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在东南对流层气溶胶和化学研究期间,利用高空间分辨率飞机遥感探测云附近的气溶胶。

Exploring aerosols near clouds with high-spatial-resolution aircraft remote sensing during SEACRS.

作者信息

Spencer Robert S, Levy Robert C, Remer Lorraine A, Mattoo Shana, Arnold George T, Hlavka Dennis L, Meyer Kerry G, Marshak Alexander, Wilcox Eric M, Platnick Steven E

机构信息

Science Systems and Applications, Inc, Lanham, Maryland, USA.

Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, MD, USA.

出版信息

J Geophys Res Atmos. 2019 Feb 27;124(4):2148-2173. doi: 10.1029/2018jd028989. Epub 2019 Jan 28.

DOI:10.1029/2018jd028989
PMID:32676260
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7365256/
Abstract

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satellite-borne Moderate-resolution Imaging Spectroradiometer (MODIS), the Dark Target (DT) retrieval algorithm provides global aerosol optical depth (AOD at 0.55 μm) in cloud-free scenes. Since MODIS' resolution (500 m pixels, 3 km or 10 km product) is too coarse for studying near-cloud aerosol, we ported the DT algorithm to the high-resolution (~50 m pixels) enhanced-MODIS Airborne Simulator (eMAS), which flew on the high-altitude ER-2 during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEACRS) Airborne Science Campaign over the U.S. in 2013. We find that even with aggressive cloud screening, the ~0.5 km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degraded-resolution AOD), co-registered Cloud Physics Lidar (CPL) profiles, MODIS aerosol retrievals, and ground-based Aerosol Robotic Network (AERONET) observations. We also define spatial metrics to indicate local cloud distributions near each retrieval, and then separate into near-cloud and far-from-cloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clear-cloud transition zone microphysics such as aerosol swelling. However, 3D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds.

摘要

由于气溶胶对我们的气候系统至关重要,我们试图观测云系统中气溶胶特性的变化。当应用于卫星搭载的中分辨率成像光谱仪(MODIS)时,暗目标(DT)反演算法可在无云场景中提供全球气溶胶光学厚度(0.55μm处的AOD)。由于MODIS的分辨率(500米像素、3千米或10千米产品)对于研究近云气溶胶来说过于粗糙,我们将DT算法移植到了高分辨率(约50米像素)的增强型MODIS机载模拟器(eMAS)上,该模拟器在2013年美国进行的区域调查排放、大气成分、云和气候耦合研究(SEACRS)机载科学活动期间搭载在高空ER-2飞机上飞行。我们发现,即使进行了积极的云筛选,约0.5千米的eMAS反演结果显示AOD有所增强,尤其是在检测到的云的6千米范围内。为了确定AOD增强的原因,我们分析了额外的eMAS产品(云反演和降分辨率AOD)、配准的云物理激光雷达(CPL)剖面、MODIS气溶胶反演结果以及地基气溶胶机器人网络(AERONET)观测数据。我们还定义了空间指标来指示每个反演附近的局部云分布,然后将其分为近云环境和远云环境。比较结果表明,低云掩膜是可靠的,未筛选的薄卷云对反演的AOD影响较小。部分增强与晴空-云过渡区微物理过程(如气溶胶膨胀)一致。然而,云与周围晴空之间的三维辐射相互作用似乎是云附近AOD较高的主要原因。

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2
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Atmos Meas Tech. 2016;9(4):1743-1753. doi: 10.5194/amt-9-1743-2016. Epub 2016 Apr 20.
5
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6
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