The Complete Data Fusion for a Full Exploitation of Copernicus Atmospheric Sentinel Level 2 Products

Abstract. The new platforms for Earth observation from space are characterized by measurements made with great spatial and temporal resolution. While this abundance of information makes it possible to detect and study localized phenomena, on the other hand it may be difficult to manage this large amount of data in the study of global and large scale phenomena.

A particularly significant example is the use by assimilation systems of level 2 products that represent gas profiles in the atmosphere. The models on which assimilation systems are based are discretized on spatial grids with horizontal dimensions of the order of tens of kilometres in which tens or hundreds of measurements may fall.

A simple procedure to overcome this problem is to extract a subset of the original measurements. However, this procedure involves a loss of information and is therefore justifiable only as a temporary solution. A more refined solution is to resort to the so-called fusion algorithms, capable of compressing the size of the dataset limiting the information loss. A novel data fusion method, the Complete Data Fusion, was recently developed to merge a-posteriori a set of retrieved products in a single one. In the present paper, the Complete Data Fusion method is applied to ozone profile measurements simulated in the thermal infrared and ultraviolet bands, in a realistic scenario, according to the specifications of the Sentinel 4 and 5 missions of the Copernicus programme. Then the fused products are compared with the input profiles; comparisons show that the output products of data fusion have in general smaller errors and higher information contents. The most significant improvement is an increased vertical resolution together with a reduction of the errors. The comparisons of the fused with the fusing products are presented both at single fusion grid-box scale and with a statistical analysis. The grid box size impact was also evaluated, showing that the Complete Data Fusion method can be used with a wide range of grid-box size, the quality of the products improving with larger grid boxes.