZWD预测对于提高气象预报的准确性至关重要.
研究的目的:
- 开发和评估一种新的ZWD预测方法,使用TimesNet的动态时间分解模块.
- 通过将时间序列数据重建为张量器来提高ZWD预测的准确性和适应性.
- 评估TimesNet与传统模型 (CNN-ATT,Informer) 的性能,同时考虑各种环境因素.
主要方法:
- 使用TimesNet将1D ZWD时间序列重构为2D张量.
- 将地形,气候和季节因素整合到预测模型中.
- 对时代网与CNN-ATT和Informer的比较分析,使用来自不同季节的20个IGS站的30秒ZWD数据.
主要成果:
- 时代网的季节性平均根平均平方误差 (RMSE) 为5.73毫米,超过了Informer (7.89毫米) 和CNN-ATT (10.02毫米).
- 该模型表现出优越的季节性适应性和地形稳定性,在具有挑战性的环境中保持高精度.
- 在稳定的气象条件下实现了低于5毫米的精度,突出显示了TimesNet的可靠性.
结论:
- 时代网为实时气象应用提供了可靠的算法基础,特别是短期降水预报.
- 动态时间分解方法有效地解决了ZWD数据的非静止性.
- 这种方法增强了全球导航卫星系统 (GNSS) 气象学的潜力,以改善天气预报.
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