北京地区气溶胶与水汽垂直廓线协变关系分析
Analysis of Covariance Relationship between Aerosol and Water Vapor Vertical Distributions in Beijing
郭磐 1王佳男 1檀望舒 1陈思颖 2陈和 2徐清玥 1杨皓凯 1李加俊3
作者信息
- 1. 北京理工大学光电学院,北京 100081
- 2. 北京理工大学光电学院,北京 100081;北京理工大学长三角研究院(嘉兴),浙江 嘉兴 314019
- 3. 北京理工大学长三角研究院(嘉兴),浙江 嘉兴 314019;北京理工大学光电学院,北京 100081
- 折叠
摘要
了解气溶胶与水汽之间的动态关系对于揭示大气过程、评估环境变化及预测气候系统的响应至关重要.依据2023年北京地区激光雷达的连续观测数据,分析气溶胶后向散射比和水汽质量混合比廓线的相关性及变化规律.研究揭示了气溶胶和水汽在分布上的一致性及其协同变化特征,发现这种相关性受到季节、气团所处高度和其来源的显著影响.数据统计分析结果表明,在 0.2～1 km的垂直范围内,气溶胶后向散射比和水汽质量混合比廓线的相关系数超过0.9,表现出显著相关性.特别是来自西北部的气团中,两廓线的相关性高于其他来源.分层统计结果表明,随着高度的增加,两廓线的相关性逐渐减弱.分季统计结果表明,秋冬两季两廓线相关性高于春夏两季.该研究为理解大气中气溶胶与水汽的相互作用提供了新的视角,对于改善大气模型和气候变化预测具有重要意义.
Abstract
Elucidating the dynamic relationship between aerosols and water vapor is crucial for revealing atmospheric processes,assessing environmental changes,and predicting climate system responses.Based on continuous lidar observations in Beijing during 2023,this study analyzed the correlation and variation patterns between aerosol backscatter ratio and water vapor mixing ratio profiles.Results reveal the consistency in the distribution and co-variation characteristics of aerosols and water vapor,where the correlation is significantly influenced by the season and both the heights and sources of air masses.Statistical analysis of the data shows that within the vertical range of 0.2‒1 km,the correlation coefficient between the aerosol backscatter and water vapor mixing ratios exceeds 0.9,indicating a significant correlation.Notably,air masses from the northwest exhibit a higher correlation between these two factors as compared with other sources.Layered statistical results indicate that the correlation between aerosols and water vapor gradually weakens with increasing height.The seasonal statistics indicate that the correlation between the two profiles during autumn and winter is higher than that during spring and summer.These findings provide a new understanding of the interaction between aerosols and water vapor in the atmosphere,which is of great significance for improving atmospheric models and climate change predictions.
关键词
遥感/激光雷达/气溶胶/水汽/相关性Key words
remote sensing/lidar/aerosol/water vapor/relevance引用本文复制引用
出版年
2024
NETL
NSTL
万方数据