The Complete Data Fusion for the improvement of Sentinel 4 and Sentinel 5 products

AURORA is a project financed by the European Commission in the framework of the Horizon 2020 Framework Program that concerns the sequential application of fusion and assimilation algorithms to simulated ozone profiles in different spectral bands, according to the specifications of atmospheric Sentinels 4 and 5(p). It is known that the atmospheric Sentinels will provide an enormous amount of data with unprecedented spatial and temporal resolution. In this scenario, a central challenge to face is to enable a generic data user (for example, an assimilation system) to ingest such a large amount of data without loss of information. In this sense, an algorithm such as the Complete Data Fusion (CDF) is particularly interesting as it is able to reduce, without loss of information, the data volume of input products that correspond to the same space and time location. CDF accepts as input a generic number of Level 2 products, retrieved with optimal estimation techniques. Each of these products is represented by a volume mixing ratio profile characterized by its covariance matrix, its averaging kernel matrix and the a priori information used in the retrieval. The output of the fusion is a single product that has the same structure and collects all the information of the input products. This work is divided in two parts. The first part, which consider the fusion of 1000 coincident pixels simulated with different errors, aims to show that the CDF is, to our knowledge, the only known algorithm able to correctly combine the information of several coincident measurements into a single product, taking into account the a priori information. The same a priori information introduces a bias if, for example, the arithmetic averages of the input profiles are considered. In the second part of the work, the products obtained by fusing not perfectly co-located simulated ozone profiles in TIR and UV bands are analyzed. In particular, the characteristics of these products are compared with those of the original products that have been fused. This comparison is aimed at highlighting the better data exploitation provided by the fusion. The second part also shows that the CDF can be applied with different coincidence grid cell sizes, for example to match the size of an assimilation grid, leading to different compression factors of the original Level 2 data volume. These results highlight the importance of the data fusion procedure in the management of large data volumes, such as those provided by the atmospheric Sentinels.