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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Validation of SOAR VIIRS Over-Water Aerosol Retrievals and ContextWithin the Global Satellite Aerosol Data Record
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Validation of SOAR VIIRS Over-Water Aerosol Retrievals and ContextWithin the Global Satellite Aerosol Data Record

机译:验证飙升VIIRS水上气溶胶检索和ContextWithin全球卫星气溶胶数据记录

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摘要

This study validates aerosol properties retrieved using a Satellite Ocean Aerosol Retrieval (SOAR) algorithm applied to Visible Infrared Imaging Radiometer Suite (VIIRS) measurements, from Version 1 of the VIIRS Deep Blue data set. SOAR is the over-water complement to the over-land Deep Blue algorithm and has two processing paths: globally, 95% of pixels are processed with the full retrieval algorithm, while the 5% of pixels in shallow or turbid (mostly coastal) waters are processed with a backup algorithm. Aerosol Robotic Network (AERONET) data are used to validate and compare the midvisible (550 nm) aerosol optical depth (AOD), ?ngstr?m exponent (AE), and fine mode fraction of AOD at 550 nm (FMF). AOD uncertainty is shown to be approximately ±(0.03 + 10%) for the full and ±(0.03 + 15%) for the backup algorithms, with a small positive median bias around 0.02. When AOD is below about 0.2, the AE and FMF have small negative offsets from AERONET around -0.15 and -0.04, respectively. For higher AOD, AE is less offset and the magnitudes of differences versus AERONET are about ±0.2 and ±0.14, respectively. Aerosol-type classifications provided by SOAR are found to be reasonable, matching optical-based classifications from AERONET over 80% of the time. Spatial and temporal patterns of AOD and AE are also compared with those of other contemporary over-water satellite aerosol data sets; dependent on region, the satellite data sets show varying levels of consistency, with SOAR broadly in-family, and the largest discrepancies in regions with persistent heavy cloud cover.
机译:本研究验证气溶胶属性检索使用卫星海洋气溶胶检索(上升)算法应用于可见光红外成像辐射计(VIIRS)测量VIIRS深蓝的第1版数据集。是水上的补充在陆地上深蓝算法和有两个加工路径:在全球范围内,95%的像素处理完整的检索算法,而5%的像素在浅或浑浊的(主要是沿海)水域处理一个备份算法。用于机器人网络(AERONET)数据验证和比较midvisible(550海里)气溶胶光学厚度(AOD) ngstr ?(AE)和细模式大气气溶胶的分数550海里(FMF)。约±0.03(+ 10%)和±0.03(+ 15%)备份算法,用小正的平均偏差约为0.02。低于0.2,AE和FMF小从AERONET约-0.15和负的偏移量-0.04,分别。与偏移量的大小差异AERONET分别约±0.2±0.14。Aerosol-type分类提供了飙升发现合理、匹配optical-based从AERONET超过80%的分类时间。也与其他的吗现代水上卫星气溶胶数据集;集显示不同程度的一致性翱翔一般在家庭,和最大的地区差异与持久的沉重云层。

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