AERONET-OC 巴伊亚布兰卡附近河口和沿海水域的光学水特征和大气校正评估

Maximiliano Arena, Paula Pratolongo, H. Loisel, Manh Duy Tran, D. Jorge, Ana Laura Delgado
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引用次数: 0

摘要

AERONET-OC 巴伊亚布兰卡站(BB-AERONET-OC)位于阿根廷巴伊亚布兰卡河口(大西洋 西南部),这是一个以高悬浮物和相对较低的有色溶解有机物为特征的沿岸系统。这些水域典型的高浊度使 BB-AERONET-OC 在 AERONET-OC 网络站中独树一帜,不仅为验证大气校正算法,而且为开发沿岸复杂水域的区域算法提供了难得的机会。SeaWiFS 入射面测量光度计修订版(SeaPRISM)仪器于 2020 年 1 月部署在 Mareograph 塔的上部导轨上,Mareograph 塔高 15 米,距离海岸 10 英里,位于光学深度水域。在这项工作中,我们利用 BB-AERONET-OC 测量得出的遥感反射率(Rrs)和现场高光谱辐射测量数据对光学水类型(OWT)进行了分类。我们将每个 Rrs(λ) 光谱归入 Tran 等人定义的五种 OWT 之一,并根据与辐射光谱同时获得的水样中光学重要成分(叶绿素-a 和悬浮颗粒物)的浓度和固有光学特性(浮游植物、非藻类颗粒物和溶解有机物的吸收)进一步确定 OWT 的特征。根据与现场数据的比对,对哨兵-3 海洋和陆地色彩仪器(OLCI)图像采用了不同的大气校正方法方案。欧洲空间局(ESA)标准(以下简称 "标准神经网络(NN)")的运行产品 OLCI 2 级被证明是最合适的大气校正算法,随后被用于描述该地区不同 OWT 的空间模式和时间变化。BB-AERONET-OC 站点位于河口水域和沿岸水域之间的急剧过渡区,这两个水域的光 学条件截然不同:随着时间的推移,OWT 4 占主导地位(占观测数据的 73.72%),其次是 OWT 3(24.74%)和 OWT 5(1.53%)。OWT 4 和 5 与巴伊亚布兰卡河口的浑浊水域有关,尤其是 OWT 5,它是河口内侧非常浑浊水域的典型代表,其颗粒物主要是矿物沉积物和碎屑。OWT 3 则描绘了内陆架富营养化的沿岸水域。OWTs 的变化以及悬浮物质中有机和无机化合物的相对比例,主要与该地区盛行的西北风 有关,西北风将推动河口沉积物向陆架输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optical water characterization and atmospheric correction assessment of estuarine and coastal waters around the AERONET-OC Bahia Blanca
The site AERONET-OC Bahía Blanca (BB-AERONET-OC) is located at the mouth of the Bahía Blanca Estuary, Argentina (Southwestern Atlantic Ocean), a coastal system defined by its high suspended loads and relatively low colored dissolved organic matter. The typically high turbidity of these waters makes the BB-AERONET-OC distinctive within the AERONET-OC network stations, providing exceptional opportunities not only for the validation of atmospheric correction algorithms but also for the development of regional algorithms for coastal complex waters. A SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM) instrument was deployed in January 2020 in the upper rail of a Mareograph Tower, a 15 m tall structure, located 10 miles away from the coast in optically deep waters. In this work we used the remote sensing reflectance (Rrs) derived from the BB-AERONET-OC measurements along with in situ hyperspectral radiometric data to classify optical water types (OWTs). We assigned each Rrs(λ) spectra to one of the five OWTs defined by Tran et al., and OWTs were further characterized with the concentrations of optically significant components (chlorophyll-a and suspended particulate matter) and inherent optical properties (absorptions of phytoplankton, non-algal particles, and dissolved organic matter), retrieved from water samples obtained simultaneously with radiometric spectra. Based on a match-up exercise with in situ data, different schemes of atmospheric correction methods were applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. The operational product OLCI Level 2 European Space Agency (ESA) standard (hereafter referred to as “Standard Neural Network (NN)”) proves to be the most suitable atmospheric correction algorithm, which was then used to describe spatial patterns and temporal variability of the different OWTs in the region. The BB-AERONET-OC site is located in a sharp transition between estuarine and coastal waters that present contrasting optical conditions: OWT 4 dominates over time (73.72% of the observations), followed by OWT 3 (24.74%) and OWT 5 (1.53%). OWTs 4 and 5 are associated with turbid waters of the Bahía Blanca Estuary, especially OWT 5, which typifies the very turbid waters from the inner estuary, with the particulate load dominated by mineral sediments and detritus. OWT 3, in turn, depicts the eutrophic coastal waters of the inner shelf. The variability of OWTs and the relative contribution of organic and inorganic compounds to the suspended material would be mostly related with the prevalence of northwest winds in the area, which would drive the export of estuarine sediments to the shelf.
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