黑海科学与创新地球观测数据框架下新的SMOS SSS地图

E. Olmedo, V. González-Gambau, A. Turiel, C. González‐Haro, Aina García-Espriu, M. Grégoire, A. Álvera-Azcárate, L. Buga, M. Rio
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引用次数: 2

摘要

摘要在欧洲空间局(ESA)名为“黑海科学与创新地球观测数据”(EO4SIBS)的区域倡议框架下,为2011-2020年黑海生成了一个新的专用土壤湿度和海洋盐度(SMOS)海面盐度(SSS)产品。检索并分布三个SMOS SSS场:分别考虑上升((Olmedo et al., 2021b), https://doi.org/10.20350/digitalCSIC/13993)和下降((Olmedo et al., 2021c), https://doi.org/10.20350/digitalCSIC/13995)卫星立交桥方向,得到0.25°× 0.25°空间分辨率栅格日图中分块SSS的二级产品;3级产品(Olmedo et al., 2021d), https://doi.org/10.20350/digitalCSIC/13996),通过结合上升和下降的卫星立交桥方向,在0.25°× 0.25°网格的9天地图中组成分层SSS;第4级产品(Olmedo et al., 2021e), https://doi.org/10.20350/digitalCSIC/13997)由0.05 × 0.0505°的每日地图组成,这些地图是通过合并第3级SSS产品和海表温度(SST)地图计算得到的。在黑海产生SMOS SSS场需要使用改进的数据处理算法来改善该地区的亮度温度,因为该盆地通常受到射频干扰(RFI)源的强烈影响,阻碍了盐度的检索。在此,我们介绍了提高该盆地盐度检索质量的算法。EO4SIBS SMOS SSS产品的验证是通过以下方式进行的:i)将EO4SIBS SMOS SSS产品与现场测量提供的近地表盐度测量结果进行比较;Ii)通过将产品与模式和其他卫星盐度测量值进行比较,评估产品的地球物理一致性;iii)利用关联三重搭配分析法计算SSS误差图。EO4SIBS SMOS SSS产品的精度取决于时间周期和产品级别。2016-2020年期间的精度优于2011-2015年,不同产品的精度如下:i)二级上升:1.85 / 1.50 psu (2011-2015 / 2016-2020);二级下降:2.95 1.95 psu;ii)三级:0.7 / 0.5 psu;iii) 4级:0.6 / 0.4 psu。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New SMOS SSS maps in the framework of the Earth Observation data For Science and Innovation in the Black Sea
Abstract. In the framework of the European Space Agency (ESA) regional initiative called Earth Observation data For Science and Innovation in the Black Sea (EO4SIBS), a new dedicated Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) product is generated for the Black Sea for the years 2011–2020. Three SMOS SSS fields are retrieved and distributed: a level 2 product consisting of binned SSS in daily maps at 0.25° × 0.25° spatial resolution grid by considering ascending ((Olmedo et al., 2021b), https://doi.org/10.20350/digitalCSIC/13993) and descending ((Olmedo et al., 2021c), https://doi.org/10.20350/digitalCSIC/13995) satellite overpass directions separately; a level 3 product ((Olmedo et al., 2021d), https://doi.org/10.20350/digitalCSIC/13996) consisting of binned SSS in 9-day maps at 0.25° × 0.25° grid by combining as cending and descending satellite overpass directions; and a level 4 product ((Olmedo et al., 2021e), https://doi.org/10.20350/digitalCSIC/13997) consisting of daily maps at 0.05 × 0.0505° that are computed by merging the level 3 SSS product with Sea Surface Temperature (SST) maps. The generation of SMOS SSS fields in the Black Sea requires the use of enhanced data processing algorithms for improving the Brightness Temperatures in the region since this basin is typically strongly affected by Radio Frequency Interference (RFI) sources which hinders the retrieval of salinity. Here, we describe the algorithms introduced to improve the quality of the salinity retrieval in this basin. The validation of the EO4SIBS SMOS SSS products is performed by: i) comparing the EO4SIBS SMOS SSS products with near-to-surface salinity measurements provided by in situ measurements; ii) assessing the geophysical consistency of the products by comparing them with a model and other satellite salinity measurements; iii) computing maps of SSS errors by using Correlated Triple Collocation analysis. The accuracy of the EO4SIBS SMOS SSS products depend on the time period and on the product level. The accuracy in the period 2016–2020 is better than in 2011–2015 and it is as follows for the different products: i) Level 2 ascending: 1.85 / 1.50 psu (in 2011–2015 / 2016–2020); Level 2 descending: 2.95 1.95 psu; ii) Level 3: 0.7 / 0.5 psu; and iii) Level 4: 0.6 / 0.4 psu.
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