基于卫星数据合成的地面太阳光谱仪测量的大气气溶胶粒径分布研究

Dane Kuhr, A. Whitten
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引用次数: 0

摘要

MN Collegeville的地面太阳光谱仪收集的数据用于生成2017日历年的气溶胶光学深度(AOD)。然后,在全年13个选定波长下对AOD数据进行可视化,并与卫星图像、高空图和向明尼苏达州中部移动的气团的向后轨迹进行比较分析,以确定与之前(20170615)、期间(20170729)、,以及在2017年夏天不列颠哥伦比亚省(BC)发生的(20170914)森林大火结束时。通过将每天的最大和最小AOD输入到基于参数的粒子群优化(PBPSO)算法中,进一步分析这些特定日子的数据,以生成双峰对数正态粒度分布。之所以选择双峰分布,是因为它们在整个粒子半径谱中携带了更多关于气溶胶载荷的信息。由此产生的分布显示,在不列颠哥伦比亚省森林火灾期间,艾特肯模式的数量密度增加,中值半径减小,并且在日最大AOD下,积累模式粒子的数量密度相对恒定(在不确定性范围内)。比较由此产生的日最小AOD的双峰对数正态分布(其中蒸发和其他日效应最小)表明,从森林火灾前到火灾后,艾特肯模式粒子的数量密度增加了两个数量级。森林火灾导致的较小半径颗粒数量密度的测量增加表明,基于Kipp-Zonen PGS-100太阳能光谱仪收集的数据,PBPSO能够区分艾特肯模式下大气气溶胶颗粒数量大小分布的变化。关键词:大气气溶胶;粒子群优化;气溶胶光学深度;太阳光谱仪;规模分布;森林火灾;卫星图像;高空图表;向后轨迹
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of Atmospheric Aerosol Size Distributions from Ground-Based Solar Spectrometer Measurements Synthesized with Satellite Data
Data collected by a ground-based solar spectrometer at Collegeville, MN, was used to generate Aerosol Optical Depths (AODs) throughout the 2017 calendar year. The AOD data was then visualized at 13 selected wavelengths throughout the year and analyzed in comparison to satellite imagery, upper air charts and backwards trajectories of air masses moving towards Central Minnesota in order to determine key dates of interest that correspond to times before (20170615), during (20170729), and at the conclusion of (20170914) forest fires that burned in British Columbia (BC) during the summer of 2017. The data from these specific days were analyzed further by inputting the maximum and minimum AODs for each day into a Parameter Based Particle Swarm Optimization (PBPSO) algorithm in order to generate bimodal lognormal particle size distributions. The bimodal distributions were chosen because they carry more information about the aerosol loads across the entire spectrum of particle radii. The resulting distributions show an increase in number density and decrease in median radius in the Aitken mode during the BC forest fires and a relatively constant (within uncertainty) number density of accumulation mode particles at daily maximum AODs. Comparing the resulting bimodal lognormal distribution for daily minimum AODs (where evaporation and other diurnal effects are at a minimum) shows an increased number density of Aitken mode particles by two orders of magnitude from pre- to post-forest fires. This measured increase in the number density of smaller radii particles due to forest fires illustrates the PBPSO’s capability of distinguishing variations in atmospheric aerosol particle number size distributions in the Aitken mode based on data collected by the Kipp-Zonen PGS-100 solar spectrometer. KEYWORDS: Atmospheric Aerosol; Particle Swarm Optimization; Aerosol Optical Depth; Solar Spectrometer; Size Distributions; Forest Fire; Satellite Imagery; Upper Air Charts; Backward Trajectory
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