Application of the Complete Data Fusion algorithm to the ozone profiles measured by geostationary and low-Earth-orbit satellites: A feasibility study

Nicola Zoppetti*, Simone Ceccherini, Bruno Carli, Samuele Del Bianco, Marco Gai, Cecilia Tirelli, Flavio Barbara, Rossana Dragani, Antti Arola, Jukka Kujanpää, Jacob C.A. Van Peet, A. Van Der Ronald, Ugo Cortesi

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The new platforms for Earth observation from space are characterized by measurements made at great spatial and temporal resolutions. While this abundance of information makes it possible to detect and study localized phenomena, it may be difficult to manage this large amount of data for 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 in the future. A simple procedure to overcome this problem is to extract a subset of the original measurements, but this involves a loss of information. Another option is the use of simple averages of the profiles, but this approach also has some limitations that we will discuss in the paper. A more advanced solution is to resort to the so-called fusion algorithms, capable of compressing the size of the dataset while limiting the information loss. A novel data fusion method, the Complete Data Fusion algorithm, was recently developed to merge a set of retrieved products in a single product a posteriori. In the present paper, we apply the Complete Data Fusion method to ozone profile measurements simulated in the thermal infrared and ultraviolet bands in a realistic scenario. Following this, the fused products are compared with the input profiles; comparisons show that the output products of data fusion have smaller total errors and higher information contents in general. The comparisons of the fused products with the fusing products are presented both at single fusion grid box scale and with a statistical analysis of the results obtained on large sets of fusion grid boxes of the same size. We also evaluate the grid box size impact, showing that the Complete Data Fusion method can be used with different grid box sizes even if this possibility is connected to the natural variability of the considered atmospheric molecule.

Original languageEnglish
Pages (from-to)2041-2053
Number of pages13
JournalAtmospheric Measurement Techniques
Volume14
Issue number3
DOIs
Publication statusPublished - 12 Mar 2021

Bibliographical note

Funding Information:
Acknowledgements. The results presented in this paper arise from research activities conducted in the framework of the AURORA project (http://www.aurora-copernicus.eu/, last access: 29 December 2020) supported by the Horizon 2020 research and innovation programme of the European Union (Call H2020-EO-2015; Topic EO-2-2015) under grant agreement no. 687428.

Funding Information:
Financial support. This research has been supported by the Hori-

Funding Information:
This work is based on the simulated data produced in the context of the Advanced Ultraviolet Radiation and Ozone Retrieval for Applications project (AURORA; Cortesi et al., 2018), funded by the European Commission in the frame-work of the Horizon 2020 programme. The project regards the sequential application of fusion and assimilation algo- rithms to ozone profiles simulated according to specifications similar to those of the atmospheric Sentinels.

Publisher Copyright:
© Author(s) 2021.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Funding

Acknowledgements. The results presented in this paper arise from research activities conducted in the framework of the AURORA project (http://www.aurora-copernicus.eu/, last access: 29 December 2020) supported by the Horizon 2020 research and innovation programme of the European Union (Call H2020-EO-2015; Topic EO-2-2015) under grant agreement no. 687428. Financial support. This research has been supported by the Hori- This work is based on the simulated data produced in the context of the Advanced Ultraviolet Radiation and Ozone Retrieval for Applications project (AURORA; Cortesi et al., 2018), funded by the European Commission in the frame-work of the Horizon 2020 programme. The project regards the sequential application of fusion and assimilation algo- rithms to ozone profiles simulated according to specifications similar to those of the atmospheric Sentinels.

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