从基于机器学习的天气系统的角度来看,改善雨季和温暖季节的臭氧估计
Zhixuan Tong1, Yingying Yan2, Shaofei Kong2
1Department of Atmospheric Science, School of Environmental Sciences, China University of Geosciences, Wuhan 430074, China.
The Science of the total environment
|December 13, 2024
概括
中国东部的高表面臭氧污染发生在梅雨季,由特定的气象条件和大气循环驱动. 纳入大气循环指数可以提高臭氧预测的准确性.
科学领域:
- 大气化学和物理大气化学和物理
- 环境科学 环境科学
- 气候科学 气候科学
背景情况:
- 表面臭氧污染在中国东部越来越令人担忧,尤其是在夏季.
- 臭氧水平表现出与区域雨季,特别是梅雨时期相关的独特模式.
研究的目的:
- 调查梅雨季 (2015-2022) 期间臭氧度的时空分布.
- 为了确定影响臭氧水平的同视觉驱动因素.
- 用气象和大气循环数据估计臭氧度.
主要方法:
- 在梅时期对臭氧度 (MDA8 O3) 的分析,区分高臭氧时期 (HOP) 和非高臭氧时期 (NHOP).
- 气象数据分析 (降水量,温度,太阳辐射,相对湿度).
- 应用林德曼,梅伦达和戈尔德方法来评估气象因素的影响.
- 与近视尺度和大规模大气循环系统 (西太平洋亚热带大气,ENSO,东亚夏季季风) 的相关性分析.
- 机器学习模型用于估计臭氧度.
主要成果:
- 在梅季 (HOP) 间隔期间观察到高臭氧水平,占该时期的15.1%,在大多数地点的度超过NHOP20微克/m3.
- 与NHOP相比,HOP的特点是降水量较低,温度更高,太阳辐射增加,相对湿度降低.
- MDA8 O3的主要气象驱动因素是相对湿度 (30.4%),表面2m温度 (28.6%) 和总降水量 (23.2%).
- 西太平洋亚热带地区的南方位置 高度和更强 ENSO/东亚夏季季风强度与较高的臭氧相关.
- 结合大气循环指数的机器学习模型显著提高了臭氧估计准确度 (R2: 0.72,NRMSE: 0.15).
结论:
- 在梅雨区间期间的特定气象条件有利于表面臭氧的升高.
- 大气循环模式在此期间在推动臭氧污染方面发挥着至关重要的作用.
- 将大气循环指数整合到模型中,可以更好地预测梅雨季的臭氧污染.
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