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Estimating marine aerosol particle volume and number from Maritime Aerosol Network data

机译:从海上气溶胶网络数据估算海洋气溶胶颗粒的数量和数量

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As well as spectral aerosol optical depth (AOD), aerosol composition and concentration (number, volume, or mass) are of interest for a variety of applications. However, remote sensing of these quantities is more difficult than for AOD, as it is more sensitive to assumptions relating to aerosol composition. This study uses spectral AOD measured on Maritime Aerosol Network (MAN) cruises, with the additional constraint of a microphysical model for unpolluted maritime aerosol based on analysis of Aerosol Robotic Network (AERONET) inversions, to estimate these quantities over open ocean. When the MAN data are subset to those likely to be comprised of maritime aerosol, number and volume concentrations obtained are physically reasonable. Attempts to estimate surface concentration from columnar abundance, however, are shown to be limited by uncertainties in vertical distribution. Columnar AOD at 550 nm and aerosol number for unpolluted maritime cases are also compared with Moderate Resolutio Imaging Spectroradiometer (MODIS) data, for both the present Collection 5.1 and forth-coming Collection 6. MODIS provides a best-fitting retrieval solution, as well as the average for several different solutions, with different aerosol microphysical models. The "average solution" MODIS dataset agrees more closely with MAN than the "best solution" dataset. Terra tends to retrieve lower aerosol number than MAN, and Aqua higher, linked with differences in the aerosol models commonly chosen. Collection 6 AOD is likely to agree more closely with MAN over open ocean than Collection 5.1. In situations where spectral AOD is measured accurately,and aerosol microphysical properties are reasonably well-constrained, estimates of aerosol number and volume using MAN or similar data would provide for a greater variety of potential comparisons with aerosol properties derived from satellite or chemistry transport model data. However, without accurate AOD data and prior knowledge of microphysical properties, such attempts are fraught with high uncertainties.
机译:除光谱气溶胶光学深度(AOD)以外,气溶胶成分和浓度(数量,体积或质量)对于各种应用也很重要。但是,这些量的遥感比AOD的遥感更为困难,因为它对与气溶胶成分有关的假设更为敏感。这项研究使用了在海上气溶胶网络(MAN)航行中测得的光谱AOD,并基于对气溶胶机器人网络(AERONET)的反演分析,对未污染的海洋气溶胶进行了微物理模型的附加约束,以估算这些海洋上的数量。当MAN数据是可能由海洋气溶胶组成的数据的子集时,获得的数量和体积浓度在物理上是合理的。然而,从柱状丰度估算表面浓度的尝试受到垂直分布不确定性的限制。对于当前的第5.1版和即将发布的第6种集合,还将未污染的海事案例的550 nm柱状AOD和气溶胶数量与中等分辨成像光谱仪(MODIS)的数据进行了比较,MODIS提供了最适合的检索解决方案,以及不同气溶胶微物理模型的几种不同解决方案的平均值。与“最佳解决方案”数据集相比,“平均解决方案” MODIS数据集与MAN更加一致。与通常选择的气溶胶模型的差异有关,Terra的气溶胶数比MAN少,而Aqua的气溶胶数更高。收集6 AOD可能比收集5.1更与MAN在公海有关。在准确测量光谱AOD且合理地限制了气溶胶微物理特性的情况下,使用MAN或类似数据估算气溶胶数量和体积将提供与从卫星或化学传输模型数据得出的气溶胶特性进行更多潜在的比较。 。然而,由于缺乏准确的AOD数据和对微物理性质的事先了解,这种尝试充满了高度的不确定性。

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